Articles in Refereed Journals

  1. R. Grossman, A note on the application of Morse theory to the study of the potential extrema of body surface potential maps, Volume 11, 1978, pages 201-202. pdf

  2. M. Beals, C. Fefferman, R. Grossman, Strictly pseudoconvex domains in Cn, Bulletin American Mathematical Society, Volume, 8, 1983, pages 125-322. pdf

  3. R. Grossman and R. Larson, Hopf algebraic structures of families of trees, Journal Algebra, Volume 26, 1989, pages 184-210. pdf

  4. R. Grossman and R. Larson, Hopf-algebraic structure of combinatorial objects and differential operators, Israel Journal Mathematics, Volume 72, 1990, pages 109-117. pdf

  5. Matt Grayson and Robert Grossman, Models for free, nilpotent Lie algebras, Journal Algebra, Volume 135, 1990, pages 177-191. pdf

  6. Robert Grossman and Richard Larson, Solving nonlinear equations from higher order derivations in linear stages, Advances in Mathematics, Vol. 82, 1990, pages 180-202. pdf

  7. Robert Grossman, The evaluation of expressions involving higher order derivations, Journal of Mathematical Systems, Estimation, and Control, Volume 1, 1991, pages 91-106. pdf

  8. Robert L. Grossman and Richard G. Larson, The realization of input-output maps using bialgebras, Forum Mathematicum, Volume 4, 1992, pages 109-121. (arxiv:2007.09526) pdf

  9. M. W. Bern, D. P. Dobkin, D. Eppstein, and R. Grossman, Visibility with a moving point of view, Algorithmica, Volume 11, pages 360-378, 1994. pdf

  10. Robert L. Grossman and Richard G. Larson, The symbolic computation of derivations using labeled trees, Journal of Symbolic Computation, Volume 13, pages 511-523, 1992. pdf

  11. Peter Crouch and Robert L. Grossman, Numerical integration of ordinary differential equations on manifolds, Journal of Nonlinear Science, Volume 3, pages 1-33, 1993. pdf

  12. Giuseppe Caire, Robert Grossman and H. Vincent Poor, Wavelet transforms associated with finite cyclic groups, IEEE Transactions on Information Theory, Volume 39, 1993, pp. 1157-1166. pdf

  13. Peter E. Crouch, Robert Grossman, Y. Yan, On the numerical integration of the rolling ball equations using geometrically exact algorithms, Mechanics of Structures of Machines, Volume 23, Issue 2, 1995, pages 257-272.

  14. Robert L. Grossman and Robert G. Larson, An algebraic approach to hybrid systems, Journal of Theoretical Computer Science, Volume 138, pages 101-112, 1995. pdf

  15. R. L. Grossman, Data Mining Challenges for Digital Libraries, ACM Computing Surveys, Volume 28A (electronic), December, 1996. pdf

  16. R. L. Grossman, S. Bailey, A. Ramu and B. Malhi, P. Hallstrom, I. Pulleyn and X. Qin, The Management and Mining of Multiple Predictive Models Using the Predictive Model Markup Language (PMML), Information and Software Technology, Volume 41, 1999, pages 589-595. pdf

  17. Robert Grossman, and Marco Mazzucco, DataSpace - A Web Infrastructure for the Exploratory Analysis and Mining of Data, IEEE Computing in Science and Engineering, July/August, 2002, pages 44-51. pdf

  18. Robert Grossman, Mark Hornick, and Gregor Meyer, Data Mining Standards Initiatives, Communications of the ACM, Volume 45-8, 2002, pages 59-61. pdf

  19. H. Sivakumar, R. L. Grossman, M. Mazzucco, Y. Pan, Q. Zhang, Simple Available Bandwidth Utilization Library for High-Speed Wide Area Networks, Journal of Supercomputing, Volume 34, Number 3, pages 231-242, 2005. pdf

  20. Robert L. Grossman, Yunhong Gu, Dave Hanley, Xinwei Hong, Dave Lillethun, Jorge Levera, Joe Mambretti, Marco Mazzucco, and Jeremy Weinberger, Experimental Studies Using Photonic Data Services at IGrid 2002, Journal of Future Computer Systems, 2003, Volume 19, Number 6, pages 945-955. pdf

  21. Andrei L. Turinsky and Robert L. Grossman, Intermediate Strategies: A Framework for Balancing Cost and Accuracy in Distributed Data Mining, Knowledge and Information Systems, 2004, to appear.

  22. Asvin Ananthanarayan, Rajiv Balachandran, Yunhong Gu, Robert Grossman, Xinwei Hong, Jorge Levera, Marco Mazzucco, Data Webs for Earth Science Data, Parallel Computing, Volume 29, 2003, pages 1363-1379. pdf

  23. J. Mambretti, J. Weinberger, J. Chen, E. Bacon, F. Yeh, D. Lillethun, R. Grossman, Y. Gu, M. Mazzuco, The Photonic TeraStream: Enabling Next Generation Applications Through Intelligent Optical Networking at iGrid 2002, Journal of Future Computer Systems, Elsevier Press, Volume 19, Number 6, pages 897-908. pdf

  24. Chong Zhang, Jason Leigh, Thomas A. DeFanti, Marco Mazzucco and Robert Grossman, TeraScope: Distributed Visual Data Mining of Terascale Data Sets Over Photonic Networks, Journal of Future Computer Systems, 2003, Volume 19, Number 6, pages 935-943 pdf

  25. Ian Foster and Robert L. Grossman, Data Integration in a Bandwidth Rich World, Communications ACM, Volume 46, Issue 11, November, 2003, pages 50-57. pdf

  26. A. Chien, T. Faber, A. Falk, J. Bannister, R. Grossman, J. Leigh, Transport Protocols for High Performance: Whither TCP?, Communications ACM, Volume 46, Issue 11, November, 2003, pages 42-49. pdf

  27. Robert L. Grossman, Pavan Kasturi, Donald Hamelberg, Bing Liu, An Empirical Study of the Universal Chemical Key Algorithm for Assigning Unique Keys to Chemical Compounds, Journal of Bioinformatics and Computational Biology, 2004, Volume 2, Number 1, 2004, pages 155-171. pdf

  28. Yunhong Gu and Robert L. Grossman, SABUL: A Transport Protocol for Grid Computing, Journal of Grid Computing, Volume 1, pages 377-386, 2004. pdf

  29. Bing Liu, Robert L. Grossman and Yanhong Zhai, Mining Web Pages for Data Records, IEEE Intelligent Systems, November/December, 2004, pages 49-55. pdf

  30. Robert L. Grossman, Yunhong Gu, Xinwei Hong, Antony Antony, Johan Blom, Freek Dijkstra, and Cees de Laat, Teraflows over Gigabit WANs with UDT, Journal of Future Computer Systems, Elsevier Press, Volume 21, Number 4, 2005, pages 501-513. pdf

  31. Robert L. Grossman, Yunhong Gu, Dave Hanley, Xinwei Hong and Parthasarathy Krishnaswamy, Experimental Studies of Data Transport and Data Access of Earth Science Data over Networks with High Bandwidth Delay Products, Computer Networks, Volume 46, 2004, pages 411-421. pdf

  32. Robert L. Grossman and Richard G. Larson, Differential Algebra Structures on Families of Trees, Advances in Applied Mathematics, Volume 35, pages 97-119, 2005. Also arXiv:math/0409006v1 [math.QA]. pdf

  33. Leland Wilkinson, Anushka Anand and Robert L Grossman, High-dimensional Visual Analytics: Interactive Exploration Guided by Pairwise Views of Point Distribution, IEEE Transactions on Visualization and Computer Graphics, Volume 12, Number 6, pages 1363-1372, 2006. pdf

  34. Robert L. Grossman, Yunhong Gu, David Handley, and Michal Sabala Joe Mambretti, Alex Szalay and Ani Thakar, Kazumi Kumazoe and Oie Yuji, Minsun Lee, Yoonjoo Kwon, and Woojin Seok, Data Mining Middleware for Wide Area High Performance Networks, Journal of Future Generation Computer Systems (FGCS), Volume 22, Number 8, pages 940-948, 2006. pdf

  35. Yunhong Gu and Robert L. Grossman, UDT: UDP-based Data Transfer for High-Speed Wide Area Networks, Computer Networks, Volume 51, Number 7, pages 1777-1799, 2007. pdf

  36. Robert L Grossman and Richard G. Larson, Hopf Algebras of Heap Ordered Trees and Permutations, Communications in Algebra, Volume 37, Issue 2, 2009, pages 453-459. Also arxiv.org/abs/0706.1327. pdf

  37. Robert L. Grossman, Yunhong Gu, Michael Sabala and Wanzhi Zhang, Compute and Storage Clouds Using Wide Area High Performance Networks, Journal of Future Generation Computer Systems (FGCS), Volume 25, Issue 2, 2009, pages 179-183. pdf

  38. Yunhong Gu and Robert L Grossman, Sector and Sphere: Towards Simplified Storage and Processing of Large Scale Distributed Data, Philosophical Transactions of the Royal Society A, Volume 367, Number 1897, pages 2429--2445, 2009. pdf

  39. Robert L. Grossman, The Case for Cloud Computing, IT Professional, volume 11, number 2, pages 23-27, March/April 2009. pdf

  40. Feng Tian, Parantu K Shah, Xiangjun Liu, Nicolas Negre, Jia Chen, Oleksiy Karpenko, Kevin P White, Robert L Grossman, Flynet: a genomic resource for Drosophila melanogaster transcriptional regulatory networks, Bioinformatics, Volume 25, Number 22, pages 3001-3004, 2009. pdf

  41. Feng Tian, Jia Chen, Suying Bao, Lin Shia, Xiangjun Liua, and Robert Grossman, A graph model based study on regulatory impacts of transcription factors of Drosophila melanogaster and comparison across species, Biochemical and Biophysical Research Communications, Volume 386, Issue 4, 2009, Pages 559-562. pdf

  42. Yunhong Gu, Robert Grossman, Towards Efficient and Simplified Distributed Data Intensive Computing, IEEE Transactions on Parallel and Distributed Systems, Volume 22, Issue 6, 2011, pages 974-984, [doi.ieeecomputersociety.org/10.1109/TPDS.2011.67]. pdf

  43. The modENCODE Consortium, Sushmita Roy, Jason Ernst, Peter V. Kharchenko, et. al., Identification of Functional Elements and Regulatory Circuits by Drosophila modENCODE, Science, Volume 330 (6012), pages 1787-1797, 2010, [doi:10.1126/science.1198374], PMID: 21177974. pdf

