About Me

I am a fourth-year Ph.D. student in the Department of Electrical Engineering & Computer Science at the University of Arkansas, advised by Dr. Xintao Wu. Previously, I obtained my bachelor's degrees in computer science, computer engineering, and applied mathematics at the University of Arkansas, where I graduated Summa Cum Laude.

Research Interests: I am broadly interested in causality, generative modeling, and applications in trustworthy AI. My current research mainly focuses on causal representation learning, counterfactual generation, and recently mechanistic interpretability in large-scale pretrained generative models.

If you are interested in causality and generative AI or want to talk about potential collaborations, feel free to reach out to me at akomandu [at] uark [dot] edu!

News

  • Sep 20, 2024. Won 1st place in NSF DART 2024 Student Poster Competition!
  • Sep 10, 2024. Invited to serve as a reviewer for LoG 2024
  • Sep 4, 2024. Invited to serve as a reviewer for TMLR
  • Aug 22, 2024. Invited to serve as a reviewer for ICLR 2025
  • Jul 8, 2024. Invited to serve as a reviewer for DMLR
  • Jul 4, 2024. One paper has been accepted to ECAI 2024
  • May 24, 2024. Invited to serve as a reviewer for NeurIPS 2024
  • May 9, 2024. Our survey paper has been accepted to TMLR
  • Apr 29, 2024. Invited to serve as a reviewer for SPIGM@ICML 2024 Workshop
  • Apr 16, 2024. One paper has been accepted to IJCAI 2024
  • Apr 8, 2024. One paper has been accepted at GCV@CVPR 2024 Workshop
  • Oct 27, 2023. One paper has been accepted at CRL@NeurIPS 2023 Workshop
  • Oct 5, 2023. Invited to serve as a PC member and reviewer for IEEE ICMLA 2024
  • Oct 25, 2022. One paper has been accepted to IEEE Big Data 2022
  • Sep 13, 2021. One paper has been accepted to IEEE ICMLA 2021
  • Aug 20, 2021. Started Ph.D. program at the University of Arkansas