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Abhinav Jangda

Observed names: Jangda Abhinav, Jangda, Abhinav
ORCID: 0000-0002-4849-6776
Observed ORCID: 0000-0002-4849-6776
OpenAlex ID: A5034240415
MultiPL-E: A Scalable and Polyglot Approach to Benchmarking Neural Code Generation
2023 · Federico Cassano, John Gouwar, et al. · IEEE Transactions on Software Engineering · 116
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Formal foundations of serverless computing
2019 · Abhinav Jangda, Donald Pinckney, et al. · Proceedings of the ACM on Programming Languages · 102
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Not So Fast: Analyzing the Performance of WebAssembly vs. Native Code
2019 · Jangda, Abhinav, Powers, Bobby, et al. · arXiv (Cornell University) · 90
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Accelerating graph sampling for graph machine learning using GPUs
2021 · Abhinav Jangda, Sandeep Polisetty, et al. · European Conference on Computer Systems · 80
Breaking the computation and communication abstraction barrier in distributed machine learning workloads
2022 · Abhinav Jangda, Jun Huang, et al. · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · 69
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Knowledge Transfer from High-Resource to Low-Resource Programming Languages for Code LLMs
2024 · Federico Cassano, John Gouwar, et al. · Proceedings of the ACM on Programming Languages · 39
Swizzle Inventor
2019 · Phitchaya Mangpo Phothilimthana, Archibald Samuel Elliott, et al. · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · 35
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An effective fusion and tile size model for optimizing image processing pipelines
2018 · Abhinav Jangda, Uday Bondhugula · ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming · 29
MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation
2022 · Cassano, Federico, Gouwar, John, et al. · arXiv (Cornell University) · 17
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Unbounded superoptimization
2017 · Abhinav Jangda, Greta Yorsh · ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software (Onward!) · 14
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An effective fusion and tile size model for optimizing image processing pipelines
2018 · Abhinav Jangda, Uday Bondhugula · ACM SIGPLAN Notices · 13
Adaptive Just-In-Time Code Diversification
2015 · Abhinav Jangda, Mohit Mishra, et al. · ACM Workshop on Moving Target Defense (MTD) · 11
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A Framework for Fine-Grained Synchronization of Dependent GPU Kernels
2024 · Abhinav Jangda, Saeed Maleki, et al. · Proceedings of the CGO/Proceedings of the ... CGO · 8
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Model-Based Warp Overlapped Tiling for Image Processing Programs on GPUs
2020 · Abhinav Jangda, Arjun Guha · International Conference on Parallel Architectures and Compilation Techniques (PACT) · 7
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Mind the Gap: Analyzing the Performance of WebAssembly vs. Native Code.
2019 · Abhinav Jangda, Bobby Powers, et al. · arXiv (Cornell University) · 6
MSCCL++: Rethinking GPU Communication Abstractions for AI Inference
2026 · Changho Hwang, Peng Cheng, et al. · International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) · 5
NextDoor: GPU-Based Graph Sampling for Graph Machine Learning.
2020 · Abhinav Jangda, Sandeep Polisetty, et al. · arXiv (Cornell University) · 3
Fast Kronecker Matrix-Matrix Multiplication on GPUs
2024 · Abhinav Jangda, Mohit Yadav · ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming · 2
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An Effective Fusion and Tile Size Model for PolyMage
2020 · Abhinav Jangda, Uday Bondhugula · ACM Transactions on Programming Languages and Systems · 2
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Predicting Variable Types in Dynamically Typed Programming Languages
2019 · Jangda, Abhinav, Anand, Gaurav · arXiv (Cornell University) · 2
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RandHeap: Heap Randomization for Mitigating Heap Spray Attacks in Virtual Machines
2017 · Abhinav Jangda, Mohit Mishra · Conference on Privacy, Security and Trust · 2
Compiling Strassen-like Matrix Multiplication Algorithms to Fast GPU Kernels
2026 · Jangda, Abhinav · Zenodo (CERN European Organization for Nuclear Research) · 1
PEAK: A Performance Engineering AI-Assistant for GPU Kernels Powered by Natural Language Transformations
2025 · Tariq, Muhammad Usman, Jangda, Abhinav, et al. · arXiv (Cornell University) · 1
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How Many Parameters Does Your Task Really Need? Task Specific Pruning with LLM-Sieve
2025 · Reda, Waleed, Jangda, Abhinav, et al. · arXiv (Cornell University) · 1
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RESOLVE: Language-Agnostic Validation of GPU Kernels Through Testing, Reduction, and Proof
2026 · Gargary, Ashkan Vedadi, Martínez, Guido, et al. · arXiv (Cornell University)
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Works count: 41
Citation count: 657
H-index: 11
I10-index: 12
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