  44. Nicolas Negre, Christopher D. Brown, Lijia Ma, et. al., Cis-Regulatory Map of the Drosophila Genome, Nature, Volume 471, pages 527–531, 2011, [doi:10.1038/nature09990], PMID: 21430782. pdf

  45. Xin Feng, Robert Grossman and Lincoln Stein, PeakRanger: A cloud-enabled peak caller for ChIP-seq data, BMC Bioinformatics 2011, 12:139, doi:10.1186/1471-2105-12-139, PMCID: PMC3103446. pdf

  46. Robert L. Grossman and Kevin P. White, A vision for a Biomedical Cloud, Journal of Internal Medicine, Volume 271, Number 2, pages 122-130, 2012. PMID: 22142244. pdf

  47. Jiang ZF, Xia F, Johnson KW, Bartom E, Tuteja JH, Stevens R, Grossman RL, Brumin M, White KP, Ghanim M., Genome Sequences of the Primary Endosymbiont Candidatus Portiera aleyrodidarum in the Whitefly Bemisia tabaci B and Q Biotypes, J Bacteriol, 194(23):6678-9, 2012 Dec, doi: 10.1128/JB.01841-12. pdf

  48. McNerney ME, Brown CD, Wang X, Bartom ET, Karmakar S, Bandlamudi C, Yu S, Ko J, Sandall BP, Stricker T, Anastasi J, Grossman RL, Cunningham JM, Le Beau MM, White KP., CUX1 is a haploinsufficient tumor suppressor gene on chromosome 7 frequently inactivated in acute myeloid leukemia, Blood, 2012, PMID: 23212519 pdf

  49. David R. Blair, Christopher S. Lyttle, Jonathan M. Mortensen, Charles F. Bearden, Anders Boeck Jensen, Hossein Khiabanian, Rachel Melamed, Raul Rabadan, Elmer V. Bernstam, Søren Brunak, Lars Juhl Jensen, Dan Nicolae, Nigam H. Shah, Robert L. Grossman, Nancy J. Cox, Kevin P. White, Andrey Rzhetsky, A Non-Degenerate Code of Deleterious Variants in Mendelian Loci Contributes to Complex Disease Risk, Cell, September, 2013 pdf

  50. Daniel Mandl, Stuart Frye, Pat Cappelaere, Matthew Handy, Fritz Policelli, McCloud Katjizeu, Guido Van Langenhove, Guy Aubé, Jean-Francois Saulnier, Rob Sohlberg, Julie A. Silva, Nataliia Kussul, Sergii Skakun, Stephen G. Ungar, Robert Grossman, and Jorg Szarzynski, Use of the Earth Observing One (EO-1) Satellite for the Namibia SensorWeb Flood Early Warning Pilot, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, volume 6, number 2, April 2013, pages 298-308. pdf

  51. Allison P. Heath, Matthew Greenway, Raymond Powell, Jonathan Spring, Rafael Suarez, David Hanley, Chai Bandlamudi, Megan McNerney, Kevin White and Robert L Grossman, Bionimbus: A Cloud for Managing, Analyzing and Sharing Large Genomics Datasets, Journal of the American Medical Informatics Association, 2014. pdf

  52. Matthew Slattery, Lijia Ma, Rebecca F. Spokony, Robert K. Arthur, Pouya Kheradpour, Anshul Kundaje, Nicolas Negre, Alex Crofts, Ryan Ptashkin, Jennifer Zieba, Alexander Ostapenko, Sarah Suchy, Alec Victorsen, Nader Jameel, A. Jason Grundstad, Wenxuan Gao, Jennifer R. Moran, E. Jay Rehm, Robert L. Grossman, Manolis Kellis and Kevin P. White, Diverse patterns of genomic targeting by transcriptional regulators in Drosophila melanogaster, Genome Research, Volume 24, pages 1224-1235, 2014. pdf

  53. Robert L. Grossman and Kevin P. Siegel, Organizational Models for Big Data and Analytics, Journal of Organization Design, Volume 3, Number 1, 2014, pages 20-25. pdf

  54. Kolker Eugene, Ozdemir Vural, Martens Lennart, et. al., Toward More Transparent and Reproducible Omics Studies Through a Common Metadata Checklist and Data Publications, OMICS: A Journal of Integrative Biology, Volume 18, Issue 1, January 23, 2014 pdf

  55. Sean Peisert, William Barnett, Eli Dart, James Cuff, Robert L. Grossman, Edward Balas, Ari Berman, Anurag Shankar, and Brian Tierney, The Medical Science DMZ, Journal of the American Medical Informatics Association, 2016. pdf

  56. Robert L. Grossman, Allison Heath, Mark Murphy, Maria Patterson, and Walt Wells, A Case for Data Commons: Toward Data Science as a Service, IEEE Computing in Science and Engineering, September/October, 2016, pages 10--20. pdf

  57. Robert L. Grossman, Allison P. Heath, Vincent Ferretti, Harold E. Varmus, Douglas R. Lowy, Warren A. Kibbe, and Louis M. Staudt, Toward a Shared Vision for Cancer Genomic Data, New England Journal of Medicine, September 22, 2016, Volume 375, Number 12, pages 1109--12. pdf

  58. Maria T. Patterson, Nikolas Anderson, Collin Bennett, Jacob Bruggemann, Robert L. Grossman, Matthew Handy, Vuong Ly, Daniel J. Mandl, Shane Pederson, James Pivarski, Ray Powell, Jonathan Spring, Walt Wells and John Xia, The Matsu Wheel: a reanalysis framework for Earth satellite imagery in data commons, International Journal of Data Science and Analytics, doi:10.1007/s41060-017-0052-3, 2017. pdf

  59. R. L. Grossman, B Abel, S Angiuoli, JC Barrett, D Bassett, K Bramlett, GM Blumenthal, A Carlsson, R Cortese, J DiGiovanna, B Davis-Dusenbery, R Dittamore, DA Eberhard, P Febbo, M Fitzsimons, Z Flamig, J Godsey, J Goswami, A Gruen, F Ortuño, J Han, D Hayes, J Hicks, D Holloway, D Hovelson, J Johnson, H Juhl, R Kalamegham, R Kamal, Q Kang, GJ Kelloff, M Klozenbuecher, A Kolatkar, P Kuhn, K Langone, R Leary, P Loverso, H Manmathan, A-M Martin, J Martini, D Miller, M Mitchell, T Morgan, R Mulpuri, T Nguyen, G Otto, A Pathak, E Peters, R Philip, E Posadas, D Reese, MG Reese, D Robinson, A Dei Rossi, H Sakul, J Schageman, S Singh, HI Scher, K Schmitt, A Silvestro, J Simmons, T Simmons, J Sislow, A Talasaz, P Tang, M Tewari, S Tomlins, H Toukhy, HR Tseng, M Tuck, A Tzou, J Vinson, Y Wang, W Wells, A Welsh, J Wilbanks, J Wolf, L Young, JSH Lee, and LC Leiman, Collaborating to compete: Blood Profiling Atlas in Cancer (BloodPAC) Consortium, Clinical Pharmacology and Therapeutics, volume 101, number 5, 2017, pages 589-592. pdf

  60. Thomas P. Stricker, Christopher D. Brown, Chaitanya Bandlamudi, Megan McNerney, Ralf Kittler, Vanessa Montoya, April Peterson, Robert Grossman, Kevin P. White, Robust stratification of breast cancer subtypes using differential patterns of transcript isoform expression, PLoS Genetics, volume 13, number 3, 2017, e1006589. pdf

  61. Mark A. Jensen, Vincent Ferretti, Robert L. Grossman, and Louis M. Staudt, The NCI Genomic Data Commons as an engine for precision medicine, Blood Volume 130, Number 4, pages 453-459, 2017. pdf

  62. Paul Geeleher, Zhenyu Zhang, Fan Wang, Robert F. Gruener, Aritro Nath, Gladys Morrison, Steven Bhutra, Robert L. Grossman, and R. Stephanie Huang, Discovering novel pharmacogenomic biomarkers by imputing drug response in cancer patients from large genomics studies, Genome Research volume 27, number 10, pages 1743-1751, 2017. pdf

  63. Robert L. Grossman, A Framework for Evaluating the Analytic Maturity of an Organization, International Journal of Information Management, volume 38, number 1, pages 45-51, 2018. pdf

  64. Maria T. Patterson and Robert L. Grossman, Detecting Spatial Patterns of Disease in Large Collections of Electronic Medical Records Using Neighbor-Based Bootstrapping, Big Data, volume 5, number 3, pages 213-224, September, 2017. pdf

  65. Shane Wilson, Michael Fitzsimons, Martin Ferguson, Allison Heath, Mark Jensen, Josh Miller, Mark W. Murphy, James Porter, Himanso Sahni, Louis Staudt, Yajing Tang, Zhining Wang, Christine Yu, Junjun Zhang, Vincent Ferretti and Robert L. Grossman, Developing Cancer Informatics Applications and Tools Using the NCI Genomic Data Commons API, Cancer Research, volume 77, number 21, 2017, pages e15-e18. pdf

  66. Sean Peisert, Eli Dart, William Barnett, Edward Balas, James Cuff, Robert L Grossman, Ari Berman, Anurag Shankar, Brian Tierney; The medical science DMZ: a network design pattern for data-intensive medical science, Journal of the American Medical Informatics Association, ocx104, published 6 October 2017, https://doi.org/10.1093/jamia/ocx104 pdf

  67. Robert L. Grossman, Progress Towards Cancer Data Ecosystems, The Cancer Journal: The Journal of Principles and Practice of Oncology, May/June 2018, Volume 24 Number 3, pages 122-126 doi: 10.1097/PPO.0000000000000318. PMID: 29794537 pdf

  68. Jerry Ssu-Hsien Lee, Warren Alden Kibbe, and Robert Lee Grossman, Data Harmonization for a Molecularly Driven Health System, Cell, Volume 174, Issue 5, p 1045-1048, August 23, 2018, DOI: 10.1016/j.cell.2018.08.012 pdf

  69. Paul Geeleher, Aritro Nath, Fan Wang, Zhenyu Zhang, Alvaro N Barbeira, Jessica Fessler, Robert L Grossman, Cathal Seoighe, and R. Stephanie Huang, Cancer eQTLs can be determined from heterogeneous tumor gene expression data by modeling variation in tumor purity, Genome Biology, Volume 19, Issue 1, page 130, 2018, https://doi.org/10.1186/s13059-018-1507-0 pdf

