Aakash Bansal

I am a PhD student at the University of Notre dame advised by Prof. Collin McMillan in the software engineering lab. Before pursuing my PhD, I earned my Masters in Computer Vision and Machine Learning at the University of Surrey with distinction. I work on developing intelligent techniques for software engineering.

My current research is at the cross-section of NLP, AI, and Software Engineering. At a high-level, my graduate work and thesis has been aimed at designing custom and purpose-built neural networks for source code summarization, particularly for adding contextual information. Source code summarization is a well-defined task of taking source code and generating natural language descriptions, with applications in code documentation, education, and software maintainance to name a few.

I will be on the Academic job market for Fall 2024 start. I am interested in mainatining a quality-first research program with graduate students and contribute to the edification on undergraduate students I am looking for tenure-track faculty positions in computer science and engineering. I expect to defend my thesis in April 2024.

news

Aug 28, 2023	I am serving on the PC for the Gaze meets ML workshop 2023 at NeurIPS, please consider sumitting your work!
Jul 15, 2023	Our Tool Demo paper titled A Language Model of Java Methods with Train/Test Deduplication, accepted at ESEC/FSE2023
Jul 7, 2023	Our New Ideas and Emerging Research (NIER) paper on automated prediction of where programmers look, accepted at ASE2023

selected publications

2023

Modeling Programmer Attention as Scanpath Prediction

Aakash Bansal, Chia-Yi Su, Zachary Karas, Yifan Zhang, Yu Huang, Toby Jia-Jun Li, and Collin McMillan

In Proceedings of The 38th IEEE/ACM International Conference on Automated Software Engineering - New Ideas and Emerging Research Track, 2023

Bib Code

@inproceedings{bansal2023scanpath,
  author = {Bansal, Aakash and Su, Chia-Yi and Karas, Zachary and Zhang, Yifan and Huang, Yu and Li, Toby Jia-Jun and McMillan, Collin},
  title = {Modeling Programmer Attention as Scanpath Prediction},
  booktitle = {Proceedings of The 38th IEEE/ACM International Conference on Automated Software Engineering - New Ideas and Emerging Research Track},
  year = {2023},
}

Towards modeling human attention from eye movements for neutral source code summarization

Aakash Bansal, Bonita Sharif, and Collin McMillan

Proceedings of ACM Human-Computer Interaction, Vol. 7, 2023

Bib Code
@article{bansal2023human, author = {Bansal, Aakash and Sharif, Bonita and McMillan, Collin}, journal = {Proceedings of ACM Human-Computer Interaction, Vol. 7}, year = {2023}, }

Function Call Graph Context Encoding for Neural Source Code Summarization

Aakash Bansal, Zachary Eberhart, Zachary Karas, Yu Huang, and Collin McMillan

IEEE Transactions on Software Engineering, 2023

Bib Code

@article{bansal2023callcon,
  author = {Bansal, Aakash and Eberhart, Zachary and Karas, Zachary and Huang, Yu and McMillan, Collin},
  journal = {IEEE Transactions on Software Engineering},
  title = {Function Call Graph Context Encoding for Neural Source Code Summarization},
  year = {2023},
  doi = {10.1109/TSE.2023.3279774},
}

2021

Project-level encoding for neural source code summarization of subroutines

Aakash Bansal, Sakib Haque, and Collin McMillan

In 2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC), 2021

Bib Code

@inproceedings{bansal2021project,
  author = {Bansal, Aakash and Haque, Sakib and McMillan, Collin},
  booktitle = {2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)},
  pages = {253--264},
  year = {2021},
  organization = {IEEE},
}