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General Information
| Name | Vivek Bharadwaj |
| Affiliation | Machine Learning Engineer, Apple |
| Research Interests | Graph Neural Networks, GPU Kernel Engineering, Randomized Algorithms, Sparsity in Machine Learning, Tensor Decomposition |
| Languages | C, C++, Python, Java, OCaml |
| Tools | MPI, CUDA, OpenMP, Pybind11, Pytorch |
Education
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2020-2025 PhD in Computer Science
University of California, Berkeley - Advisors: James Demmel and Aydın Buluç
- Funding: DOE National Computational Science Graduate Fellowship
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2016-2020 BS, Computer Science and Mathematics
California Institute of Technology (Caltech) - Cumulative GPA: 3.9/4.3
Experience
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Sep 2025-Now Machine Learning Engineer
Apple - Mapping machine learning workloads to hardware on the platform architecture team.
- Work spans performance modeling, kernel engineering, and algorithm exploration.
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Summer 2024 Sparse Linear Algebra Intern
NVIDIA Math Libraries Team - Rewrote large parts of cuSPARSELt, a library for structured sparse-dense matrix multiplication in machine learning, for new Blackwell generation GPUs.
- Investigated custom semiring support with JIT linking for sparse matrix-vector multiplication.
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Summers '23
'21, '20Graduate Student Researcher
Lawrence Berkeley National Laboratory - Focused on high-performance algorithms for randomized sparse problems.
- Research blended theoretical and applied work, from new randomized algorithms to optimized software kernels for high performance.
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Summer 2022 Visiting Graduate Student Researcher
National Renewable Energy Laboratory - Focused on Krylov subspace methods for ill-conditioned linear systems.
- Wrote CUDA kernels for randomized butterfly transformations and incomplete LDL preconditioners.
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Summer 2019 Software Engineering Intern
Jane Street Capital - Wrote protocols to relay market data from exchanges to traders.
- Improved Iron, an in-house fork of the Mercurial version control system.
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Summer 2018 Summer Undergraduate Research Fellowship (SURF) Intern
Anandkumar Lab, Caltech - Focused on tensor decompositions and Gaussian process modeling.
- Mentored by Rose Yu (now UCSD).
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Summer 2017 Summer Undergraduate Research Fellowship (SURF) Intern
Shapiro Lab, Caltech - Focused on GPU-based MRI simulations of diffusing water molecule spins.
- Work published in a journal of the German Chemical Society (code on GitHub).
Publications, Talks, and Teaching
- See links in the navigation bar.
Awards and Fellowships
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2024 - Berkeley Teaching Effectiveness Award
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2022 - Berkeley Outstanding Graduate Student Instructor
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2021 - Department of Energy Computational Science Graduate Fellowship
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2020 - Honorable Mention, National Science Foundation GRFP
- Caltech Thomas A. Tisch Prize for Undergraduate Teaching
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2019 - Best Educational Hack, Hacktech
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2017 - Ph11 Scholar
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2016 - National Merit Scholar
Professional Service
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Ongoing Peer review for the following journals / conferences:- 2026: SIAM Journal on Scientific Computing
- 2025: ACM Transactions on Mathematical Software
- 2025: ACM SPAA Junior PC
- 2025: GrAPL IPDPS Workshop
- 2024: Neural Information Processing Systems (NeurIPS)
- 2024: Supercomputing (SC) Artifact Evaluation
- 2023: Numerical Linear Algebra with Applications, Wiley
- 2021: IEEE Signal Processing Letters
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Mar 2022 - Reviewer, Berkeley SURF Research Applications
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2019-2020 Caltech Board of Control- Served on the student panel adjudicating cases of academic dishonesty.
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2018 - Student Chair, Caltech CS Student-Faculty Conference
Volunteering
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Ongoing Middle / High School Competition Judge- Alameda County Science Fair (2023, 2022)
- USA Young Physicists' Tournament (2021)
- Blair Middle School Science Fair (2020)
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Oct-Dec 2021 CRS Science Ambassador- Presented science talks virtually for students at Washington Elementary, Richmond.
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Jan-Mar 2021 Virtual Be a Scientist Mentor- Coached Berkeley students through science projects weekly.
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Jan-Apr 2020 Caltech RISE Tutor- Volunteer tutor for high school students in need of assistance from Pasadena Unified School District.