  70. Paula Friedman, Mohammed Shaazuddin, Li Gong, Robert Grossman, Arthur Harralson, Teri Klein, Norman Lee, Doriane Miller, Edith Nutescu, Travis O'Brien, Peter O'Donnell, Kevin O'Leary, Matthew Tuck, David Meltzer, and Minoli Perera, The ACCOuNT Consortium: a model for the discovery, translation and implementation of precision medicine in African Americans, Clinical and Translational Science, 2018 Dec 28. doi: 10.1111/cts.12608. PMID: 30592548 pdf

  71. Robert L. Grossman, Data Lakes, Clouds and Commons: A Review of Platforms for Analyzing and Sharing Genomic Data, Trends in Genetics 35, 2019, pages 223-234. PMID: 30691868 PMCID: PMC6474403 pdf

  72. Nhan Do, Robert Grossman, Theodore Feldman, Nathanael Fillmore, Danne Elbers, David Tuck, Rupali Dhond, Luis Selva, Frank Meng, Michael Fitzsimons, Samuel Ajjarapu, Siamack Ayandeh, Robert Hall, Stephanie Do, Mary Brophy, The Veterans Precision Oncology Data Commons: Transforming VA Data into a National Resource for Research in Precision Oncology, Seminars in Oncology, October 2, 2019. PMID: 31629530 pdf

  73. Phillip G. Febbo, Anne-Marie Martin, Howard I. Scher, J. Carl Barrett, Julia A. Beaver, Paul J. Beresford, Gideon M. Blumenthal, Kelli Bramlett, Carolyn Compton, Ryan Dittamore, David A. Eberhard, Daniel Edelstein, James Godsey, Andrew Gruen, Sean E. Hanlon, James Hicks, Daniel Hovelson, Melanie Hullings, Donald Johann, Justin Johnson, Anand Kolatkar, Peter Kuhn, Rebecca Levine, Jean-Francois Martini, Daniel P. Miller, Carissa Moore, Bryan Moy, Anand Pathak, Reena Philip, David Reese, Wendy Royalty, Matthew Ryder, Hakan Sakul, Lea M. Salvatore, Andrew Schade, Angela Silvestro, John K. Simmons, Jonathan Simons, Seema Singh Bhan, Matthew D. Smalley, Stella B. Somiari, AmirAli Talasaz, Muneesh Tewari, Hsian-Rong Tseng, Jake Vinson, Walt Wells, Allison Welsh, Robert L. Grossman, Jerry S. H. Lee and Lauren C. Leiman, Minimum Technical Data Elements for Liquid Biopsy Data Submitted to Public Databases, Clinical Pharmacology and Therapeutics, 2020. pdf

  74. Mark A. Applebaum, Erin K. Barr, Jason Karpus, Diana C. West-Szymanski, Meritxell Oliva, Elizabeth A. Sokol, Sheng Zhang, Zhou Zhang, Wei Zhang, Alexandre Chlenski, Helen R. Salwen, Emma Wilkinson, Marija Dobratic, Robert L. Grossman, Lucy A. Godley, Barbara E. Stranger, Chuan He and Susan L. Cohn, 5-Hydroxymethylcytosine Profiles in Circulating Cell-Free DNA Associate with Disease Burden in Children with Neuroblastoma, Clinical Cancer Research 26, number 6, 2020, pages 1309-1317. PMID: 31852832 PMCID: PMC7073281 DOI: 10.1158/1078-0432.CCR-19-2829 pdf

  75. ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Concosortium, Pan-cancer analysis of whole genomes, Nature 578, no. 7793 (2020): pages 82-93. PMID: 32025007 PMCID: PMC7025898 DOI: 10.1038/s41586-020-1969-6 pdf

  76. Sergei Yakneen, Sebastian M. Waszak, PCAWG Technical Working Group, Michael Gertz, Jan O. Korbel and PCAWG Consortium, Butler enables rapid cloud-based analysis of thousands of human genomes, Nature Biotechnoloy, 2020, Volume, 38, page: 288–292, PMID: 32024987 PMCID: PMC7025898 DOI: 10.1038/s41587-019-0360-3. pdf

  77. Stacy Thomas, Tara Lichtenberg, Kristen Dang, Michael Fitzsimons, Robert L. Grossman, Ritika Kundra, Jessica A. Lavery, Michele L. Lenoue-Newton, Katherine S. Panageas, Charles Sawyers, Nikolaus D. Schultz, Sahussapont J. Sirintrapun, Umit Topaloglu, Angelica Welch, Thomas Yu, Ahmet Zehir, and Stuart Gardos, Linked Entity Attribute Pair (LEAP): A Harmonization Framework for Data Pooling, JCO Clinical Cancer Informatics 2020 Volume 4, pages 691-699. PMID: 32755461 DOI: 10.1200/CCI.20.00037 pdf

  78. Danne C. Elbers, Nathanael R. Fillmore, Feng-Chi Sung, Spyridon S. Ganas, Andrew Prokhorenkov, Christopher Meyer, Robert B. Hall, Samuel J. Ajjarapu, Daniel C. Chen, Frank Meng, Robert L. Grossman, Mary T. Brophy, and Nhan V. Do, The Veterans Affairs Precision Oncology Data Repository, a Clinical, Genomic, and Imaging Research Database, Patterns Volume 1 (2020) 100083. DOI: 10.1016/j.patter.2020.100083 pdf

  79. Bohdan B Khomtchouk, Christopher S Nelson, Kasra A Vand, Salvator Palmisano, Robert L Grossman, HeartBioPortal2.0: new developments and updates for genetic ancestry and cardiometabolic quantitative traits in diverse human populations, Database, Volume 2020, 2020, PMID: 33382884, PMCID: PMC7774463, DOI: 10.1093/database/baaa115. pdf

  80. Heath AP, Ferretti V, Agrawal S, An M, Angelakos JC, Arya R, Bajari R, Baqar B, Barnowski JHB, Burt J, Catton A, Chan BF, Chu F, Cullion K, Davidsen T, Do PM, Dompierre C, Ferguson ML, Fitzsimons MS, Ford M, Fukuma M, Gaheen S, Ganji GL, Garcia TI, George SS, Gerhard DS, Gerthoffert F, Gomez F, Han K, Hernandez KM, Issac B, Jackson R, Jensen MA, Joshi S, Kadam A, Khurana A, Kim KMJ, Kraft VE, Li S, Lichtenberg TM, Lodato J, Lolla L, Martinov P, Mazzone JA, Miller DP, Miller I, Miller JS, Miyauchi K, Murphy MW, Nullet T, Ogwara RO, Ortuño FM, Pedrosa J, Pham PL, Popov MY, Porter JJ, Powell R, Rademacher K, Reid CP, Rich S, Rogel B, Sahni H, Savage JH, Schmitt KA, Simmons TJ, Sislow J, Spring J, Stein L, Sullivan S, Tang Y, Thiagarajan M, Troyer HD, Wang C, Wang Z, West BL, Wilmer A, Wilson S, Wu K, Wysocki WP, Xiang L, Yamada JT, Yang L, Yu C, Yung CK, Zenklusen JC, Zhang J, Zhang Z, Zhao Y, Zubair A, Staudt LM, and Grossman RL, The NCI Genomic Data Commons, Nature Genetics 2021 Mar;53(3):257-262. PMID: 33619384 doi: 10.1038/s41588-021-00791-5. PMID: 33619384 pdf

  81. Zhenyu Zhang, Kyle Hernandez, Jeremiah Savage, Shenglai Li, Dan Miller, Stuti Agrawal, Francisco Ortuno, Louis M. Staudt, Allison Heath, and Robert L. Grossman, Uniform genomic data analysis in the NCI Genomic Data Commons, Nature communications 12, no. 1 (2021), pages 1-11. PMID: 33619257 doi: 10.1038/s41467-021-21254-9. pdf

  82. Robert L. Grossman, Jonathan R. Dry, Sean E. Hanlon, Donald J. Johann, Anand Kolatkar, Jerry SH Lee, Christopher Meyer, Lea Salvatore, Walt Wells, and Lauren Leiman, BloodPAC Data Commons for liquid biopsy data, JCO Clinical Cancer Informatics Volume 5, 2021, pages 479-486. PMID: 33929890 DOI: 10.1200/CCI.20.00179 pdf

  83. Frederick M. Howard, James Dolezal, Sara Kochanny, Jefree Schulte, Heather Chen, Lara Heij, Dezheng Huo, Rita Nanda, Olufunmilayo I. Olopade, Jakob N. Kather, Nicole Cipriani, Robert L. Grossman1, and Alexander T. Pearson, The impact of site-specific digital histology signatures on deep learning model accuracy and bias, Nature Communications 12, no. 1, 2021, pages 1-13. pdf

  84. Craig Barnes, Binam Bajracharya, Matthew Cannalte, Zakir Gowani, Will Haley, Taha Kass-Hout, Kyle Hernandez, Michael Ingram, Hara Prasad Juvvala, Gina Kuffel, Plamen Martinov, J. Montgomery Maxwell, John McCann, Ankit Malhotra, Noah Metoki-Shlubsky, Chris Meyer, Andre Paredes, Jawad Qureshi, Xenia Ritter, L. Philip Schumm, Mingfei Shao, Urvi Sheth, Trevar Simmons, Alexander VanTol, Zhenyu Zhang, and Robert L. Grossman, The Biomedical Research Hub: A Federated Platform for Patient Research Data, Journal of the American Medical Informatics Association, 2021, doi:10.1093/jamia/ocab247. pdf

  85. Rehm, Heidi L., Angela JH Page, Lindsay Smith, Jeremy B. Adams, Gil Alterovitz, Lawrence J. Babb, Maxmillian P. Barkley et al., GA4GH: International policies and standards for data sharing across genomic research and healthcare, Cell Genomics 1, no. 2, 2021, 100029. pdf

  86. Schatz, M.C., Philippakis, A.A., Afgan, E., Banks, E., Carey, V.J., Carroll, R.J., Culotti, A., Ellrott, K., Goecks, J., Grossman, R.L. and Hall, I.M., Inverting the model of genomics data sharing with the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space, Cell Genomics, Jan 12, 2022, 2(1):100085. doi: 10.1016/j.xgen.2021.100085. pdf

  87. Zingyan Kuang, Fan Wang, Kyle Hernandez, Zhenyu Zhang and Robert L. Grossman, Accurate and rapid prediction of tuberculosis drug resistance from genome sequence data using traditional machine learning algorithms and CNN, Scientific Reports, 2022 pdf

