I am a PhD candidate in Electrical Engineering at Northeastern University, working with the Machine Learning group @ SPIRAL supervised by Professor Jennifer Dy. My current research interests include continual learning, adversarial attacks, and leveraging them for transparent and interpretable machine learning. Additionally, I have worked on unsupervised 3D reconstruction and classification, time-series forecasting and implicit neural networks.

Previously, I worked as an AI and ML consultant with Endress+Hauser, Germany. I completed my Masters in EE at the Robotics and Computer Vision lab at KAIST, South Korea, under the supervision of Professor In So Kweon. I worked on occlusion‐robust vehicle re‐identification, and on utilizing adversarial attacks for understanding deep networks with relevant publications.

Besides my academic interests, I enjoy community service and reading biographies.

Research Interests

  • 3D reconstruction
  • Self-supervised continual learning
  • Adversarial attacks for robust and interpretable ML
  • 3D object detection, representation learning and reconstruction
  • 2D object detection, segmentation and tracking

Work Experience

   September 2024 ~
   Student Researcher, Project Starline, Google Cambridge, MA

   May - August 2024
   Research Intern, Project Starline, Google LA

   Sept 2021 - Present
   Graduate Research Assistant at Machine Learning Lab, SPIRAL

   Sept 2020 - Aug 2021
   External Consultant for ML and AI

   Sept 2018 - Aug 2020
   Graduate Research Assistant at Robotics and Computer Vision (RCV) Lab

   Sept 2015 - May 2018
   Research Intern at TUKL NUST R&D Centre

News

Teaching

Academic Service

  • Workflow Chair: AAAI 2024
    • Managed the AAAI 2024 paper review process for 12,100 submissions, working with 7k reviewers, 765 senior program committee (SPC), and 320 area chairs (AC).
    • Used topic modeling and text similarity to determine reviewer, SPC, and AC assignments.
  • Conference Reviewer: CVPR, ECCV, ACCV 2024, ICCV 2023, NeurIPS 2023 (New in ML Workshop)
  • Volunteer: ICML 2022