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I am a data scientist at the research institute of Children's Hospital of Philadelphia (CHOP). My research focuses on designing efficient machine learning methods, including natural language processing (NLP) and multimodal techniques for electronic health records (EHR).
I finished my Ph.D. studies in Computer Science at Drexel University, where I was co-advised by Drs. Dario Salvucci and Ed Kim. I defended my dissertation entitled "Representation Learning on Sequential and Temporal Data Manifolds" in May 2023.
My dissertation research focused on understanding sequential data using representation learning models in various domains such as health, driving, and machine vision.
As a research assistant at the Sparse Coding lab, I worked on providing energy-efficient and robust-to-bias solutions to computer vision problems using neuromorphic concepts.
For my master's, I worked on modeling the visual pathway using unsupervised spiking neural networks for object recognition and identification. Before heading to Ph.D., I worked in the industry as a software analyst and tester.
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June 2023: I presented my papers as an oral presentation at WiCV workshop of CVPR 2023.
May 2023: I joined the Children's Hospital of Philadelphia (CHOP) research as a senior data scientist.
May 2023: I successfully defended my PhD dissertation on Representation Learning on Sequential and Temporal Data Manifolds.
April 2023: I received the Three Minute Thesis (3MT) People’s Choice Award at Drexel University. My talk was entitled When AI "Sees" It Wrong: Understanding Weaknesses and Building Robustness in Vision.
April 2023: Our paper ''Perception Over Time: Temporal Dynamics for Robust Image Understanding", was accepted as an oral in the WiCV workshop at CVPR 2023 (Top 10%).
April 2023: Our work on phenotype embedding was featured in media, including CHOP PR, ACM Communications, EurekAlert!
March 2023: I had the pleasure to serve as a judge at Philly Codefest.
March 2023: Our paper "Enriching Representation Learning Using 53 Million Patient Notes through Human Phenotype Ontology Embedding," was accepted to the Journal of Artificial Intelligence in Medicine.
July 2022: Our pre-print, "Enriching Representation Learning Using 53 Million Patient Notes through Human Phenotype Ontology Embedding," is out. This work was my focus area during my internship at CHOP research.
June 2022: Joined BOSCH Center for Artificial Intelligence (BCAI) as a machine learning research intern in the Robust and Safe Deep Learning team.
June 2022: Received the Shabahang annual scholarship award (3rd place) for outstanding achievements.
May 2022: Invited talk on Robust Perception at Drexel AI 2022 symposium.
Mar 2022: Our pre-print, "Perception Over Time: Temporal Dynamics for Robust Image Understanding," is out.
Jan. 2022: Invited to present my work on visual perception over time for the Visual Algorithms Research team at Intel.
Dec. 2021: Attended NeurIPS 2021 and volunteered at the WiML 2021 Virtual Workshop
Nov. 2021: Presented a part of my internship work at the MidAtlantic Bioinformatics Conference.
Oct. 2021: Presented our study on comparing human and machine perception over time at GHC21.
Sep. 2021: Received the AnitaB.org student scholarship to attend GHC21.
Jul. 2021: Received travel funding to attend ICML 2021. I also organized a session at the WiML Un-Workshop.
Jun. 2021: Joined the research institute of the Children's Hospital of Philadelphia (CHOP) as a research intern in machine learning.
Jun. 2020: Received the Outstanding Research Assistant Award from the Department of Computer Science, Drexel University.
Apr. 2021: Presented our study on driving anomaly detection at CRA-WP 2021.
Apr. 2021: Our work on analyzing the confidence of deep neural networks on object recognition over time got accepted to WiCV @ CVPR 2021.
Feb. 2021: Co-organized a poster session for our CCI PhD students. I also presented my work on TBI driving.
Jan. 2021: Got accepted to the 2020-2021 class of Google’s CS Research Mentorship Program (CSRMP)
Dec. 2020: Attended NeurIPS 2020 and volunteered at the WiML 2020 Virtual Workshop
Oct. 2020: Presented our work on Concussed Driving Classification at Human Factors and Ergonomics (HFES) 2020
Sep. 2020: Presented our work at Student Research Competition (SRC), ACM at GHC20 (Only 9 graduate students were accepted).
Sep. 2020: Joined the Sparse Coding Lab at Drexel and started working on neuromorphic software.
Jul-Aug 2020: Attended the Neuromatch Academy (NMA) computation neuroscience summer school.
May. 2020: Received the Outstanding Teaching Assistant Award from the Department of Computer Science, Drexel University.
Apr-Jun 2020: TAed CS615, Deep Learning graduate course at Drexel.
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