  88. Thomas O’Hara, PhD; Anil Saldanha, MS; Matthew Trunnell, MSc; Robert L. Grossman, PhD; Bala Hota, MD; and Casey Frankenberger, PhD, Economical Utilization of Health Information with Learning Healthcare System Data Commons, Perspectives in Health Information Management, AHIMA, 2022, Vol. 19, Issue 2, 2022. pdf

  89. Shi, C., Babiker, N., Urbanek, J.K. et al. Free-living wrist and hip accelerometry forecast cognitive decline among older adults without dementia over 1- or 5-years in two distinct observational cohorts. npj Aging 8, 7 (2022). https://doi.org/10.1038/s41514-022-00087-w pdf

  90. Sheffield, N.C., Bonazzi, V.R., Bourne, P.E., Burdett, T., Clark, T., Grossman, R.L., Spjuth, O. and Yates, A.D., From biomedical cloud platforms to microservices: next steps in FAIR data and analysis, Nature Scientific Data, 2022, https://doi.org/10.1038/s41597-022-01619-5. pdf

  91. L. Philip Schumm, Mihai C. Giurcanu, Kenneth J. Locey, Jean Czerlinski Ortega, Zhenyu Zhang, Robert L. Grossman, Racial and Ethnic Disparities in the Observed COVID-19 Case Fatality Rate Among the U.S. Population, Annals of Epidemiology 74 (2022): 118-124. pdf

  92. Christina A. Clarke, Kathryn Lang, Girish Putcha, Jonathan P. Beer, Maude Champagne, Andrea Ferris, James H. Godsey, Robert L. Grossman, Jody M. Hoyos, Donald J. Johann, Nancy Krunic, Peter Kuhn, Jerry S. H. Lee, Tara Maddala, Marielena Mata, Jeremiah McDole, Omar Perez, Howard Scher, Mark D. Stewart, Seema Singh Bhan, Qu Zhang, and Lauren C. Leiman, BLOODPAC: Collaborating to chart a path towards blood-based screening for early cancer detection, Clinical and Translational Science, 16: 5-9, 2022, https://doi.org/10.1111/cts.13427. pdf

  93. Hernandez, Kyle M., Kelli S. Bramlett, Phaedra Agius, Jonathan Baden, Ru Cao, Omoshile Clement, Adam S. Corner et al. Contrived Materials and a Data Set for the Evaluation of Liquid Biopsy Tests: A Blood Profiling Atlas in Cancer (BLOODPAC) Community Study. The Journal of Molecular Diagnostics 25, no. 3 (2023): 143-155. pdf

  94. Grossman, Robert L. Ten lessons for data sharing with a data commons. Scientific Data 10, no. 1 (2023): 120. pdf

  95. Lukowski, Michael, Andrew Prokhorenkov, and Robert L. Grossman. Towards self-describing and FAIR bulk formats for biomedical data. PLOS Computational Biology 19, no. 3 (2023): e1010944. pdf

  96. Shawn M. Sweeney; Hisham K. Hamadeh; Natalie Abrams; Stacey J. Adam; Sara Brenner; Dana E. Connors; Gerard J. Davis; Louis D. Fiore; Susan H. Gawel; Robert L. Grossman et al., Challenges to using big data in cancer. Cancer research 83, no. 8 (2023): 1175-1182. pdf

  97. Shawn M. Sweeney; Hisham K. Hamadeh; Natalie Abrams; Stacey J. Adam; Sara Brenner; Dana E. Connors; Gerard J. Davis; Louis D. Fiore; Susan H. Gawel; Robert L. Grossman et al., Case Studies for Overcoming Challenges in Using Big Data in Cancer. Cancer Research 83 no. (8) (2023): 1183–1190. pdf

  98. Ahalt, Stan, Paul Avillach, Rebecca Boyles, Kira Bradford, Steven Cox, Brandi Davis-Dusenbery, Robert L. Grossman et al. Building a collaborative cloud platform to accelerate heart, lung, blood, and sleep research. Journal of the American Medical Informatics Association (2023): ocad048. pdf

  99. Kyle M. Hernandez, Aarti Venkat, Danne C. Elbers, John R. Bihn, Mary T. Brophy, Nhan V. Do, Jennifer La, Qiong Liu, Andrew Prokhorenkov, Noah Metoki-Shlubsky, Feng-Chi Sung, Channing J. Paller, Nathanael R. Fillmore and Robert L. Grossman, Prostate cancer patient stratification by molecular signatures in the Veterans Precision Oncology Data Commons, Molecular Case Studies, 9(4), p.a006298. pdf

  100. Robert L. Grossman, Rebecca R. Boyles, Brandi N. Davis-Dusenbery, Amanda Haddock, Allison P. Heath, Brian D. O'Connor, Adam C. Resnick, Deanne M. Taylor, and Stan Ahalt. "A Framework for the Interoperability of Cloud Platforms: Towards FAIR Data in SAFE Environments." Sci Data 2024, in press. pdf

  101. James M. Dolezal, Rachelle Wolk, Hanna M. Hieromnimon, Frederick M. Howard, Andrew Srisuwananukorn, Dmitry Karpeyev, Siddhi Ramesh, Sara Kochanny, Jung Woo Kwon, Meghana Agni, Richard C. Simon, Chandni Desai, Raghad Kherallah, Tung D. Nguyen, Jefree J. Schulte, Kimberly Cole, Galina Khramtsova, Marina Chiara Garassino, Aliya N. Husain, Huihua Li, Robert Grossman, Nicole A. Cipriani and Alexander T. Pearson, Deep learning generates synthetic cancer histology for explainability and education, npj Precis. Onc. 7, 49 (2023), https://doi.org/10.1038/s41698-023-00399-4 pdf

  102. Clark M, Meyer C, Ramos-Cejudo J, Elbers DC, Pierce-Murray K, Fricks R, Alterovitz G, Rao L, Brophy MT, Do NV, Grossman RL, Fillmore NR. Transfer Learning for Mortality Prediction in Non-Small Cell Lung Cancer with Low-Resolution Histopathology Slide Snapshots. Stud Health Technol Inform. 2024 Jan 25; 310:735-739. doi: 10.3233/SHTI231062. PMID: 38269906 pdf

Articles in Refereed Proceedings

  1. R. Grossman, Quantum Controllability, Proceedings of the 23rd Conference on Decision and Control, IEEE, 1984 pages 1466-7.

  2. R. Grossman and C. Martin, The approximation and control of symmetric systems over the circle, Mathematical Theory of Network and Systems, Lecture Notes in Computer Science Voume 58, P. A. Fuhrmann, editor, Springer-Verlag, New York, 1984, pages 376-388.

  3. R. Grossman and C. Martin, The approximation and control of symmetric systems over compact groups, Proceedings of the Berkeley-Ames Conference on Nonlinear Problems in Control and Fluid Dynamics, L. R. Hunt and C. F. Martin, editors, Math Sci Press, Brookline, 1984, pages 145-170.

  4. R. Grossman and R. Larson, The symbolic computation of higher order derivations: symmetries of expressions and actions of group algebras, Differential Geometry: The Interface Between Pure and Applied Mathematics, Contemporary Mathematics, 68, M. Luksic, C. Martin and W. Shadwick, editors, American Mathematical Society, Providence, 1987, pages 121-131.

  5. R. Grossman, P. S. Krishnaprasad, and J. E. Marsden, The dynamics of two coupled rigid bodies, Dynamical Systems Approaches to Nonlinear Problems in Systems and Circuits, F. M. A. Salam and M. L. Levi, editors, SIAM, Philadelphia, 1988, pages 373-378. pdf

  6. R. Grossman and R. Larson, Labeled trees and the algebra of differential operators, Graphs and Algorithms, Contemporary Mathematics, Volume 89, B. Richter, editor, American Mathematical Society, Providence, 1989, pages 81-87. pdf

  7. R. Fateman and R. Grossman, Computer algebra and operators, Symbolic Computation: Applications to Scientific Computing, R. Grossman, editor, SIAM, Philadelphia, 1989, pp. 1-14.

  8. M. Grayson and R. Grossman, Nilpotent Lie algebras and vector fields, Symbolic Computation: Applications to Scientific Computing, R. Grossman, editor, SIAM, Philadelphia, 1989, pages 77-96. pdf

  9. R. Grossman and R. G. Larson, Labeled trees and the efficient computation of derivations, Proceedings of 1989 International Symposium on Symbolic and Algebraic Computation, ACM, 1989, pages 74-80. pdf

  10. R. Grossman, Querying databases of trajectories of differential equations I: data structures for trajectories, Proceedings of the 23rd Hawaii International Conference on Systems Sciences, IEEE, 1990, pages 18-23. pdf

  11. M. W. Bern, D. P. Dobkin, D. Eppstein, and R. Grossman, Visibility with a moving point of view (extended abstract), Proceedings of the First Annual ACM-SIAM Symposium on Discrete Algorithms, SIAM, 1990, pp. 107-117.

