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
- [04/20/2025] I will be interning with the Pixel Biometrics team at Google this Summer!
- [01/22/2025] Our paper “STAR: Stability-Inducing Weight Perturbation for Continual Learning” got accepted at ICLR 2025.
- [01/05/2025] Our paper “ADAPT to Robustify Prompt Tuning Vision Transformers” got accepted at TMLR.
- [03/16/2024] I will be interning with the Project Starline team at Google this Summer!
- [05/01/2023] I will be serving as a workflow chair for AAAI 2024.
- [12/01/2022] Passed my PhD Qualification Exam.
- [07/18/2022] Presented my research on Sparse and Interpretable Adversarial Attacks at WiML Workshop @ ICML’22.
- [09/01/2021] Started my PhD at Northeastern University, under the supervision of Professor Jennifer Dy.
- [09/01/2020] Starting working as a Consultant for ML/AI at Endress+Hauser, Germany (remote).
- [06/28/2020] Completed my MS in Electrical Engineering at KAIST under the supervision of Professor In So Kweon.
- [06/15/2020] Successfully defended my Master’s thesis titled “Occlusion-Robust Object Re-identification”.
- [12/20/2019] Gave an invited talk about my research on adversarial attacks at KEEP-I (KAIST EE Partners - International).
- [09/06/2019] Delivered an invited talk reflecting on my academic and overall experience at KAIST at KAIST EE camp.
- [09/01/2018] Started my Master’s at KAIST supervised by Professor In So Kweon.
Teaching
- EECE7397 Advanced Machine Learning, Northeastern University: Teaching Assistant with Professor Jennifer Dy.
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