Mahashweta Das

Sr. Staff Research Scientist

Research areas: Data Mining, Machine Learning and Databases

Biography

Dr. Mahashweta Das joined Visa Research as a Senior Research Scientist in December 2016, and is currently a Senior Staff Research Scientist. Mahashweta received her Ph.D. in Computer Science from the University of Texas at Arlington in 2013. She received her M.S. in Computer Science from The Ohio State University, and received her B.S. in Computer Science and Engineering from Jadavpur University in 2007. Prior to joining Visa, Mahashweta was a research intern at Hewlett Packard Labs, building big data analytics solutions for HPE’s ‘The Machine.” Before working at Hewlett Packard, she was a Graduate Research Assistant at The University of Texas at Arlington, a Summer Research Intern at Yahoo! Research and Technicolor, respectively.

As a member of the Security team, her research interests are in large-scale mining, machine learning, big data analytics, databases, information retrieval and algorithms. She has published over fifteen articles in several international conferences and journals, including International Conference on Very Large Data Bases (VLDB), Special Interest Group on Knowledge Discovery in Data (SIGKDD), Association for Computing Machinery's Special Interest Group on Management of Data (SIGMOD), SIAM International Conference on Data Mining (SDM) and others, and regularly serves on the program committees of these conferences. Dr. Das is the recipient of numerous awards, including an Honorable Mention for the 2014 Doctoral Dissertation Award for her Ph.D. thesis, and the 2012 Best Paper Award at VLDB for her paper titled 'Who Tags What? An Analysis Framework.'

Conferences

  • Das, M., Morales, Gianmarco De Francisci, Gionis, A., & Weber, I. (2019). Learning to question: Leveraging User Preferences for Shopping Advice. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
  • Das, M., Simitsis, A., & Wilkinson, K. (2016). A hybrid solution for mixed workloads on dynamic graphs. International Workshop on Graph Data Management Experiences and Systems.
  • Kannapalli, R., Nazi, A., Das, M., & Das, G. (2016). AD-WIRE: Add-on for Web Item Reviewing System. International Conference on Very Large Data Bases (VLDB).
  • Das, M., & Das, G. (2015). Structured analytics in social media. International Conference on Very Large Data Bases, 8(12), 2046–2047.
  • Abon Chaudhuri & Mahashweta Das. (2015). Crowd MGR: Interactive Visual Analytics to Interpret Crowdsourced Data. Workshop on Interactive Data Exploration and Analytics, held in conjunction with ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
  • Nazi, A., Das, M., & Das, G. (2015). The TagAdvisor: Luring the Lurkers to Review Web Items. ACM SIGMOD International Conference on Management of Data
  • Das, M., Thirumuruganathan, S., Amer-Yahia, S., Das, G., & Yu, C. (2013). An expressive framework and efficient algorithms for the analysis of collaborative tagging. The VLDB Journal, 23(2), 201–226.
  • Das, M., Rahman, H., Das, G., & Hristidis, V. (2013). Generating informative snippet to maximize item visibility. ACM International Conference on Conference on Information & Knowledge Management.
  • Das, M. (2013). Exploratory Mining of Collaborative Social Content. ACM SIGMOD International Conference on Data Management.
  • Das, M., Thirumuruganathan, S., Amer-Yahia, S., Das, G., & Cong, Y. (2012). Who Tags What? An Analysis Framework. International Conference on Very Large Data Bases.
  • Das, M., Amer-Yahia, S., & Das, G. (2011). MRI: Meaningful Interpretations of Collaborative Ratings. International Conference on Very Large Data Bases.
  • Das, M., Das, G., & Hristidis, V. (2011). Leveraging collaborative tagging for web item design. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
  • Das, M., Deepak, P., Prasad, M., Deshpande, & Kannan, R. (2011). Fast Rule Mining Over Multi-Dimensional Windows. SIAM International Conference on Data Mining.
  • Das, M., & Parthasarathy, S. (2009). Anomaly detection and spatio-temporal analysis of global climate system. International Workshop on Knowledge Discovery from Sensor Data.

Patents

  • Morales, G. D., Das, M., Gionis, A., & Weber, I. (2001). Method and apparatus to build flowcharts for e-shopping recommendations. U.S. Patent No. 20,140,458,720. U.S. Patent and Trademark Office.