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I've recently begun working as a Research Engineer (contract) at the Digital Safety Research Institute (DSRI), UL Research Institutes. My primary focus centers on the safety evaluation of cutting-edge AI tools that assist in code generation.

I am also collaborating with Dr. Alipour as a Volunteer Researcher (previously served as a Postdoctoral Fellow) in Computer Science at the University of Houston. We are interested in AI/ML and LLMs for code intelligence and safe coding; currently investigating the impact of backdoor attacks in code LLMs and developing methods to identify trojans and mitigate vulnerabilities through unlearning.

I completed my Ph.D. (with MS) in Computer Science from the University of Houston in May 2023. My research advisor was Dr. Alipour and I was a member of the Software Engineering Research Group (SERG). My research interest includes Software Engineering, Machine Learning, and Deep Learning for Code Intelligence and Safe Coding.  I've explored methodologies to evaluate and enhance the transparency and safety of source code models.

I obtained my B.Sc. in Computer Science and Engineering (CSE) from Khulna University of Engineering & Technology (KUET) in May 2015. Later, I joined BJIT Group, Bangladesh (Aug 2015 - Jun 2018) as a Software Engineer.

Recent Updates

• Mar 2024: Our paper "On Trojan Signatures in Large Language Models of Code" has been accepted at the SeT LLM Workshop @ ICLR 2024.

• Dec 2023: Started as a Research Engineer (contract) at the Digital Safety Research Institute (DSRI), UL Research Institutes (ULRI).

• Dec 2023: Attending NeurIPS 2023 Conference (in-person).

• Dec 2023: Check our preprint Occlusion-based Detection of Trojan-triggering Inputs in Large Language Models of Code.

• Nov 2023: TrojanedCM: A Repository of Trojaned Large Language Models of Code (arXiv, GitHub)

• Nov 2023: Attending virtual LLM Developer Day by the NVIDIA Deep Learning Institute.

• Jun 2023: A Survey of Trojans in Neural Models of Source Code: Taxonomy and Techniques (arXiv 2023)

• Jun 2023: Artifact Evaluation Program Committee at ISSTA'23.

• May 2023: Presented conference paper at InteNSE'23 (Co-located with ICSE). [Presentation Video]

• May 2023: Attending University Commencement for NSM (PhD, Computer Science). [Hooding] [Event]

• Apr 2023: Presented our poster (Inspecting Neural Models of Source Code) at PhD Research Showcase, Dept. of Computer Science, UH.

• Apr 2023: Successfully defended my PhD dissertation - Methodology for Evaluating and Interpreting Neural Code Intelligence Models.

• Mar 2023: Our paper "Study of Distractors in Neural Models of Code" has been accepted at InteNSE'23, co-located with ICSE'23.

• Dec 2022: Virtually attended ICMLA'22.

• Nov 2022: Our tool papers (ProgramTransformer and  FeatureExtractor) have been published by the journal Software Impacts 2022, Elsevier.

• Oct 2022: Attending virtual Microsoft Research Summit 2022 and NVIDIA Speech AI Summit 2022.

• Sep 2022: Our paper "Memorization and Generalization in Neural Code Intelligence Models" has been accepted by the IST Journal 2023, Elsevier.

• Sep 2022: Attending virtual Instagram Recommendation Systems At Scale Workshop 2022.

• Aug 2022: Attending virtual IBM Neuro-Symbolic AI Summer School 2022. 

• Aug 2022: Our paper "Code2Snapshot: Using Code Snapshots for Learning Representations of Source Code" has been accepted at ICMLA'22.

• Jun 2022: Presented conference paper at MAPS'22 (Co-located with PLDI). [Presentation Video]

• May 2022: Our paper "Syntax-Guided Program Reduction for Understanding Neural Code Intelligence Models" has been accepted at MAPS'22.

• April 2022: Successfully defend PhD proposal - Methodology for Evaluating and Interpreting Neural Code Intelligence Models.

• Feb 2022: Presented our research Testing and Explaining the Behavior of Code Intelligence Models at TU Delft, SERG.

• Jan 2022: Our IST paper on the generalizability of neural program models has been accepted for presentation in the Journal First Track, SANER 2022.

