Photo of Wei Ding, PhD

Wei Ding, PhD

University Of Massachusetts - Boston

University Of Massachusetts - Boston
Phone: (617) 287-6428
Fax: (617) 287-6438


ding@cs.umb.edu

Photo of Wei Ding, PhD

University Of Massachusetts - Boston
Phone: (617) 287-6428
Fax: (617) 287-6438


ding@cs.umb.edu

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Wei Ding, PhD

University Of Massachusetts - Boston

EDUCATIONAL TITLES

  • Assistant Professor, College of Science and Math, University Of Massachusetts - Boston
  • Assistant Professor, Computer Science, University Of Massachusetts - Boston

HCC PROGRAM AFFILIATION

Research Abstract

Wei Ding received her Ph.D. degree in Computer Science from the University of Houston in 2008. She has been an Assistant Professor of Computer Science in the University of Massachusetts Boston since 2008. Her research interests include data mining, machine learning, artificial intelligence, computational semantics, and with applications to health science, astronomy, geosciences, and environmental sciences. She has published more than 85 referred research papers, 1 book, and has 2 patents. She is an Associate Editor of Knowledge and Information Systems (KAIS) and an editorial board member of the Journal of Information System Education (JISE), the Journal of Big Data, and the Social Network Analysis and Mining Journal. She is the recipient of a Best Paper Award at the 2011 IEEE International Conference on Tools with Artificial Intelligence (ICTAI), a Best Paper Award at the 2010 IEEE International Conference on Cognitive Informatics (ICCI), a Best Poster Presentation award at the 2008 ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPAITAL GIS), and a Best PhD Work Award between 2007 and 2010 from the University of Houston. Her research projects are currently sponsored by NASA and DOE. She is an IEEE senior member and an ACM member.

Publications from Harvard Catalyst Profiles

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  • Hampel PJ, Swaminathan M, Rogers KA, Parry EM, Burger JA, Davids MS, Ding W, Ferrajoli A, Hyak JM, Jain N, Kenderian SS, Wang Y, Wierda WG, Woyach JA, Parikh SA, Thompson PA. A multicenter study of venetoclax-based treatment for patients with Richter transformation of chronic lymphocytic leukemia. Blood Adv 2024; 8:2342-2350. PubMed
  • Woyach JA, Perez Burbano GE, Ruppert AS, Miller CR, Heerema NA, Zhao W, Wall A, Ding W, Bartlett NL, Brander DM, Barr PM, Rogers KA, Parikh SA, Stephens DM, Brown JR, Lozanski G, Blachly JS, Nattam S, Larson RA, Erba HP, Litzow MR, Luger SM, Owen C, Kuzma C, Abramson JS, Little RF, Dinner SN, Stone RM, Uy GL, Stock W, Mandrekar SJ, Byrd JC. Long-term Follow-up from A041202 Shows Continued Efficacy of Ibrutinib Regimens for Older Adults with CLL. Blood 2024. PubMed
  • Ruppert AS, Booth AM, Ding W, Bartlett NL, Brander DM, Coutre S, Brown JR, Nattam S, Larson RA, Erba H, Litzow M, Owen C, Kuzma CS, Abramson JS, Little RF, Smith SE, Stone RM, Byrd JC, Mandrekar SJ, Woyach JA. Adverse event burden in older patients with CLL receiving bendamustine plus rituximab or ibrutinib regimens: Alliance A041202. Leukemia 2021. PubMed
  • Kuijjer ML, Paulson JN, Salzman P, Ding W, Quackenbush J. Cancer subtype identification using somatic mutation data. Br J Cancer 2018. PubMed
  • Kang T, Ding W, Zhang L, Ziemek D, Zarringhalam K. A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data. BMC Bioinformatics 2017; 18:565. PubMed
  • W. Ding, T. Stepinski, Y. Mu, L. Bandeira, R. Vilalta, Y. Wu, Z. Lu, T. Cao, X. Wu. Sub-Kilometer Crater Discovery with Boosting and Transfer Learning .
  • K. Yue, A. Yang, W. Ding, and P. Chen. Open Courseware and Computer Science Education .
  • W. Ding, T. Stepinski, R. Parmar, D. Jiang, C. F. Eick. Discovery of Feature-Based Hot Spots Using Supervised Clustering .
  • P. Chen, W. Ding, C. Ding. A Lexical Knowledge Representation Model for Natural Language Understanding .
  • P. Chen, W. Ding, M. Choly, C. Bowes. Word Sense Disambiguation with Automatically Acquired Knowledge .
  • T. Stepinski, W. Ding, C. Eick. Controlling Patterns of Geospatial Phenomena .
  • W. Ding, C. Eick, X. Yuan, J. Wang, J. Nicot,. A Framework for Regional Association Rule Mining and Scoping in Spatial Datasets .
  • X. Zhu, W. Ding, P. Yu, C. Zhang. One-Class Learning and Concept Summarization for Data Streams .
  • Y. Mu, H. Lo, W. Ding, K. Amaral, S. E. Crouter. Bipart: Learning Block Structure for Activity Detection TKDE .
  • X. Wu, X. Zu, G. Wu, W. Ding. Data Mining with Big Data TKDE .
  • P. Chen, W. Ding, W. Garcia. Adaptive Study Design through Semantic Association Rule Analysis .
  • L. Bandeira, W. Ding, T.F. Stepinski. Detection of Sub-Kilometer Craters in High Resolution Planetary Images Using Shape and Texture Features .
  • S. Liu, W. Ding, F. Gao, T. Stepinski. Adaptive Selective Learning for Automatic Identification of Sub-Kilometer Craters .
  • K. Yu, X. Wu, W. Ding, H. Wang. Exploring Causal Relationships with Streaming Features .
  • Y. Wu, L. Wang, J. Ren, W. Ding, X. Wu. Mining Sequential Patterns with Periodic Wildcard Gaps .
  • X. Wu, K. Yu, W. Ding, H. Wang, and X. Zhu. Online Feature Selection with Streaming Features TPAMI .
  • D. Wang, W. Ding, H. Lo, T. Stepinski, J. Salazar, and M. Morabito. Crime Hotspot Mapping Using the Crime Related Factors--A Spatial Data Mining Approach .
  • K. Yu, W. Ding, H. Wang, X. Wu. Bridging Causal Relevance and Pattern Discriminability: Mining Emerging Patterns from High-Dimensional Data TKDE .
  • Y. Mu, W. Ding, D. Tao. Local Discriminative Distance Metrics Ensemble Learning .
  • D. Wang, W. Ding, H. Lo, M. Morabito, P. Chen, J. Salazar, and T. Stepinski,. Understanding the Spatial Distribution of Crime Based on Its Related Variables Using Geospatial Discriminative Pattern .
  • X. Wu, F. Xie, G. Wu, and W. Ding. PNFS: Personalized Web News Filtering and Summarization .
  • J. Cohen, W. Ding. Crater Detection via Genetic Search Methods to Reduce Image Features .
  • R. Vetro, D. A. Simovici, W. Ding,. Entropy Quad-Trees for High Complexity Regions Detection .
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