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Jack Lu I’m a third-year Computer Science Ph.D. student in the CILVR lab at NYU Courant , advised by Mengye Ren and collaborating with Greg Durrett and Seunghoon Hong . My research is supported by the NSERC PGS-D Scholarship . Prior to joining NYU, I received my bachelor’s degree in Computer Science and Mathematics from the University of Waterloo .
I’m currently interested in:
LLM Reasoning : understanding and improving how LLMs solve and verify problems that require complex reasoning. Adaptive Models and Agents : efficiently adapting diffusion and language models to out-of-distribution tasks, new knowledge, and dynamic environments. Previously, I did research and software engineering for autonomous driving and ML for health at NVIDIA , Waabi/Uber-ATG , IBM , and DarwinAI . I was fortunate to have worked with Raquel Urtasun , Sanja Fidler , and Alexander Wong .
I’m happy to discuss collaboration, mentorship, and research in general. You can email me for a virtual or in-person chat. My office is at 60 5th Ave, New York.
Jul 07, 2025 Our work, Context Tuning for In-Context Optimization , was accepted by the ICML 2025 Test-Time Adaptation Workshop. Jul 01, 2024 Our work, ProCreate, Don’t Reproduce! Propulsive Energy Diffusion for Creative Generation , was accepted by ECCV 2024. Apr 25, 2024 I was selected to receive the NSERC PGS-D Scholarship to support my PhD at NYU. Jan 29, 2024 Our work, SceneControl: Diffusion for Controllable Traffic Scene Generation , was accepted by ICRA 2024. Sep 01, 2023 I started my PhD in Computer Science at NYU, advised by Mengye Ren .
ArXiv When Does Verification Pay Off? A Closer Look at LLMs as Solution Verifiers
Dec 2025
ArXiv SkillFactory: Self-Distillation For Learning Cognitive Behaviors
Dec 2025
ICML Context Tuning for In-Context Optimization
ICML Test-Time Adaptation Workshop , Jul 2025
ProCreate, Don’t Reproduce! Propulsive Energy Diffusion for Creative Generation
European Conference on Computer Vision (ECCV) , Oct 2024
SceneControl: Diffusion for Controllable Traffic Scene Generation
IEEE International Conference on Robotics and Automation (ICRA) , May 2024
Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression From Chest CT Images
Frontiers in Artificial Intelligence , Nov 2021
Surviving the Plato's Cave