  12. R. Grossman, Querying databases of trajectories of differential equations II: index functions, Fourth NASA Workshop on Computational Control of Flexible Aerospace Systems, NASA Conference Proceedings, Number 10065, Part 1, L. W. Taylor, Jr., editor, NASA Langley Research Center, 1991, pp. 35-39. pdf

  13. R. Grossman, Using trees to compute approximate solutions of ordinary differential equations exactly, Differential Equations and Computer Algebra M. Singer, editor, Academic Press, New York, 1991, pp. 29-59. pdf

  14. P. Crouch, R. Grossman, and R. G. Larson, Computations involving differential operators and their actions on functions, Proceedings of 1991 International Symposium on Symbolic and Algebraic Computation, ACM, 1991, pp. 301-307. pdf

  15. A. Baden and R. Grossman, Database computing and high energy physics, Computing in High-Energy Physics 1991, edited by Y. Watase and F. Abe, Universal Academy Press, Inc., Tokyo, 1991, pp. 59-66. pdf

  16. R. Grossman and R. G. Larson, The symbolic computation of vector field expressions, Algebraic Computing in Control 1991, edited by G. Jacob and F. Lamnabhi-Lagarrigue, Springer-Verlag, Berlin, 1991, pp. 1-10. pdf

  17. R. Grossman and D. Radford, A simple construction of bialgebra deformations, Contemporary Mathematics: Quantum Groups and Deformations, AMS, pp. 115-117, 1992. pdf

  18. P.E. Crouch and R. L. Grossman, The Explicit Computation of Integration Algorithms and First Integrals for Ordinary Differential Equations With Polynomial Coefficients Using Trees, Proceedings of the 1992 International Symposium on Symbolic and Algebraic Computation, ACM Press, pp. 89-94. pdf

  19. R. L. Grossman and R. G. Larson, Viewing hybrid systems as products of control systems and automata, Proceedings of the 31st IEEE Conference on Decision and Control, IEEE Press, 1992, pages 2953-2955. pdf

  20. P.E. Crouch, R. Grossman, and Y. Yan, On the numeric integration of dynamic attitude equations, Proceedings of the 31st IEEE Conference on Decision and Control, IEEE Press, 1992, pages 1497-1501. pdf

  21. R. L. Grossman, D. Lifka, and X. Qin, A proof-of-concept implementation interfacing an object manager to a hierarchical storage system, Twelfth IEEE Symposium on Mass Storage Systems, IEEE Press, Los Alamites, 1993, pp. 209-214. pdf

  22. E. May, D. Lifka, E. Lusk, L. E. Price, C. T. Day, S. Loken, J. F. MacFarlane, A. Baden R. Grossman, X. Qin, L. Cormell, A. Gauthier, P. Leibold, J. Marstaller, U. Nixdorf, B. Scipioni Requirements for a System to Analyze High Energy Physics Events Using Database Computing Twelfth IEEE Symposium on Mass Storage Systems, IEEE Press, Los Alamites, 1993, pp. 31-36. pdf

  23. C. T. Day, S. Loken, J. F. MacFarlane, E. May, D. Lifka, E. Lusk, L. E. Price, A. Baden, R. Grossman, X. Qin, L. Cormell, P. Leibold, D. Liu, U. Nixdorf, B. Scipioni, T. Song, Database Computing in HEP -- Progress Report, Proceedings of the International Conference on Computing in High Energy Physics '92, C. Verkerk and W. Wojcik, editors, CERN-Service d'Information Scientifique, 1992, ISSN 0007-8328, pp. 557-560. pdf

  24. R. L. Grossman and R. L. Larson, Some Remarks About Flows in Hybrid Systems, in R. L. Grossman, A. Nerode, A. P. Ravn, and H. Rischel, editors, Hybrid Systems, Lecture Notes in Computer Science, Volume 736, Springer-Verlag, New York, 1993, pp. 357-365.

  25. R. L. Grossman, D. Valsamis and X. Qin, Persistent stores and hybrid systems, Proceedings of the 32st IEEE Conference on Decision and Control, IEEE Press, 1993, pp. 2298-2302.

  26. R. L. Grossman, Working With Object Stores of Events Using PTool, 1993 Cern Summer School in Computing, C. E. Vandoni and C. Verkerk, editors, CERN-Service d'Information Scientifique 94-06, pages 66-97, 1994. Available from: http://cds.cern.ch/record/399341/files/p66.pdf. pdf

  27. R. L. Grossman and X. Qin, Ptool: a scalable persistent object manager, Proceedings of SIGMOD 94, ACM, 1994, page 510. pdf

  28. R. L. Grossman, A. Sundaram, H. Ramamoorthy, M. Wu, S. Hogan, J. Shuler and O. Wolfson, Viewing the U.S. Government Budget as a Digital Library, Proceedings of Digital Libraries 1994: Conference on the Theory and Practice of Digital Libraries, ACM, 1994.

  29. R. L. Grossman, W. Sluis, and W. Shadwick, On Nonlinear Normal Forms, Proceedings of the 33st IEEE Conference on Decision and Control, EEE Press, 1994.

  30. D. R. Quarrie, C. T. Day, S. Loken, J. F. Macfarlane, D. Lifka, E. Lusk, D. Malon, E. May, L. E. Price, L. Cormell, A. Gauthier, P. Liebold, J. Hilgart, D. Liu, J. Marstaller, U. Nixdorf, T. Song, R. Grossman, X. Qin, D. Valsamis, M. Wu, W. Xu, A. Baden, The PASS Project: A Progress Report, Proceedings of the Conference on Computing in High Energy Physics 1994, edited by S. C. Loken, pages 229-232, 1995. pdf

  31. D. R. Quarrie, C. T. Day, S. Loken, J. F. Macfarlane, D. Lifka, E. Lusk, D. Malon, E. May, L. E. Price, L. Cormell, A. Gauthier, P. Liebold, J. Hilgart, D. Liu, J. Marstaller, U. Nixdorf, T. Song, R. Grossman, X. Qin, D. Valsamis, M. Wu, W. Xu, A. Baden, The PASS Project Architectural Model, Proceedings of the Conference on Computing in High Energy Physics 1994, edited by S. C. Loken, pages 233-235, 1995. pdf

  32. E. N. May, D. Lifka, D. Malon, L. E. Price L. Cormell, A. Gauthier, J. Marsteller, S. Mestad, U. Nixdorf R. Grossman, X. Qin, D. Valsamis, M. Wu, W. Xu A Demonstration of a Multi-level Object Store and its Application to the Analysis of High Energy Physics Data, Proceedings of the Conference on Computing in High Energy Physics 1994, edited by S. C. Loken, pages 236-238, 1995. pdf

  33. D. Malon, D. Lifka, E. May R. Grossman, X. Qin, W. Xu Parallel Query Processing for Event Store Data, Proceedings of the Conference on Computing in High Energy Physics 1994, edited by S. C. Loken, pp. 239-240, 1995. pdf

  34. R. L. Grossman, N. Araujo, X. Qin, and W. Xu, Managing physical folios of objects between nodes, Persistent Object Systems (Proceedings of the Sixth International Workshop on Persistent Object Systems), M. P. Atkinson, V. Benzaken and D. Maier, editors, Springer-Verlag and British Computer Society, 1995, pages 217-231.

  35. R. L. Grossman, X. Qin, D. Valsamis, W. Xu, C. T. Day, S. Loken, J. F. MacFarlane, D. Quarrie, E. May, D. Lifka, D. Malon, L. Price, Analyzing High Energy Physics Data Using Databases: A Case Study, Proceedings of the Seventh International Working Conference on Scientific and Statistical Database Management, IEEE Press, 1994, pages 283-286. pdf

  36. R. L. Grossman, A. Nerode, and W. Kohn, Nonlinear Systems, Automata, and Agents: Managing their Symbolic Data Using Light Weight Persistent Object Managers, International Symposium on Fifth Generation Computer Systems, 1994: Workshop on Heterogeneous Cooperative Knowledge-Bases, Kazumasa Yokota, editor, ICOT, pages 65-74.

  37. J. Leigh, C. A. Vasilakis, T. A. DeFanti, R. Grossman, C. Assad, B. Rasnow, A. Protopappas, E. DeSchutter, J. M. Bower, Virtual Reality in Computational Neuroscience, Virtual Reality Applications, edited by R. Earnshaw, J. A. Vince and H. Jones, Academic Press, London, 1995, pages 293-306.

  38. R. L. Grossman D. Hanley, and X. Qin Caching and migration for physical collections of objects: Interfacing persistent object stores and hierarchical storage systems, in Proceedings of the 14th IEEE Computer Society Mass Storage Systems Symposium, S. Coleman, editor, IEEE, 1995, pages 127-135. pdf

  39. R. L. Grossman, D. Hanley, and X. Qin, PTool: A Light Weight Persistent Object Manager, Proceedings of SIGMOD 95, ACM, 1995, p. 488. pdf

  40. R. L. Grossman and M. Sweedler Hybrid Systems and Quantum Automata: Preliminary Announcement, Hybrid Systems II, P. Antsaklis, W. Kohn, A. Nerode, S. Sastry, editors, Springer Lecture Notes in Computer Science, Volume 999, pages 191-201, 1995. pdf

  41. M. J. Doffou and R. L. Grossman, The Symbolic Computation of Differential Invariants of Polynomial Vector Field Systems Using Trees, Proceedings of the 1995 International Symposium on Symbolic and Algebraic Computation, A. H. M. Levelt, editor, ACM, 1995, pages 26-31. pdf

  42. N. Araujo, R. Grossman, D. Hanley, W. Xu, S. Ahn, K. Denisenko, M. Fischler, M. Galli D. Malon and E. May, Some Remarks on Parallel Data Mining Using a Persistent Object Manager, Proceedings of the Conference on Computing in High Energy Physics 1995. pdf

  43. S. Bailey, R. Grossman, and D. Hanley, D. Benton and B. Hollebeek, Scalable Digital Libraries of Event Data and the NSCP Meta-Cluster, Proceedings of the Conference on Computing in High Energy Physics 1995. pdf

  44. R. L. Grossman and H. V. Poor, Optimization Driven Data Mining and Credit Scoring, in Proceedings of the IEEE/IAFE 1996 Conference on Computational Intelligence for Financial Engineering (CIFEr), IEEE, Piscataway, 1996, pages 104-110. pdf

  45. S. Bailey, R. L. Grossman, L. Gu, and D. Hanley, A Data Intensive Approach to Path Planning and Mode Management for Hybrid Systems, in R. Alur, T. A. Henzigner, and E. Sontag, Hybrid Systems III, Proceedings of the DIMACS Workshop on Verification and Control of Hybrid Systems, Springer-Verlag, LNCS 1066, 1996.

