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Teaching


Students

    Current Ph.D. Students

  • Hoang-Chau Luong (Fall 2025-)

  • Graduated Ph.D. Students

  • Bradley Ashmore (Dissertation: Graph-Centric Bot Detection: Addressing Extreme Data Imbalances, Heterophily, and Scarcity. December 2024)
  • Daniel Grahn (Dissertation: Understanding and Enhancing the Efficiency and Efficacy of Machine Learning–Assisted Software Vulnerability Detection. Co-advise. December 2023)

  • Graduated Master Students

  • Calvin Greenewald (Thesis: Learning Under Data Scarcity: Reasoning and Negative Distillation for Texts and Graphs. April 2025)
  • Brian Davis (Thesis: Leveraging Counterfactuals for Enhanced Natural Language Inference: A Multitask Knowledge Distillation Approach. April 2025)
  • Jesse Smith (Thesis: Test-time Backdoor Attack Using Universal Perturbation. December 2024)
  • Bibek Joshi (Thesis: Enhancing Robustness of Graph Neural Network against Adversarial Attacks by Balancing Local and Global Perspectives. December 2024)
  • Jasbin Karki (Thesis: Pneumonia Detection With Limited and Imbalanced Data Using Energy-Based Out-of-Distribution Technique. December 2024)
  • Lakshmi Katyayani Devasani (Thesis: Solidity Compiler Version Identification on Smart Contract Bytecode. July 2023)
  • Aravinda Sai Gundubogula (Thesis: Enhancing Graph Convolutional Network with Label Propagation and Residual for Malware Detection. May 2023)
  • Ekula Praveen Kumar (Thesis: Few-Shot Malware Detection Using A Novel Adversarial Reprogramming Model. December 2022)