Parantapa Bhattacharya

I am Research Scientist at the Network Systems Science and Advanced Computing Division of the Biocomplexity Institute and Initiative at the University of Virginia . I am generally interested in building tools and systems for extracting useful information out of data. My research focuses on High Performance Computing, Agent Based Modeling, and Analysis of Large Datasets. I am also interested in Explainable AI with special interest in explaining Natural Language (NLP) models.

You can contact me at pb [at] parantapa [dot] net.

Publications

• “Multi-agent Simulations and Vaccine Allocation Strategies”. J. Chen, S. Hoops, P. Bhattacharya, D. Machi, and M. Marathe. Siam News, 2022.
  [URL]
• “Data-Driven Scalable Pipeline using National Agent-Based Models for Real-time Pandemic Response and Decision Support”. P. Bhattacharya, J. Chen, S. Hoops, D. Machi, B. Lewis, S. Venkatramanan, M. L. Wilson, B. Klahn, A. Adiga, B. Hurt, J. Outten, A. Adiga, A. Warren, H. Baek, P. Porebski, A. Marathe, D. Xie, S. Swarup, A. Vullikanti, H. Mortveit, S. Eubank, C. L. Barrett, and M. Marathe. The International Journal of High Performance Computing Applications (IJHPCA), 2022.
  [To Appear]
  [Finalist for the 2021 ACM Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research]
  [Article in Nature Computational Science]
• “AI-Driven Agent-Based Models to Study the Role of Vaccine Acceptance in Controlling COVID-19 Spread in the US”. P. Bhattacharya, D. Machi, J. Chen, S. Hoops, B. Lewis, H. Mortveit, S. Venkatramanan, M. L. Wilson, A. Marathe, P. Porebski, B. Klahn, J. Outten, A. Vullikanti, D. Xie, A. Adiga, S. Brown, C. Barrett, and M. Marathe. In Proceedings of the 2021 IEEE International Conference on Big Data (IEEE BigData). 2021.
  [PDF]
• “Integrated Directional Gradients: Feature Interaction Attribution for Neural NLP Models”. S. Sikdar, P. Bhattacharya, and K. Heese. In Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Main Conference) (ACL-IJCNLP). 2021.
  [PDF] [CODE]
• “PanSim + Sim-2APL: A Framework for Large-Scale Distributed Simulation with Complex Agents”. P. Bhattacharya, J. de Mooij, D. Dell'Anna, M. Dastani, B. Logan, S. Swarup. In Proceedings of The 9th International Workshop on Engineering Multi-Agent Systems (EMAS). 2021.
  [PDF] [PanSim CODE] [Sim2APL CODE]
• “Quantifying the Effects of Norms on COVID-19 Cases Using an Agent-based Simulation”. J. de Mooij, D. Dell'Anna, P. Bhattacharya, M. Dastani, B. Logan, S. Swarup. In Proceedings of The Multi-Agent-Based Simulation Workshop (MABS). 2021.
  [PDF]
• “Deepfake Videos in the Wild: Analysis and Detection”. J. Pu, N. Mangaokar, L. Kelly, P. Bhattacharya, K. Sundaram, M. Javed, B. Wang, B. Viswanath. In Proceedings of The Web Conference (WWW). 2021.
  [Preprint]
• “Scalable Epidemiological Workflows to Support COVID-19 Planning and Response”. D. Machi, P. Bhattacharya, S. Hoops, J. Chen, H. Mortveit, S. Venkatramanan, B. Lewis, M. Wilson, A. Fadikar, T. Maiden, C. L. Barrett, and M. V. Marathe. In Proceedings of the 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS). 2021.
  [PDF] [SLIDES] [Extended Preprint]
• “From 5Vs to 6Cs: Operationalizing Epidemic Data Management with COVID-19 Surveillance”. A. S. Peddireddy, D. Xie, P. Patil, M. L. Wilson, D. Machi, S. Venkatramanan, B. Klahn, P. Porebski, P. Bhattacharya, S. Dumbre, E. Raymond and M. Marathe. In Proceedings of the 2020 IEEE International Conference on Big Data (BigData), 2020.
  [COVID-19 Surveillance Dashboard] [Preprint]
• “An automated approach for finding spatio-temporal patterns in disease spread”. P. Sambaturu, P. Bhattacharya, J. Chen, B. Lewis, M. Marathe, S. Venkatramanan, A. Vullikanti. JMIR Public Health Surveillance, 2020.
  [PDF]
• “Jekyll: Attacking Medical Image Diagnostics using Deep Generative Models”. N. Mangaokar, J. Pu, P. Bhattacharya, C. K. Reddy and B. Viswanath. InProceedings of the 5th IEEE European Symposium on Security and Privacy (EuroS&P). Genova, Italy, 2020.