  46. R. L. Grossman, H. Bodek, D. Northcutt, and H. V. Poor, Data Mining and Tree-based Optimization, Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD 1996), E. Simoudis, J. Han and U. Fayyad, editors, AAAI Press, Menlo Park, California, 1996, pp 323-326. pdf

  47. R. L. Grossman, The Terabyte Challenge: An Open, Distributed Testbed for Managing and Mining Massive Data Sets, Proceedings of the 1996 Conference on Supercomputing, IEEE, 1996. pdf

  48. R. L. Grossman, S. Bailey and D. Hanley, Data Mining Using Light Weight Object Management in Clustered Computing Environments, Proceedings of the Seventh International Workshop on Persistent Object Stores, Morgan-Kauffmann, San Mateo, 1997, pages 237-249. pdf

  49. S. Bailey, A. Goldstein, R. L. Grossman, and D. Hanley, Accessing Warehoused Collections of Objects Through Java, Proceedings of the First International Workshop on Persistence and Java, Sun Microsystems, 1996. pdf

  50. S. Bailey and R. L. Grossman, JTool: Accessing Warehoused Collections of Objects with Java, Proceedings of the Second Workshop on Persistence and Java, Sun Microsystems, 1998. pdf

  51. R. L. Grossman and S. Bailey, An Overview of Dynamic Classification: Mining Collections of Trajectories (invited paper), 1998 Proceedings of the Section on Physical and Engineering Sciences, American Statistical Association, Alexandria, Virgina, pages 24-28. pdf

  52. R. L. Grossman, S. Bailey, A. Ramu, B. Malhi and A. Turinsky, The Preliminary Design of Papyrus: A System for High Performance, Distributed Data Mining over Clusters, in Advances in Distributed and Parallel Knowledge Discovery, H. Kargupta and P. Chan, editors, AAAI Press/The MIT Press, Menlo Park, California, 2000, pages 259-275. pdf

  53. R. L. Grossman, S. Bailey, A. Ramu, B. Malhi and H. Sivakumar, A. Turinsky, Papyrus: A System for Data Mining over Local and Wide Area Clusters and Super-Clusters, Proceedings of Supercomputing 1999, IEEE. pdf

  54. R. L. Grossman, The Role of QoS in Wide Area Data Mining, Proceedings of the First Internet 2 Joint Applications Engineering QoS Workshop: Enabling Advanced Applications Through QoS, UCAID, 1999, pages 19-21. pdf

  55. J. Leigh, A. Johnson, T. DeFanti, S. Bailey, R. L. Grossman, A Methodology for Supporting Collaborative Exploratory Analysis of Massive Data Sets in Tele-Immersive Environments, 8th IEEE International Symposium on High Performance and Distributed Computing, Redundo Beach, California, Aug 3-6, 1999. pdf

  56. J. Leigh, A. Johnson, T. DeFanti, S. Bailey, R. L. Grossman, A Tele-Immersive Environment for Collaborative Exploratory Analysis of Massive Data Sets, ASCI 99, pages 3-9, Heijen, the Netherlands, 1999. pdf

  57. S. Bailey, E. Creel, R. Grossman, S. Gutti, and H. Sivakumar, A High Performance Implementation of the Data Space Transfer Protocol (DSTP), Large-Scale Parallel Data Mining, M. J. Zaki and C.-T. Ho, editors, Springer-Verlag, Berlin, 2000, pages 55-64. pdf

  58. R. L. Grossman and Yike Guo, Parallel Methods for Scaling Data Mining Algorithms to Large Data Sets, Hanndbook on Data Mining and Knowledge Discovery, Jan M Zytkow, editor, Oxford University Press, 2002, pages 433 - 442. pdf

  59. H. Sivakumar, R. Grossman, B. Schiefer, X. Xue, and S. Syed, Performance of DB2 UDB EEE on NT with Virtual Interface Architecture, Lecture Notes in Computer Science: Advances in Database Technology EDBT 2000, 7th International Conference on Extending Database Technology Konstanz, Germany March 2000.

  60. H. Sivakumar, S. Bailey, R. L. Grossman, PSockets: The Case for Application-level Network Striping for Data Intensive Applications using High Speed Wide Area Networks, Proceedings of the 2000 ACM/IEEE Conference on Supercomputing (CDROM), IEEE Computer Society, Washington, DC, USA, 2000, page 38. pdf

  61. N. Sawant, C. Scharver, J. Leigh, A Johnson, G. Reinhart, E. Creel, S. Batchu, S. Bailey, R. L. Grossman, The Tele-Immersive Data Explorer: A Distributed Architecture for Collaborative Interactive Visualization of Large Data-sets, 4th International Immersive Projection Technology Workshop, Ames, Iowa, June 19-20, 2000. pdf

  62. R. L. Grossman and R. Hollebeek, The National Scalable Cluster Project: Three Lessons about High Performance Data Mining and Data Intensive Computing, in Handbook of Massive Data Sets, J. Abello, P. M. Pardalos, and M. G. C. Resende, editors, Kluwer Academic Publishers, 2002. pdf

  63. A DataSpace Infrastructure for Astronomical Data, Robert Grossman, Emory Creel, Marco Mazzucco, Roy Williams in R. L. Grossman, C. Kamath, W. Philip Kegelmeye, V. Kumar, and R. Namburu, Data Mining for Scientific and Engineering Applications, Kluwer Academic Publishers, 2001, pages 115-123. pdf

  64. Robert Grossman, Mark Hornick, and Gregor Meyer, Emerging Standards and Interfaces in Data Mining, Handbook of Data Mining, Nong Ye, editor, Lawrence Erlbaum Associates, Publishers, Mahwah, New Jersey, 2003, pages 453-459. pdf

  65. M. Cornelson, E. Greengrass, R. L. Grossman, R. Karidi, and D. Shnidman, Combining Information Retrieval Algorithms Using Machine Learning, Survey of Text Mining: Clustering, Classification, and Retrieval Michael W. Berry, editor, Springer-Verlag, 2003, pages 159-169. pdf

  66. Marco Mazzucco, Asvin Ananthanarayan, Robert L. Grossman, Jorge Levera, and Gokulnath Bhagavantha Rao, Merging Multiple Data Streams on Common Keys over High Performance Networks, Proceedings of the IEEE/ACM SC2002 Conference, 2002, IEEE Computer Society, page 67. pdf

  67. R. L. Grossman and R. G. Larson, An Algebraic Approach to Data Mining: Some Examples, Proceedings of the 2002 IEEE International Conference on Data Mining, IEEE Computer Society, Los Alamitos, California, 2002, pages 613-616. pdf

  68. Robert L. Grossman, Yunhong Gu, Dave Hanley, Xinwei Hong, Dave Lillethun, Jorge Levera, Joe Mambretti, Marco Mazzucco, and Jeremy Weinberger, Photonic Data Services: Integrating Path, Network and Data Services to Support Next Generation Data Mining Applications, Data Mining: Next Generation Challenges and Future Directions, H. Kargupta, A. Joshi, K. Sivakumar, and Y. Yesha, editors, AAAI Press, 2004. pdf

  69. Robert L. Grossman, Yunhong Gu, Dave Hanley, Xinwei Hong, Dave Lillethun, Jorge Levera, Joe Mambretti, Marco Mazzucco, and Jeremy Weinberger, Global Access to Large Distributed Data Sets using Photonic Data Services, Proceedings of the 20th IEEE/11th NASA Goddard Conference on Mass Storage Systems and Technologies (MSST 2003), IEEE Computer Society, Los Alamitos, California, pages 62-66. pdf

  70. Thomas A. DeFanti, Jason Leigh, Maxine D. Brown, Daniel J. Sandin, Oliver Yu, Chong Zhang, Rajvikram Singh, Eric He, Javid Alimohideen, Naveen K. Krishnaprasad, Robert Grossman, Marco Mazzucco, Larry Smarr, Mark Ellisman, Phil Papadopoulos, Andrew Chien, John Orcutt, Teleimmersion and Visualization with the OptIPuter, Proceedings of the 12th International Conference on Artificial Reality and Telexistence (ICAT 2002), Ohmsha/IOS Press. pdf

  71. R. Grossman, X. Qin, W. Xu, H. Hulen, and T. Tyler, An Architecture for a Scalable, High-Performance Digital Library, 14th IEEE Symposium on Mass Storage Systems, IEEE Press, pages 89-98, 1995. pdf

  72. Robert L. Grossman and Dave Northcutt, A Note on Interfacing Object Warehouses and Mass Storage Systems for Data Mining Applications, Proceedings of the Goddard Conference on Mass Storage Systems, 1996.

  73. Shitij Mutreja, Stuart Bailey, Robert Grossman, and Dave Hanley, Lightweight Video Service for Multi-Media Digital Libraries, Proceedings of CASCON '95, 1995. pdf

  74. Robert Grossman, Donald Hamelberg, Pavan Kasturi, and Bing Liu, Experimental Studies of the Universal Chemical Key (UCK) Algorithm on the NCI Database of Chemical Compounds, Proceedings of the 2003 IEEE Computer Society Bioinformatics Conference (CSB 2003), IEEE Computer Society, Los Alamitos, California, pages 244-250. pdf

  75. Bing Liu, Robert L. Grossman and Yanhong Zhai, Mining Data Records in Web Pages, Proceedings of The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2003), pages 601-606. pdf

  76. Robert L. Grossman, Alert Management Systems: A Quick Introduction, in Managing Cyber Threats: Issues, Approaches and Challenges, edited by Vipin Kumar, Jaideep Srivastava and Aleksandar Lazarevic, Springer Science+Business Media, Inc., New York, 2005, pages 281-291, ISBN 0-387-24226-0. pdf

  77. R.L. Grossman, Y. Gu, D. Hanley, X. Hong, and G. Rao, Open DMIX - Data Integration and Exploration Services for Data Grids, Data Web and Knowledge Grid Applications, Proceedings of the First International Workshop on Knowledge Grid and Grid Intelligence (KGGI 2003), W. K. Cheung and Y. Ye, editors, pages 16-28. pdf

  78. S. Bailey, R. L. Grossman and D. Hanley, Clusters, meta-clusters, and digital libraries: digital libraries for scientific, engineering and medical applications, ACM SIGWEB Newsletter, Volume 4, Number 2, ACM Press, New York, NY, 1995, pages 8-10.

