Hung Viet Pham

Hung Viet Pham

Assistant Professor at York University, interested in Software Engineering and Machine Learning

Hung Viet Pham

I am an Assistant Professor at the Department of Electrical Engineering and Computer Science at York University. My work applies software engineering testing techniques to ensure the reliability of machine learning and deep learning systems. My research interests include software testing, program repair, software engineering, and machine learning.

Publications

TOSEM-24 - Journal
History-Driven Fuzzing For Deep Learning Libraries
Nima Shiri Harzevili, Mohammad Mahdi Mohajer, Moshi Wei, Hung Viet Pham, and Song Wang

AIware-24
Effectiveness of ChatGPT for Static Analysis: How Far Are We?
Mohammad Mahdi Mohajer, Reem Aleithan, Nima Shiri harzevili, Moshi Wei, Alvine Boaye Belle, Hung Viet Pham, and Song Wang

MSR-24 - Mining Challenge
Can ChatGPT Support Developers? An Empirical Evaluation of Large Language Models for Code Generation
Kailun Jin, Chung-Yu Wang, Hung Viet Pham, Hadi Hemmati

ISSTA-23
How Effective are Neural Networks for Fixing Security Vulnerabilities?
Yi Wu, Nan Jiang, Hung Viet Pham, Thibaud Lutellier, Jordan Davis, Lin Tan, Petr Babkin, and Sameena Shah

AAAI-23
DisGUIDE: Disagreement-Guided Data-Free Model Extraction_
Jonathan Rosenthal, Eric Enouen, Hung Viet Pham, and Lin Tan

ISSTA-22
DocTer: Documentation-Guided Fuzzing for Testing Deep Learning API Functions
Danning Xie, Yitong Li, Mijung Kim, Hung Viet Pham, Lin Tan, Xiangyu Zhang, Mike Godfrey

ICSE-22
EAGLE: Creating Equivalent Graphs to Test Deep Learning Libraries
Jiannan Wang, Thibaud Lutellier, Shangshu Qian, Hung Viet Pham, and Lin Tan

NeurIPS-21
Are My Deep Learning Systems Fair? An Empirical Study of Fixed-Seed Training
Shangshu Qian, Hung Viet Pham, Thibaud Lutellier, Zeou Hu, Jungwon Kim, Lin Tan, Yaoliang Yu, Jiahao Chen, and Sameena Shah

ETR&D-21(Jornal)
Designing for robot-mediated interaction among culturally and linguistically diverse children
Yanghee Kim, Sherry Marx, Hung Viet Pham, Tung T. Nguyen

ASE-21(Tool)
DEVIATE: A Deep Learning Variance Testing Framework
Hung Viet Pham, Mijung Kim, Lin Tan, Yaoliang Yu, and Nachiappan Nagappan

ASE-20
Problems and opportunities in training deep learning software systems: an analysis of variance
Hung Viet Pham, Shangshu Qian, Jiannan Wang, Thibaud Lutellier, Jonathan Rosenthal, Lin Tan, Yaoliang Yu, Nachiappan Nagappan

ISSTA-20
CoCoNuT: combining context-aware neural translation models using ensemble for program repair
Thibaud Lutellier, Hung Viet Pham, Lawrence Pang, Yitong Li, Moshi Wei, Lin Tan

ICSE-19
CRADLE: Cross-Backend Validation to Detect and Localize Bugs in Deep Learning Libraries
Hung Viet Pham, Thibaud Lutellier, Weizhen Qi, Lin Tan

ICSE-18 (NIER)
Deep Learning UI Design Patterns of Mobile Apps
Tam The Nguyen, Phong Minh Vu, Hung Viet Pham, Tung Thanh Nguyen

ICSE-18 (Poster)
Recommending Exception Handling Patterns with ExAssist
Tam The Nguyen, Phong Minh Vu, Hung Viet Pham, Tung Thanh Nguyen

ICSE-18 (Poster)
Alpaca-advanced linguistic pattern and concept analysis framework for software engineering corpora
Phong Minh Vu, Tam The Nguyen, Hung Viet Pham, Tung Thanh Nguyen

NL4SE-18
Improving the quality of Clone Detection with Conceptual Similarity of Source code
Hung Viet Pham, Tam The Nguyen, Phong Minh Vu, Tung Thanh Nguyen

ICSE-16
Learning API usages from bytecode: a statistical approach
Tam The Nguyen, Hung Viet Pham, Phong Minh Vu, Tung Thanh Nguyen

ASE-15
Mining user opinions in mobile app reviews: A keyword-based approach
Phong Minh Vu, Tam The Nguyen, Hung Viet Pham, Tung Thanh Nguyen

ASE-15 (Demo)
Tool support for analyzing mobile app reviews
Phong Minh Vu, Hung Viet Pham, Tam The Nguyen, Tung Thanh Nguyen

ASE-15(Demo)
Recommending API usages for mobile apps with hidden markov model
Tam The Nguyen, Hung Viet Pham, Phong Minh Vu, Tung Thanh Nguyen

KSE-15
Discriminative Prediction of Enhancers with Word Combinations as Features
Hung Viet Pham , Tu Minh Phuong

Research experience

  • Research Assistant at University of Waterloo, Waterloo, Canada (2018 - 2022)
    • Develop testing techniques for deep learning libraries
  • Research Assistant at Utah State University, Logan, UT, USA (2014 - 2017)
    • Develop defect prediction techniques and source code embeddings

Teaching experience

  • Teaching Assistant, Instructional Apprentice at University of Waterloo, Waterloo, Canada (2018 - 2022)
    • CS115: Introduction to Computer Science 1 (Winter 2018, Fall 2018, Fall 2019)
    • CS135: Designing Functional Programs (Fall 2020)
    • CS245: Logic and Computation (Spring 2018)
    • CS251: Computer Organization and Design (Winter 2019, Spring 2019)
  • Teaching Assistant at Utah State Univeristy, Logan, UT, USA (2014 - 2017)

    • CS 5050: Advanced Algorithms (Fall 2016)

    • Lecturer at Postal and Telecommunication Institute of Technology, Hanoi, Vietnam (2011 - 2014)
    • Teach Introduction to AI and Image Processing courses

Industry experience

  • Research Intern at Microsoft Research, Redmond, WA, US (2021)
    • Develop techniques to improve deep learning models
  • Web app developer at Sonic Viet, Hanoi, Vietnam (2011 - 2014)
    • Lead a team of 8 developers, Architecure Design
  • Java developer at Calypso Technology, Brighton, UK (2009 - 2011)
    • Work as a Java developer in a team working on products that optimize investment portfolios using generic algorithms

Education

  • Ph.D in Software Engineering, University of Waterloo, Canada, (2018 - 2022)
  • M.S. in Evolutionary and Adaptive System (EASy), University of Sussex, UK, (2008 - 2009)
  • B.S. in Computing, Imperial College, UK, (2004 - 2007)