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Short Bio

I have experience in Vision, RL, Generative Models, Sequence Models, Self-supervised Learning, GCNs, LLMs. My PhD thesis revolves around multiple aspects of LLM agents, including pretraining, evaluation, and prompting architectures.

Education

  • 2021 - Current
    PhD in Machine Learning
    Carnegie Mellon University, Pittsburgh, PA, USA
  • 2017 - 2020
    B.S. in Computer Science
    Carnegie Mellon University, Pittsburgh, PA, USA
    • B.S. in Computer Science (Major GPA 3.91/4.0)
    • Minor in Machine Learning (Minor GPA 4.0/4.0)
    • Department Honors and University Honors
    • Alumni Award for Undergraduate Excellence

Research Experience

  • Fall 2023
    Consultant
    Microsoft Research | Host: Dr. Yuanzhi Li and Dr. Sébastien Bubeck
    • GPT...
  • Summer 2023
    Research Intern
    Microsoft Research | Host: Dr. Yuanzhi Li and Dr. Sébastien Bubeck
    • GPT...
  • Summer 2022
    Research Intern
    IBM Research | Host: Yuya Ong and Dr. Taiga Nakamura
    • Graph-based recommender-system that operates unstructured long texts with the use of large language models. SOTA at competitive benchmarks.
  • 2021
    Research Assistant
    Machine Learning Department (in collaboration with Apple A.I. Research) | With Dr. Ruslan Salakhutdinov, Dr. Shuangfei Zhai, and Dr. Joshua M. Susskind
    • Offline RL and Energy Based Models formulation for sequence generation.
  • Summer 2020
    Research Intern
    Apple A.I. Research | Host: Dr. Hanlin Goh and Dr. Joshua M. Susskind
    • Uncertainty estimation to stabilize actor-critic based offline reinforcement learning.
  • Summer 2020
    Research Assistant
    MultiComp Lab, CMU | With Dr. Ruslan Salakhutdinov and Dr. Louis-Philippe Morency
    • An information-theoretical explanation for the effectiveness of the unsupervised or self-supervised learned representations. The explanation inspires new loss function designs.
    • Policy based unsupervised domain transfer framework for visual navigation. Obtains promising results on few-shot sim2real indoor navigation.
  • 2019 - 2020
    Research Assistant
    Machine Learning Department | With Dr. Zhiting Hu and Dr. Eric P. Xing
    • Novel GAN formulation through variational inference and constrained reinforcement learning that leads to probability ratio clipping and discriminator re-weighting.
  • 2018 - 2019
    Research Assistant
    MultiComp Lab, CMU | With Dr. Louis-Philippe Morency
    • Unsupervised Facial Landmark detection and structure-from motion.
  • 2018 - 2019
    Research Assistant
    Biorobotics Lab, CMU | With Dr. Guillaume Sartoretti and Dr. Howie Choset
    • Asynchronous Reinforcement Learning for collaborative robotic manipulation tasks.
    • Asynchronous Reinforcement Learning for collaborative construction.

Media Coverage

Honors and Awards

  • 2019
    • School of Computer Science Alumni Award for Undergraduate Excellence
    • $2000 Award at IBM BlueHack
  • 2018
    • Grand Award at HackAuton 2018
    • Builders’ Choice and Staff’s Choice at Build18 2018
  • 2017
    • Most Entrepreneurial Hack at HackCMU
    • Silver Tier at Halite 2 Competition