Harshinee Sriram

PhD student in AI for Health
Email: harshinee [dot] sriram [at] ubc [dot] ca

See my work

Who am I?

Hi! I am Harshinee.

  • I am currently pursuing my PhD in Computer Science at the University of British Columbia (UBC), Vancouver under the co-supervision of Miriam Spering and Margo Seltzer.
  • I am interested in investigating how to leverage eye-tracking (ET) data to build Deep Learning models that can be used for the screening of neurodegenerative diseases (e.g., Alzheimer's and Parkinson's Disease).
  • My research areas of interest are: User Modelling, Human-Centered AI, Explainable AI (XAI), and Responsible & Trustworthy AI.
  • I am currently also an Applied Scientist Intern at the Amazon Web Services (AWS) Cloud Innovation Centre , where my work involves building cloud-based solutions using state-of-the-art concepts in AI to solve challenges faced by the community.
  • Check out my most up-to-date resume below!

Publications

Click here to view my Google scholar profile!

  • [C2] Harshinee Sriram, Cristina Conati, and Thalia Field, "Classification of Alzheimer's Disease with Deep Learning on Eye-tracking Data.", 25th ACM International Conference on Multimodal Interaction (ICMI) 2023. [Arxiv link]

  • [W1] Harshinee Sriram and Cristina Conati, "Evaluating the overall sensitivity of saliency-based explanation methods.", International Joint Conference on Artificial Intelligence (IJCAI) Workshop on Explainable Artificial Intelligence 2023. [Poster] [Arxiv link]

  • [C1] Anuj Harisinghani, Harshinee Sriram, Cristina Conati, Giuseppe Carenini, Thalia Field, Hyeju Jang, Gabriel Murray, "Classification of Alzheimer’s using deep-learning methods on webcam-based gaze data", ACM Symposium on Eye Tracking Research Applications (ETRA) 2023. [Paper]