I am an Assistant Professor of Computer Science at Virginia Tech. Prior to VT, I spent a year as research scientist (Research Staff Member) at IBM Almaden Research Center, working on Machine Learning, Natural Language Processing and Information Retrieval problems. I obtained my Ph.D. from the Computer Science Department, University of Illinois at Urbana - Champaign, under the supervision of Prof. ChengXiang Zhai, Text Information Management and Analysis Group (TIMAN).

My research interests are broadly defined at the intersection of Data Science, Big Data, Machine Learning, and Artificial Intelligence. My work revolves around machine learning challenges related to data, e.g., learning with limited imperfect supervision, self-supervision, zero-shot learning, adversarial training, essentially work under the theme of Data Quality in Machine Learning, and multi-modal learning with applications to Vision + Language, e.g., video understanding, language grounding, (bio)medical imaging, etc. Overall, I am interested in building intelligent task assistants that augment human intelligence. I have extensively collaborated on transdisciplinary projects that touch societal dimensions, in areas ranging from Health Informatics and Genomics to Psychology, Education and Social Computing. You can learn more by looking at my publications.

News

  • June, 2022: Will be giving a keynote at ACM PETRA 2022. Also serving as the PETRA’22 Doctoral Consortium Chair. Looking forward to meeting students and conference attendees.
  • April, 2022: Thrilled to join the NeurIPS 2022 Organizing Commitee as an Expo co-Chair!
  • March, 2022: Gave a talk at the Women in STEM Mentoring Seminars. Slides are available here.
  • February, 2022: We are grateful to receive an NSF EAGER CMMI-AM grant!
  • January, 2022: TriGORank, a gene ontology enriched learning-to-rank model for trigenic fitness prediction tasks was published at the IEEE BIBM’21 BiOK 2021 workshop. Joint work with the Computer Science Department and the Carl R. Woese Institute for Genomic Biology at the University of Illinois at Urbana-Champaign.
  • January, 2022: Recent paper on unsupervised novelty detection in structural health monitoring (SHM) accepted to the Computer-Aided Civil and Infrastructure Engineering (CACAIE) Journal. Joint work with the Department of Civil and Environmental Engineering at Virginia Tech and the Department of Civil Engineering at the KN Toosi University of Technology in Tehran, Iran.
  • October, 2021: Chest ImaGenome Dataset for Clinical Reasoning is accepted to NeurIPS’21 Datasets and Benchmarks Track. Paper, dataset, and reviews are available at OpenReview. Joint work with IBM Research, Rensselaer Polytechnic Institute, MIT Critical Data, Albert Einstein Healthcare Network and Harvard Medical School.
  • August, 2021: My student’s paper on truncated sparse bit-vector representations was accepted to CIKM’21 Applied Track (joint work with IBM Research).
  • August, 2021: Our work on HPV vaccine risk perceptions on social media was accepted to Journal of Medical Internet Research (in collaboration with the University of Illinois at Urbana-Champaign and the University of Illinois Chicago). News Release
  • May, 2021: AnaXNet paper accepted to MICCAI’21 (Early accept top 13%, joint work with IBM Research and RPI).
  • April, 2021: Paper accepted to SIGIR’21 and workshop paper accepted to PerInt@PETRA’21.
  • April, 2021: Will be teaching CS5604: Information Storage and Retrieval in Fall 2021.
  • March, 2021: Our multimodal Chest X-ray data was recently published in Nature Scientific Data, accompanied with a short blog describing the work. We show that utilizing eye-gaze information can lead to improved performance and guide the model to produce more accurate activation maps.
  • December, 2020: Will be teaching a new seminar course, CS6604: Data Challenges in Machine Learning.