• Jan 2022: Awarded the badge "The Micro-credential in Data Science" by UH HPE DSI.

• Jan 2022: Received LeetCoding Challenge Annual Badge 2021.

• Dec 2021: Organized a conference (Research Quest 2021) via the Research Methods course.

• Nov 2021: Check our preprint encoding program as image.

• Oct 2021: Attending virtual Microsoft Research Summit 2021.

• Oct 2021: Attending virtual Google Systems Innovation Summit 2021.

• Sept-Nov 2021: Attending Virtual AI and Machine Learning Education Series 2021.

• Aug 2021: Presented conference paper at ESEC/FSE'21. [Presentation Video]

• Aug 2021: Student Volunteer at ESEC/FSE'21.

• Jul 2021: Attending virtual ECOOP/ISSTA Summer School 2021.

• Jul 2021: Attending virtual International Summer School on Software Engineering, ISSSE 2021.

• Jun 2021: Attending virtual FASE'21.

• Jun 2021: Check our preprint memorization and generalization in Neural Code Intelligence Models.

• May 2021: Our paper "Understanding Neural Code Intelligence Through Program Simplification" has been accepted at ESEC/FSE'21. 

• May 2021: Check our preprint understanding of CI models' prediction through prediction-preserving program simplification.

• Mar 2021: Co-Chair at ACM SAC-SVT Poster Session (P3-D).

• Mar 2021: Presented conference paper at ACM SAC-SVT'21. [Presentation Video]

• Feb 2021: Our article "On the Generalizability of Neural Program Models with respect to Semantic-Preserving Program Transformations" has been accepted at IST Journal, Elsevier 2021. 

• Dec 2020: Attending virtual Facebook Testing and Verification Symposium 2020.

• Dec 2020: Our paper "Configuring Test Generators using Bug Reports" has been accepted at ACM SAC-SVT'21.

• Nov 2020: Student Volunteer at ESEC/FSE'20.

• Nov 2020: Presented workshop paper at RL+SE&PL'20 (Co-located with ESEC/FSE). [Presentation Video]

• Oct 2020: Our paper "Towards Demystifying Dimensions of Source Code Embeddings" has been accepted at RL+SE&PL'20, co-located with ESEC/FSE'20.

• Oct 2020: Completed NLP Specialization, Coursera.

• Aug 2020: Check our preprint towards demystifying dimensions of source code embeddings.

• Jul 2020: Check our preprint on the generalizability of Neural Program Analyzers with respect to semantic-preserving transformations.

• Jun 2020: Completed Deep Learning Specialization, Coursera.

• Jun 2020: Attending virtual PLDI 2020. 

• Apr 2020: Check our preprint for evaluation of Neural Program Analyzers under Semantic-Preserving Transformations.

• Nov 2019: Presented two posters at ASE 2019 (LBR).

• Nov 2019: Visited San Diego, California to attend ASE 2019.

• Aug 2019: Our LBR paper #2 has been accepted at ASE 2019 (LBR).

• Aug 2019: Our LBR paper #1 has been accepted at ASE 2019 (LBR).

• May 2019: Visited Montreal, Canada to attend ICSE 2019.

• Aug 2018: Joined UH as a CS Ph.D. student.

• Jun 2018: Associate Member, IEB.

• Sep 2017: Our journal paper has been appeared in APIN, Springer.

• Nov 2017: Worked as ICT Trainer (part-time) with B-JET.

• May 2016: Our conference paper has been accepted at ICIEV.

• Mar 2016: Interview on the experience of ITPEC Top Gun Program 2016.

• Mar 2016: Appointed as ITPEC Ambassador, IPA, Japan.

• Feb 2016: Visited Tokyo, Japan to attend ITPEC Top Gun Program 2016.

• Feb 2016: Designated as Software Engineer, BJIT Group.

• Dec 2015: Our conference paper has been accepted at ICCIT.

• Oct 2015: High Score Passer at ITEE FE, Bangladesh.

• Aug 2015: Joined BJIT Group as Programmer.

• May 2015: Graduated with B.Sc. in CSE from KUET.