  79. Chetan Gupta and Robert L. Grossman, GenIc: A Single Pass Generalized Incremental Algorithm for Clustering, 2004 SIAM International Conference on Data Mining (SDM 04), to appear. pdf

  80. Robert L. Grossman and Richard G. Larson, Bialgebras and Realizations, in Hopf Algebras, Jeffrey Bergen, Stefan Catoiu, and William Chin, editors, Marcel Dekker, Inc., New York, 2004, pages 157-166. pdf

  81. Robert L. Grossman, Yunhong Gu, Chetan Gupta, David Hanley, Xinwei Hong, and Parthasarathy Krishnaswamy, Open DMIX: High Performance Web Services for Distributed Data Mining, 7th International Workshop on High Performance and Distributed Mining, in association with the Fourth International SIAM Conference on Data Mining, 2004. pdf

  82. Jorge Levera, Benjamin Barin, and Robert Grossman, Experimental Studies Using Median Polish Procedures to Reduce Alarm Rates in Data Cubes of Intrusion Data, Intelligence and Security Informatics for National and Homeland Security, Hsinchun Chen, Reagan Moore, Daniel Zeng, John Jeavitt, editors, LNCS 3073, Springer Verlag, New York, 2004, pages 482-491. pdf

  83. Robert L. Grossman, Dave Hanley, Xinwei Hong and Parthasarathy Krishnaswamy, Using DataSpace to Support Long-Term Stewardship of Remote and Distributed Data, NASA/IEEE MSST 2004, 12th NASA Goddard/21st IEEE Conference on Mass Storage Systems and Technologies, 2004, pages 239-244. pdf

  84. Yunhong Gu, Xinwei Hong, and Robert Grossman, Experiences in Design and Implementation of a High Performance Transport Protocol, ACM/IEEE International Conference for High Performance Computing and Communications (SC '04), page 22. pdf

  85. Andrei L. Turinsky and Robert L. Grossman, A Greedy Algorithm for Selecting Models in Ensembles, Proceedings 4th IEEE International Conference Data Mining (ICDM 2004), Brighton, UK, pages 547-550, IEEE Computer Society Press, 2004. pdf

  86. Yunhong Gu, Xinwei Hong and Robert Grossman, An Analysis of AIMD Algorithms with Decreasing Increases, Proceedings of GridNets 2004, IEEE Press, 2004. pdf

  87. Parthasarathy Krishnaswamy, Stephen G. Eick, Robert L Grossman, Visual Browsing of Remote and Distributed Data, IEEE Symposium on Information Visualization (INFOVIS'04), 2004, page 12. pdf

  88. Yunhong Gu and Robert L. Grossman, Optimizing UDP-Based Protocol Implementations, Proceedings of the Third International Workshop on Protocols for Fast Long-Distance Networks PFLDnet 2005, 2005. pdf

  89. Greeshma Neglur and Robert L. Grossman, Assigning Unique Keys to Chemical Compounds for Data Integration: Some Interesting Counter Examples, 2nd International Workshop on Data Integration in the Life Sciences (DILS 2005), La Jolla, July 20-22, 2005. pdf

  90. Joseph Bugajski, Robert L. Grossman, Eric Sumner and Tao Zhang, An Event Based Framework for Improving Information Quality That Integrates Baseline Models, Causal Models and Formal Reference Models, Second International ACM SIGMOD Workshop on Information Quality in Information Systems (IQIS 2005), June 17th, Baltimore, Maryland, co-located with ACM SIGMOD/PODS 2005. pdf

  91. Robert L. Grossman, Michal Sabala, Javid Alimohideen, Anushka Aanand, John Chaves, John Dillenburg, Steve Eick, Jason Leigh, Peter Nelson, Mike Papka, Doug Rorem, Rick Stevens, Steve Vejcik, Leland Wilkinson, and Pei Zhang, Real Time Change Detection and Alerts from Highway Traffic Data, ACM/IEEE International Conference for High Performance Computing and Communications (SC '05). pdf

  92. Yunhong Gu and Robert Grossman, Supporting Configurable Congestion Control in Data Transport Services, ACM/IEEE International Conference for High Performance Computing and Communications (SC '05). pdf

  93. Joseph Bugajski, Robert Grossman, Eric Sumner, Tao Zhang, A Methodology for Establishing Information Quality Baselines for Complex, Distributed Systems, 10th International Conference on Information Quality (ICIQ), 2005. pdf

  94. L. Wilkinson, A. Anand and R. Grossman, Graph-theoretic scagnostics, Proceedings of the IEEE Information Visualization 2005 (INFOVIS'05), pages 157-164. pdf

  95. Rajmonda Sulo, Stephen Eick, Robert Grossman, DaVis: A tool for Visualizing Data Quality, Proceedings of the IEEE Information Visualization 2005 (INFOVIS'05). pdf

  96. Yong Mao, Yunhong Gu, Jia Chen and Robert L. Grossman, SDCS: Simplified Data Communications in Parallel/Distributed Applications, IEEE International Symposium on Cluster Computing and the Grid (CCGrid06), pages 292-295, 2006. pdf

  97. Greeshma Neglur, Robert L. Grossman, Natalia Maltsev, and Clement Yu, Using Term Lists and Inverted Files to Improve Search Speed for Metabolic Pathway Databases, 3rd International Workshop on Data Integration in the Life Sciences 2006 (DILS'06), Lecture Notes in Bioinformatics, Volume 4075, Springer-Verlag, Berlin, 2006, pages 168-184. pdf

  98. Yunhong Gu, Robert L. Grossman, Alex Szalay and Ani Thakar, Distributing the Sloan Digital Sky Survey Using UDT and Sector, Proceedings of e-Science 2006. pdf

  99. Joseph Bugajski, Robert L. Grossman, Eric Sumner and Steve Vejcik, Monitoring Data Quality for Very High Volume Transaction Systems, Proceedings of the 11th International Conference on Information Quality, 2006. pdf

  100. Rajmonda Sulo, Anushka Anand, Leland Wilkinson, Robert Grossman, Stephen Eick, Topographically-Based Real-time Traffic Anomaly Detection in a Metropolitan Highway System, Proceedings of the IEEE Information Visualization 2006 (INFOVIS'06). pdf

  101. Joseph M. Bugajski, Robert L. Grossman, and Steve Vejcik, A Service Oriented Architecture Supporting Data Interoperability for Payments Card Processing Systems, Proceedings of the International Conference on Service-Oriented Computing (ICSOC) 2006, Springer Lecture Notes in Computer Science, Volume 4296, 2006, pages 591-600. pdf

  102. Yong Mao, Yunhong Gu, Jia Chen, and Robert L. Grossman, FastPara: A High-Level Declarative Data-Parallel Programming Framework on Clusters, Parallel and Distributed Computing and Systems, 2006. pdf

  103. Joseph Bugajski, Chris Curry, Robert L. Grossman, David Locke, Steve Vejcik, Detecting Changes in Large Data Sets of Payment Card Data: A Case Study, Proceedings of The Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2007), ACM, 2007. pdf

  104. G. Caire, Robert L. Grossman and H. Vincent Poor, Wavelet transforms associated with finite cyclic groups, The Twenty-Sixth Asilomar Conference on Signals, Systems and Computers, Volume 1, pages 113 - 119, 1992. pdf

  105. Fang Fang, Robert L. Grossman and Ziangjun Liu, An Algorithm for Assigning Unique Keys To Metabolic Pathways, Proceedings of the 2007 IEEE International Conference on Bioinformatics and Biomedicine, pages 374-382, 2007. pdf

  106. Yunhong Gu, Robert L. Grossman and Joe Mambretti, A Peer-to-Peer Infrastructure for Distributing Large Scientific Data Sets over Wide Area High-Performance Networks: Experimental Studies Using Wide Area Layer 2 Services, Proceedings of the First International Conference on Networks for Grid Applications (GridNets 2007), ICST, ISBN: 978-963-9799-02-8, 2007. pdf

  107. Joseph Bugajski and Robert L. Grossman, An Alert Management Approach to Data Quality: Lessons Learned from the Visa Data Authority Program, Proceedings of the 12th International Conference on Information Quality, (ICIQ 2007). pdf

  108. Joseph Bugajski, Chris Curry, Robert L. Grossman, David Locke and Steve Vejcik, Data Quality Models for High Volume Transaction Streams: A Case Study, Proceedings of the Second Workshop on Data Mining Case Studies and Success Stories, ACM 2007. pdf

  109. Robert L. Grossman, A Review of Some Analytic Architectures for High Volume Transaction Systems, The 5th International Workshop on Data Mining Standards, Services and Platforms (DM-SSP '07), ACM, 2007, pages 23-28. pdf

  110. Chetan Gupta and Robert L. Grossman, Outlier Detection with Streaming Dyadic Decomposition, Proceedings of the 7th Industrial Conference on Data Mining, LNCS Volume 4597, Springer-Verlag, 2007, pages 77-91. pdf

  111. David Ferrucci, Robert L. Grossman, Anthony Levas, PMML and UIMA Based Frameworks For Deploying Analytic Applications and Services, Proceedings of the 4th International Workshop on Data Mining Standards, Services and Platforms (DM-SSP 06), ACM, New York, 2006, pages 14-26. pdf

  112. Robert L Grossman and Yunhong Gu, Data Mining Using High Performance Clouds: Experimental Studies Using Sector and Sphere, Proceedings of The 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), ACM, 2008, pages 920-927. pdf

  113. Yunhong Gu and Robert Grossman, UDTv4: Improvements in Performance and Usability, Proceedings of GridNets 2008, Springer-Verlag 2008. pdf

  114. Yunhong Gu and Robert Grossman, Exploring Data Parallelism and Locality in Wide Area Networks, Proceedings of the Workshop on Many-task Computing on Grids and Supercomputers (MTAGS), IEEE, 2008, pages 1-10. pdf

  115. Robert L Grossman, Michal Sabala, Yunhong Gu, Anushka Anand, Matt Handley, Rajmonda Sulo and Lee Wilkinson, Discovering Emergent Behavior from Network Packet Data: Lessons From the Angle Project, in Next Generation Data Mining, edited by Hillol Kargupta, Jiawei Han, Philip S Yu, Rajeev Motwani and Vipin Kumar, CRC Press, Boca Raton, 2009, pages 243-260. pdf

  116. Robert Grossman, Yunhong Gu, Michal Sabala, Collin Bennett, Jonathan Seidman and Joe Mambratti, The Open Cloud Testbed: A Wide Area Testbed for Cloud Computing Utilizing High Performance Network Services, GridNets 2009, Springer-Verlag, 2009. pdf

  117. Yunhong Gu and Robert L Grossman, Lessons Learned From a Year's Worth of Benchmarks of Large Data Clouds, 2nd Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS 2009), ACM, 2009. pdf

  118. Wenxuan Gao, Robert Grossman, Philip Yu, and Yunhong Gu, Why Naive Ensembles Do Not Work in Cloud Computing, Proceedings of the The First Workshop on Large-scale Data Mining: Theory and Applications (LDMTA 2009), 2009. pdf

  119. Collin Bennett, Robert L. Grossman, David Locke, Jonathan Seidman and Steve Vejcik, MalStone: Towards a Benchmark for Analytics on Large Data Clouds, The 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2010), ACM, 2010. pdf

  120. Robert L. Grossman, Yunhong Gu, Joe Mambretti, Michal Sabala, Alex Szalay, and Kevin White, An Overview of the Open Science Data Cloud, Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing (HPDC '10), ACM, 2010. pdf

  121. Yunhong Gu, Li Lu, Robert Grossman, and Andrew Yoo, Processing massive sized graphs using Sector/Sphere, 2010 IEEE Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS), pages 1-10, doi: 10.1109/MTAGS.2010.5699427. pdf

  122. Rajmonda Sulo, Tanya Berger-Wolf, and Robert Grossman, Meaningful selection of temporal resolution for dynamic networks, Proceedings of the Eighth Workshop on Mining and Learning with Graphs (MLG '10), ACM, New York, NY, USA, pages 127-136, DOI=10.1145/1830252.1830269. pdf

