vita
Basics
| Name | Ishrak Hayet |
| Label | CS PhD Student @ NC State University |
| ihayet@ncsu.edu | |
| Url | https://ihayet.github.io/ |
| Summary | Third-year PhD student in Computer Science at NCSU, advised by Marcelo d'Amorim. Over 6 years of experience in software and machine learning engineering, focusing on advancing software testing methodologies and debugging tools. |
Work
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2022.08 - Present Graduate Research and Teaching Assistant
Software Testing Research Lab, NC State University
Responsible for mining and analyzing Software Engineering data from GitHub and Stack Overflow. I apply program analysis along with various Machine Learning models on the processed data to build novel techniques for ensuring software reliability. An important part of my job is to publish and present our findings to the research community to inform further innovation and development. I have worked on two NSF-funded projects which have been published in prestigious venues.
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2019.08 - 2022.05 Graduate Research and Teaching Assistant
Information Assurance Research Lab, University of Kansas
My key responsibilities were to analyze various machine learning privacy threat models and to build a custom deep neural architecture to infer private training dataset of fine-tuned language models. I have disseminated our findings through publication in top-tiered machine learning conference. Additionally, I have regularly attending the reading group of our lab where we discussed various security and privacy issues.
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2018.01 - 2019.07 Software Developer
Porate Chai EdTech
My job was to develop the front and backend of an Android app to facilitate a student-tutor matchmaking marketplace. I developed various Android activities like dashboard, job feed, profile, authentication, payment portal etc. Applied various cache optimizations to reduce app loading time in milliseconds.
Education
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2022.08 - Present Raleigh, North Carolina
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2019.08 - 2022.05 Lawrence, Kansas
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2014.01 - 2017.12 Dhaka, Bangladesh
Awards
- 2024.09.01
Travel Grant
ACM SIGSOFT
This award partially supported my travel to present our paper at ACM ISSTA 2024 in Vienna, Austria.
- 2022.03.01
Distinguished Teaching Assistant
University of Kansas (KU)
I was recognized as a distinguished Graduate Teaching Assistant for my contributions to teaching duties at KU.
- 2021.11.08
Registration Scholarship
Asian Conference on Machine Learning (ACML)
I was awarded free registration to attend the Online Asia Machine Learning School (OAMLS) conference.
- 2014.01.01
OIC Scholarship
Organization of Islamic Cooperation
This international scholarship fully covered my undergraduate tuition, lodging, and monthly stipends.
- 2009.04.01
Exchange Scholarship
ECA, US Department of State
I was awarded this scholarship to conduct high school STEM research on a Bangladeshi river and to present our findings at the YouthCaN 2009 conference in New York City.
Certificates
| Attention Models | ||
| DeepLearning.AI | 2022-11 |
| Fine-tuning BERT | ||
| DeepLearning.AI | 2022-06 |
| Vector Spaces | ||
| DeepLearning.AI | 2020-08 |
| SDE Fundamentals | ||
| Microsoft | 2014-12 |
Publications
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2025 ChatAssert: LLM-based Test Oracle Generation with External Tools Assistance
IEEE TSE
This paper proposes ChatAssert, a prompt engineering framework that can generate jUnit test oracles using large language models. ChatAssert combines a generation phase with summaries and few-shot examples, and a repair phase with static and dynamic oracle repair.
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2024 Incompleter: Feedback-directed Partial Execution
ACM ISSTA
In this paper, we propose Incompleter, a partial code execution technique that inductively mocks undefined code elements based on error feedback and eventually unmocks the mocked objects using a deductive and neural type inference. Our evaluations showed that bugs can still be found from partial code snippets if they are executed with Incompleter.
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2022 Invernet: An Inversion Attack Framework to Infer Fine-tuning Datasets through Word Embeddings
EMNLP Findings
We propose Invernet as an inversion model that can infer word-to-word co-occurrence statistics using the differential embeddings between a pretrained and a fine-tuned language model. We also showed that simple decoding approaches can be used to fairly reconstruct private training dataset using the inferred word-to-word co-occurrence statistics.
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2019 Designing a Hierarchical Keyboard Layout for Brain Computer Interface based Text Entry
IEEE International Conference on Electrical, Computer, and Communication Engineering
In this paper, we propose an accessiblity-aware text entry technique with an EEG-based input modality. Our technique combines a hierarchical motor signal classifier and a hidden markov model based text completion module that are combined in a soft keyboard layout.
Languages
| English | |
| Fluent |
| Bangla | |
| Native |
| Hindi | |
| Conversational |
Interests
| Software Reliability |
| Machine Learning |
| Large Language Models |
| Natural Language Processing |
Volunteer
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2017.06 - 2017.12 Dhaka, Bangladesh
Head of Mobile App Dev Contest
Computer Society, IUT
I was responsible for organizing and coordinating the activities for mobile app development contest at one of the largest national ICT competitions held at IUT.
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2017.01 - 2017.12 Dhaka, Bangladesh
Head of Software Systems
Mars Rover Project, IUT
I led the software team for the IUT Mars Rover project which ran successful campaigns at various international rover competitions. Our team developed the navigation, motor control, and communication software for a life-sized mars rover robot.
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2008.01 - 2010.12 Dhaka, Bangladesh
Tutor
St. Joseph Higher Secondary School
Teaching various subjects to underprivileged children after regular school hours.