Welcome! I am an Assistant Professor of Computer Science at Johns Hopkins University. I am also a part of DSAI and ISI. I received my Ph.D. in Computer Science from the University of Pennsylvania, where I was advised by Prof. Mayur Naik. My primary research interests lie in programming languages and machine learning, with special interest in neurosymbolic methods. I also have work in security and software engineering.
My dissertation research is focused on neurosymbolic programming, an emerging paradigm that bridges the gap between deep learning and logical reasoning. To this end, I have developed Scallop, a general-purpose neurosymbolic programming language and compiler toolchain. Scallop has been used to develop diverse applications in the domains of natural language processing (NLP), computer vision (CV), cybersecurity, clinical-decision making, and bioinformatics. I was awarded the AWS Fellowship in 2023 for my research on trustworthy AI.
Before my PhD, I obtained a dual B.S. degree in Computer Science and Mathematics from the UCSD, where I conducted research in computer graphics with Prof. Ravi Ramamoorthi. I also spent a year working in the UCSD Design Lab on HCI with Prof. Scott Klemmer. In my spare time, I am a Piano enthusiast and the keyboardist of the band, The Protagonists, where I play Jazz, Fusion, and Pop music. My favorite programming language is Rust!
For students: I am looking for self-motivated students at both undergraduate and graduate levels to work on research in the intersection of programming languages, security, and machine learning. Please reach out to me via email if you are interested! I am also looking for Ph.D. students; prospective applicants should include their CV and a brief statement of research interests when contacting me.
Recent News
- Sep 2025 - I am teaching EN.601.727, Machine Programming, a new course on foundation, frontiers, and applications of program synthesis!
- July 2025 - I joined the Johns Hopkins University as an Assistant Professor in CS and a part of DSAI!
- June 2025 - I defended my PhD thesis!
- June 2025 - Our 🦞 Lobster paper is headed to ASPLOS 2026! Yes, another seafood-themed system! Check it out on ArXiv.
- May 2025 - I will be joining Johns Hopkins University as a Tenure-Track Assistant Professor in CS and a part of DSAI!
- Spring 2025 - I am on the academic job market for the 2024-25 cycle! Here is my CV, Teaching Statement, and Research Statement.
Teaching
- EN.601.727, Machine Programming - Johns Hopkins University, Fall 2025
Publications
Core Scallop Language and its Applications:
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ESCA: Contextualizing Embodied Agents via Scene-Graph Generation Preprint 2025
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Lobster: A GPU-Accelerated Framework for Neurosymbolic Programming ASPLOS 2026
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LASER: A Neuro-Symbolic Framework for Learning Spatial-Temporal Scene Graphs with Weak Supervision ICLR 2025
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Neurosymbolic Programming with Scallop: Principles and Practice Foundations and Trends in Programming Languages, 2024
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Data-Efficient Learning with Neural Programs NeurIPS 2024
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Relational Programming with Foundation Models AAAI 2024
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Improved Logical Reasoning of Language Models via Differentiable Symbolic Programming ACL Findings 2023
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Scallop, A Language for Neurosymbolic Programming PLDI 2023
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Scallop: From Probabilistic Deductive Databases to Scalable Differentiable Reasoning NeurIPS 2021
Security and Program Analysis:
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Locus: Agentic Predicate Synthesis for Directed Fuzzing Preprint
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Challenges and Paths Towards AI for Software Engineering Preprint
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LLM-Assisted Static Analysis for Detecting Security Vulnerabilities ICLR 2025
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Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities ICST 2025
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TYGR: Type Inference on Stripped Binaries using Graph Neural Networks USENIX Security 2024
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Arbitrar: User Guided API Misuse Detection IEEE S&P 2021
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Hoppity: Learning Graph Transformation to Detect and Fix Bugs in Programs ICLR 2020
Health and Bioinformatics:
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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications Preprint 2025
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Crowd-sourced machine learning prediction of Long COVID using data from the National COVID Cohort Collaborative eBioMedicine 2024🏆 NIH L3C Honorable Mention Award Paper
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DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation ICML 2024🏆 Spotlight ArXiv
Others:
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TurnaboutLLM: A Deductive Reasoning Benchmark from Detective Games EMNLP 2025 (Main)
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NeuroStrata: Harnessing Neurosymbolic Paradigms for Improved Design, Testability, and Verifiability of Autonomous CPS FSE 2025 IVR Track
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Towards Faithful and High-Fiedlity Synthesis of Driving Scene Videos Preprint 2024
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Numerical Reasoning over Legal Contracts via Relational Database NeurIPS 2021 Workshop on Databases and AI
Talks and Tutorials
- Dec 19, 2024 Neurosymbolic Scene Graph Generation @ TACPS Workshop, CAV'25
- Dec 19, 2024 Invited talk on Scallop and Neurosymbolic Programming @ HKUST SEPL Seminar
- Oct 11, 2024 Invited talk on Scallop and Neurosymbolic Programming @ Columbia University
- Oct 4, 2024 Invited talk on Scallop and Neurosymbolic Programming @ TACPS workshop, ESWEEK'24
- Sep 26, 2024 Invited talk on Scallop and Neurosymbolic Programming @ UT Austin
- Jun 10-11, 2024 Scallop tutorial @ Summer School of Neurosymbolic Programming (SSNP'24) Tutorial
- Apr 17, 2024 Guest lecture on Neurosymbolic Programming in CIS 7000, Spring 2024
- Dec 10, 2023 Invited talk on Scallop and Neurosymbolic Programming @ Peking University PL Seminar
- Nov 9, 2023 Invited talk on Scallop and Neurosymbolic Programming @ Purdue University
- Aug 7, 2023 Invited talk on Scallop @ KDD'23
- Jun 17-19, 2023 Tutorial and Talk on Scallop and Neurosymbolic Programming @ PLDI'23 Tutorial Slides
- Apr 10, 2023 Invited talk on Scallop and Neurosymbolic Programming @ MIT Neurosymbolic Reading Group
- Jun 1-2, 2022 Tutorial on Scallop @ Summer School of Formal Techniques (SSFT'22) Tutorial Slides