  123. Shi Yu, Robert Grossman and Andrey Rzhetsky, Global and Local Approach of Part-of-Speech Tagging for Large Corpora, Information Retrieval and Knowledge Discovery in Biomedical Text: Papers from the 2012 AAAI Fall Symposium, AAAI Press, Menlo Park, California, 2012. pdf

  124. Michael Hausenblas, Robert Grossman, Andreas Harth, Philippe Cudre-Mauroux: Large-scale Linked Data Processing - Cloud Computing to the Rescue?. CLOSER 2012, pages 246-251. pdf

  125. Daniel J. Mandl, Stuart Frye, Rob Sohlberg, Pat Cappelaere, Matthew Handy, Robert Grossman: The Namibia Early Flood Warning System, a CEOS pilot project, IEEE International Symposium on Geoscience and Remote Sensing (IGARSS) 2012, pages 3521-3524. pdf

  126. Wenxuan Gao, Lijia Ma, Christopher Brown, Matthew Slattery, Philip S. Yu, Robert L. Grossman, Kevin P. White, Discovering geometric patterns in genomic data, ACM International Conference on Bioinformatics, Computational Biology and Biomedicine (BCB 12), ACM Press, pages 147-154. pdf

  127. Heidi L. Alvarez, Malcolm Atkinson, Robert L. Grossman, Matthew Greenway, Christine Harvey, Allison P. Heath, Iraklis Klampanos, Joe J. Mambretti, Ray Powell, Rafael D. Suarez, Walt Wells and Kevin White, The Design of a Community Science Cloud: The Open Science Data Cloud Perspective, 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, ACM Press, 2012. pdf

  128. Sandhya Narayan, Stuart Bailey, Anand Daga, Matthew Greenway, Robert Grossman, Allison Heath and Ray Powell, OpenFlow Enabled Hadoop Over Local and Wide Area Clusters, 2012 SC Companion: High Performance Computing, Networking Storage and Analysis, IEEE Press, 2012. pdf

  129. Maria T. Patterson, Nikolas Anderson, Collin Bennett, Jacob Bruggemann, Robert L. Grossman, Matthew Handy, Vuong Ly, Daniel J. Mandl, Shane Pederson, James Pivarski, Ray Powell, Jonathan Spring, Walt Wells and John Xia, The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery, 2016 IEEE Second International Conference on Big Data Computing Service and Applications (BigDataService), Oxford, 2016, pages 156-165. pdf

  130. Jim Pivarski, Collin Bennett, and Robert L. Grossman, Deploying Analytics with the Portable Format for Analytics (PFA), in Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '16), ACM, New York, NY, USA, pages 579-588. DOI: http://dx.doi.org/10.1145/2939672.2939731 pdf

  131. Rajmonda Sulo Caceres, Tanya Berger-Wolf and Robert L. Grossman, Temporal Scale of Processes in Dynamic Networks, Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on, Vancouver, BC, Canada, December 11, 2011, DOI: 10.1109/ICDMW.2011.165 pdf

  132. Samuel L. Volchenboum, Suzanne M. Cox, Allison Heath, Adam Resnick, Susan L. Cohn, and Robert Grossman, Data commons to support pediatric cancer research, American Society of Clinical Oncology Educational Book 37, 2017, pages 746-752. pdf

  133. Renyu Zhang, Robert L. Grossman, Christopher Weber and Aly Khan, Evaluating and interpreting caption prediction for histopathology images, Machine Learning for Healthcare 2020, Virtual, in Proceedings of Machine Learning Research, Volume 126, pages 418-435, 2020. pdf

  134. Renyu Zhang, Aly Khan and Robert Grossman, Evaluation of Hyperbolic Attention in Histopathology Images, The 20th IEEE International Conference on BioInformatics And BioEngineering (BIBE-20), October 26-28, 2020. pdf

  135. Michael Hao Tong, Robert L. Grossman, and Haryadi S. Gunawi, Experiences in Managing the Performance and Reliability of a Large-Scale Genomics Cloud Platform, in 2021 USENIX Annual Technical Conference (USENIX ATC 21), pages 973-988, 2021. pdf

  136. Renyu Zhang, Aly Khan, Robert L. Grossman, Yuxin Chen, BALanCe: Deep Bayesian Active Learning via Equivalence Class Annealing, International Conference on Learning Representations (ICLR), 2023. pdf

  137. Martin L. Putra, In Kee Kim, Haryadi S. Gunawi, and Robert L. Grossman, CNT: Semi-Automatic Translation from CWL to Nextflow for Genomic Workflows, 2023 IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE). pdf

  138. Zhang, Renyu, Aly A. Khan, Yuxin Chen, and Robert L. Grossman, Enhancing Instance-Level Image Classification with Set-Level Labels, ICLR 2024. Also arXiv preprint arXiv:2311.05659 (2023). pdf

Books

  1. M. Beals, C. Fefferman, R. Grossman, Strictly Pseudoconvex Domains in Cn, Moscow, 1987, 286 pages, in Russian. Translation of Article 2.

  2. R. Grossman, editor, Symbolic Computation: Applications to Scientific Computing, SIAM, Philadelphia, 1989, 185 pages.

  3. R. L. Grossman, A. Nerode, A. P. Ravn, and H. Rischel, editors, Hybrid Systems, Lecture Notes in Computer Science, Volume 736, Springer-Verlag, New York, 1993.

  4. Yike Guo and Robert Grossman, editors, High Performance Data Mining: Scaling Algorithms, Applications and Systems, Kluwer Academic Publishers, 1999.

  5. R. L. Grossman, J. Han and V. Kumar, editors, Proceedings of the SIAM First International Conference on Data Mining (SDM-01), SIAM, 2001, ISBN 0-89871-495-8.

  6. Robert L. Grossman, Chandrika Kamath, Philip Kegelmeyer, Vipin Kumar, and Raju R. Namburu, Data Mining for Scientific and Engineering Applications, Kluwer Academic Publishing, 2001. ISBN 1-4020-0033-2.

  7. Robert Grossman, Jiawei Han, Vipin Kumar, Heikki Mannila, and Rajeev Motwani, editors, Proceedings of the Second SIAM International Conference on Data Mining, Society for Industrial and Applied Mathematics (SIAM), Philadelphia, 2002.

  8. Robert L. Grossman, Roberto Bayardo, Kristin Bennet, and Jaideep Vaidya, editors, Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2005), ACM Press, New York, 2005, ISBN 1-59593-135-X.

  9. Inderjit S. Dhillon, Yehuda Koren, Rayid Ghani, Ted E. Senator, Paul Bradley, Rajesh Parekh, Jingrui He, Robert L. Grossman, and Ramasamy Uthurusamy, editors, Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, New York, NY, USA, 2013.

Other Publications

  1. Robert Grossman, Simon Kasif, Reagan Moore, David Rocke, and Jeff Ullman, Data Mining Research: Opportunities and Challenges. A Report of three NSF Workshops on Mining Large, Massive, and Distributed Data, http://www.ncdm.uic.edu/m3d2.htm, 1998. pdf

  2. Haim Bodek, Robert Lee Grossman and Ivan Pulleyn, Detecting Network Intrusions through the Data Mining of Network Packet Data Using the ACT Algorithm, 1997. pdf

  3. Robert L. Grossman, Symbolic Computation and Flows of Differential Equations, Second Workshop on Computer Algebra, July 21, 1993, Rio de Janeiro.

  4. Andrew Baden and Robert L. Grossman, A Model for Computing at the SCC, SSC Technical Report, June 6, 1990. pdf

  5. KDD-2003 Workshop on Data Mining Standards, Services, and Platforms (DM-SSP 03), ACM SIGKDD Explorations, Volume 5, Issue 2, page 197, 2003. pdf

  6. Robert L. Grossman and David Radford, Bialgebra Deformations of Certain Universal Enveloping Algebras, Laboratory for Advanced Computing Technical Report, University of Illinois at Chicago, 1991. pdf

  7. This technical report is now archaic.

  8. R. L. Grossman, S. Mehta and X. Qin, Path planning by querying persistent stores of trajectory segments, Laboratory for Advanced Computing Technical Report Number LAC 93-R3, September, 1992. pdf

  9. Jason Leigh, Eric He, and Robert Grossman, Grid Networks and UDT Services, Protocols, and Technologies, in Franco Travostino, Joe Mambretti, and Gigi Karmous-Edwards, editors, Grid Networks: Enabling Grids with Advance Communication Technology, Wiley, 2006, pages 171-184.

  10. Robert L. Grossman, Yunhong Gu, Michal Sabala, and Joel J. Mambretti, Real Time, Distributed Detection of Anomalies and Emergent Behavior Using the Angle Algorithm, University of Illinois at Chicago, Laboratory for Advanced Computing, Technical Report, 2006. pdf

  11. Robert L. Grossman, Fifth International Workshop on Data Mining Standards, Services, and Platforms, Preface, Proceedings of The Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, 2007. pdf

  12. Bennett Bertenthal, Robert Grossman, David Hanley, Mark Hereld, Sarah Kenny, Gina Levow, Michael E. Papka, Steve Porges, Kavithaa Rajavenkateshwaran, Rick Stevens, Thomas Uram, and Wenjun Wu, Social Informatics Data Grid, Third International Conference on e-Social Science October 7-9, 2007, Ann Arbor, Michigan. pdf

  13. This technical report is now archaic.

  14. Gregory Piatetsky-Shapiro, Robert Grossman, Chabane Djeraba Ronen Feldman, Lise Getoor, Mohammed Zaki Is There A Grand Challenge or X-Prize for Data Mining?, Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM Press, 2006, pages 954 - 956. See also SIGKDD Explorations, Volume 8, Number 2, 2006. pdf

  15. Robert L Grossman and Yunhong Gu, On the Varieties of Clouds for Data Intensive Computing, Bulletin of the Technical Committee on Data Engineering, March 2009, Volume 32, Number 1, pages 44-50. pdf

  16. John Chaves, Chris Curry, Robert L. Grossman, David Locke and Steve Vejcik, Augustus: the Design and Architecture of a PMML-based Scoring Engine, in Proceedings of the 4th International Workshop on Data Mining Standards, Services and Platforms (DMSSP '06), ACM, New York, NY, 38-46. pdf

  17. Robert L. Grossman, What is Analytic Infrastructure and Why Should You Care?, SIGKDD Explorations, July 2009, Volume 11, Issue 1, pages 5-9. pdf