Kyung Min (Brian) Ko

ko120 [at] purdue [dot] edu

prof_pic.jpg
Research Assistant @ Purdue University
School of Electrical and Computer Engineering
ko120 [at] purdue [dot] edu

Research Interests: Trustworthy ML, LLM, Reinforcemennt Learning

Welcome! I am a recent graduate in Electrical Engineering from the School of Electrical and Computer Engineering at Purdue University, Class of Spring 2024, with distinction. Under the guidance of Prof.David Inouye, I have cultivated a passion for building trustworthy machine learning tools through probabilistic methods.

Previously, I was a research intern at Georgia Tech, advised by Prof. Siva Theja Maguluri, focusing on reinforcement learning throughout the NSF-funded summer research program. Furthermore, I was a research intern at Purdue University under the mentorship of Prof. Lin Tan, also as part of an NSF-funded summer research program, focusing on the application of code LLMs to solve the malware authorship problem.

My research interests span across trustworthy machine learning, large language models (LLMs) and reinforcement learning.

news

May 23, 2024 I graduated Purdue University with distinction in ECE!
Mar 15, 2024 I am starting my research assistant position at Prof. David I. Inouye’s lab focusing on Truthyworthy ML!
May 28, 2023 Accepted to Purdue NSF-SURF program!
May 22, 2023 I finished my military service @ South Korea!

selected publications

  1. IEEE RO-MAN Oral
    Backward Curriculum Reinforcement Learning
    Kyung Min Ko
    In 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2023
  2. Pre-Print
    A Unified Framework for Comparing Distribution Matching Methods Across Trustworthy Machine Learning Tasks
    Kyung Min Ko, Ziyu Gong, Jim Lim, and David Inouye
    2024
  3. Pre-Print
    V-advCSE: Virtual Adversarial Contrastive Learning for Sentence Embeddings
    Kyung Min Ko
    2023
  4. Pre-Print
    Unmasking the Author: Exploiting Code Language Models and Contrastive Learning in Binary Code Authorship Attribution
    Kyung Min Ko, Nan Jiang, and Lin Tan
    2023