Excited about the intersection of formal methods, hardware design, and programming language theory
I am a final-year Computer Science student at Cornell University, where I combine my passion for programming language theory, hardware design, and distributed systems to explore questions at the intersection of software and hardware. My academic journey has been shaped by research experiences in formal verification, machine learning theory, and fairness in computational systems. I thrive on interdisciplinary challenges, designing scalable solutions that bridge abstract principles and real-world applications.
Cornell University, Ithaca, NY
B.A. in Computer Science, Minor in Data Science and Business
Expected May 2025 | GPA: 3.856
Relevant Coursework: OOP & Data Structures, Algorithms, Database Systems, Distributed Systems, Computer Architecture, Operating Systems, Programming Languages & Logics, Compilers, Machine Learning, Computer Visions, Unix Tools, and more.
Designed a profile-guided optimization framework for Bril, dynamically extracting execution traces and injecting fast paths using speculative guards and commits for runtime performance gains. Leveraged LLVM-inspired optimization techniques to eliminate redundant operations within traces, ensuring correctness through equivalence tests and instruction count analysis.
Developed a comprehensive data flow analysis framework, implementing dominance frontier computation and SSA transformations to enable advanced compiler optimizations. Created and validated dead code elimination and local value numbering passes, ensuring correctness and reliability through the Turnt testing framework and benchmark evaluation.
Built an OCaml-based type checker and interpreter for System F, with Menhir parser generator and QCheck property-based testing. Developed an automatic verification tool for Hoare-style annotated programs, leveraging Z3 for partial correctness.
Collaborated on trading bot algorithms and integrated AWS services to scale financial data processing. Won Best Startup Idea at the 2024 Cornell FinTech Hackathon. Explore Straato
Developed a mobile app using Android NDK for micro-loan seekers, enabling 630 underwritten loans with a 94% collection rate. Integrated logistic regression and random forest models to assess loan eligibility.
Software Co-Lead | August 2022 - December 2023
Led the development of an embedded bird call match filter, implementing FFT-based signal processing pipeline and noise reduction algorithms to enable reliable species identification under environmental interference and strict power/compute constraints for Cornell's Lab of Ornithology.
Collaborated with project leads to create hands-on embedded systems curriculum for new members, developing practical exercises in C, Verilog, and Arduino. Explore C2S2
Cornell University | July 2024 - Present
Mentored by PhD student Rachit Nigam, developing formal verification frameworks using Alloy to model memory consistency models (MCMs). Focused on producer-consumer synchronization, stage transitions, and declarative specifications for buffet storage systems. Explore CAPRA
Cornell University | August 2023 - December 2023
Researched hedonic game theoretic resource allocation models for federated learning. Simulated multiplayer federated learning experiments to evaluate fairness-utility trade-offs and adversarial threat scenarios. Read More
Cornell University | August 2022 - December 2022
Investigated algorithmic fairness in job recommendation systems. Developed scalable recommendation algorithms and integrated sentiment analysis pipelines to provide real-time feedback on resumes and cover letters.