  [Preprint]
• “Learning Linear Influence Models in Social Networks from Transient Opinion Dynamics”. A De, S. Bhattacharya, P. Bhattacharya, N. Ganguly, and S. Chakrabarti. ACM Transactions on the Web (TWEB), 2019.
  [PDF]
• “The Matrix: An Agent-Based Modeling Framework for Data Intensive Simulations”. P. Bhattacharya, S. Ekanayake, C. J. Kuhlman, C. Lebiere, D. Morrison, S. Swarup, M. L. Wilson, and M. G. Orr. In Proceedings of the 2019 International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Montreal, Canada, 2019.
  [PDF] [SLIDES] [POSTER] [CODE] [Nominated for Best Paper]
• “Characterizing Deleted Tweets and their Authors”. P. Bhattacharya, and N. Ganguly. In Proceedings of the 10th AAAI International Conference on Web and Social Media (ICWSM). Cologne, Germany, 2016.
  [PDF] [POSTER]
• “On the Wisdom of Experts vs. Crowds: Discovering Trustworthy Topical News in Microblogs”. M. B. Zafar, P. Bhattacharya, N. Ganguly, S. Ghosh, and K. P. Gummadi. In Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW). San Francisco, California, USA, 2016.
  [PDF] [What is Happening]
• “Sampling Content from Online Social Networks: Comparing Random vs. Expert Sampling of the Twitter Stream”. M. B. Zafar, P. Bhattacharya, N. Ganguly, K. P. Gummadi, and S. Ghosh. ACM Transactions on the Web (TWEB), 2015.
  [PDF]
• “Learning a Linear Influence Model from Transient Opinion Dynamics”. A. De, S. Bhattacharya, P. Bhattacharya, N. Ganguly, and S. Chakrabarti. In Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM). Shanghai, China, 2014.
  [PDF]
• “Inferring User Interests in the Twitter Social Network”. P. Bhattacharya, M. B. Zafar, N. Ganguly, S. Ghosh, and K. P. Gummadi. In Proceedings of the 8th ACM Recommender System Conference (RecSys). Silicon Valley, California, USA, 2014.
  [PDF] [POSTER] [Who Likes What]
• “Deep Twitter Diving: Exploring Topical Groups in Microblogs at Scale”. P. Bhattacharya, S. Ghosh, J. Kulshrestha, M. Mondal, M. B. Zafar, N. Ganguly, and K. P. Gummadi. In Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW). Baltimore, Maryland, USA, 2014.
  [PDF] [SLIDES]
• “On Sampling the Wisdom of Crowds: Random vs. Expert Sampling of the Twitter Stream”. S. Ghosh, M. B. Zafar, P. Bhattacharya, N. Sharma, N. Ganguly, and K. P. Gummadi. In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM). San Francisco, California, USA, 2013.
  [PDF]
• “VMPatrol: Dynamic and Automated QoS for Virtual Machine Migrations”. V. Mann, A. Vishnoi, A. Iyer, and P. Bhattacharya. In Proceedings of the 8th International Conference on Network and Service Management (CNSM). Las Vegas, Nevada, USA, 2012.
  [PDF]
• “Remedy: Network-aware Steady State VM Management for Data Centers”. V. Mann, A. Gupta, P. Dutta, A. Vishnoi, P. Bhattacharya, R. Poddar, and A. Iyer. In Proceedings of the 11th International IFIP TC 6 Conference on Networking (Networking). Prague, Czech Republic, 2012.
  [PDF]
• “An Analytical Framework for Measuring Network Security using Exploit Dependency Graph”. P. Bhattacharya, and S. K. Ghosh. IET, Information Security, 2012.
  [PDF]

Preprints

• “Prioritizing allocation of COVID-19 vaccines based on social contacts increases vaccination effectiveness”. J. Chen, S. Hoops, A. Marathe, H. Mortveit, B. Lewis, S. Venkatramanan, A. Haddadan, P. Bhattacharya, A. Adiga, A. Vullikanti, A. Srinivasan, M. L. Wilson, G. Ehrlich, M. Fenster, S. Eubank, C. Barrett, and M. Marathe. medRxiv, 2021.

Education

Doctor of Philosophy
from IIT Kharagpur (2017)
Thesis Title: Characterizing Twitter Users for Building Social Systems

Master of Technology in Information Technology
from IIT Kharagpur (2010)

Bachelor of Engineering (Hons.) in Information Technology
from Bengal Engineering and Science University, Shibpur (2008)