Chidubem Arachie

Doctoral Candidate

Kelly 219
Department of Computer Science
Virginia Tech
Blacksburg, Virginia
Email: achid17[at]vt[dot]edu



I am a Ph.D. student in the computer science department at Virginia Tech. I work in the Machine Learning Laboratory, advised by Bert Huang. I am also a member of the Discovery Analytics Center (DAC) at Virginia Tech. I received my bachelor's degree in Computer Science from American University of Nigeria.

Research Interests

My research investigates new methods for weakly supervised learning with special focus on adversarial learning and constrained optimization. The aim of my work is to find effective and efficient ways to combine human knowledge to algorithms that train with weak learners.


  • Virginia Polytechnic Institute and State University
    Ph.D. Student, Department of Computer Science, school of Engineering

  • American University of Nigeria
    B.S. in Computer Science and Technology

  • American University, Washington DC
    Study Abroad


I have served as a teaching assistant in the courses listed below where my roles include but not limited to grading, organizing programming labs and assisting students with their projects and assignments during my office hours.

  • Software Design & Data Structures, Fall 2018

  • Object-Oriented Programming w/Java, Summer 2018. Fall 2020

  • Data and Algorithm Analysis, Spring 2018. Spring 2021

  • Intro to Software Design, Fall 2017


  • Constrained Labeling for Weakly Supervised Learning
    Chidubem Arachie, Bert Huang
    Uncertainty in Artificial Intelligence (UAI), 2021.

  • A General Framework for Adversarial Label Learning
    Chidubem Arachie, Bert Huang
    Journal of Machine Learning Research (JMLR), 2021.

  • Unsupervised Detection of Sub-events in Large Scale Disasters
    Chidubem Arachie, Manas Gaur, Sam Anzaroot, William Groves, Ke Zhang, Alejandro Jaimes
    AAAI-20 AI for Social Impact, 2020.

  • Adversarial Label Learning
    Chidubem Arachie, Bert Huang
    Association for the Advancement of Artificial Intelligence (AAAI), 2019.
    Paper, Code

  • An Adversarial Labeling Game for Learning from Weak Supervision
    Chidubem Arachie, Bert Huang
    Smooth Games Optimization and Machine Learning Workshop at NIPS, 2018.

  • Adversarial Learning for Weak Supervision
    Chidubem Arachie, Bert Huang
    Black In AI (BAI) Workshop at NIPS, 2018.

  • Integrating Machine Learning to Improve Optimal Estimation of Atmospheric Composition
    Bert Huang, Chidubem Arachie, Elena Spinei, Natalya Kramarova and Kris Wargan
    NASA Goddard Workshop on Artificial Intelligence, 2018.