cv

Click the icon to the right to download a PDF version.

General Information

Name Vivek Bharadwaj
Interests Numerical Linear Algebra, Tensor Problems, High-Performance Computing, Randomized Algorithms, Sparsity in ML
Languages C, C++, Python, Java, OCaml
Tools OpenMP, MPI, CUDA, UPC++, Pybind11, Pytorch

Education

  • 2020-2025
    PhD, Computer Science
    University of California, Berkeley
    • Advisors: James Demmel and Aydın Buluç
    • Focus: Randomized Algorithms for Tensor Problems
    • Funding: DOE CSGF (2021-2025)
  • 2016-2020
    Bachelor of Science, Computer Science & Mathematics
    California Institute of Technology
    • Cumulative GPA: 3.9/4.3

Experience

  • Summer '24
    Sparse Linear Algebra Intern
    NVIDIA Math Libraries Team
    • Focus: rewrote large parts of cuSPARSELt, a library for structured sparse-dense matrix multiplication in machine learning, for new Blackwell generation GPUs.
    • Also investigated custom semiring support with JIT linking for sparse matrix-vector multiplication.
  • Summers
    '23, '21, '20
    Graduate Student Researcher
    Lawrence Berkeley National Lab
    • Focus: randomized algorithms for sparse matrix and tensor factorization.
    • Research is a blend of theoretical and applied work, with an emphasis on high-peformance implementation.
  • Summer '22
    Visiting Student Researcher
    National Renewable Energy Laboratory
    • Focus: randomized Krylov method preconditioning.
    • Wrote CUDA kernels for randomized butterfly transformations and incomplete LDL factorization, both used as preconditioners.
  • Summer '19
    Software Engineering Intern
    Jane Street Capital
    • Wrote protocols to relay market data from exchanges to traders.
    • Made improvements to Iron, an in-house fork of the Mercurial VCS.
  • Summer '18
    Caltech SURF Intern
    Anandkumar Lab, Caltech
    • Focus: Continuous analogues of tensor decomposition and Gaussian process modeling, mentored by Rose Yu.
  • Summer '17
    Ph11 Scholar
    Shapiro Lab, Caltech
    • Focus: GPU-based MRI simulations of diffusing water molecule spins in strong magnetic fields.
    • 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

  • 2024
    • Berkeley Teaching Effectiveness Award
  • 2022
    • Berkeley Outstanding Graduate Student Instructor
  • 2021
    • DoE Computational Science Graduate Fellowship
  • 2020
    • Honorable Mention, National Science Foundation GRFP
    • Thomas A. Tisch Prize for Undergraduate Teaching
  • 2019
    • Caltech Hacktech Best Educational Hack (Presentr)
  • 2017
    • Ph11 Scholar. Funded research position awarded for solving "hurdle" problems at Caltech.
  • 2016
    • National Merit Scholar. Applied funds to study at Caltech.

Professional Service

  • Ongoing
    Peer review for the following journals / conferences:
    • 2024: Neural Information Processing Systems
    • 2024: Supercomputing 2024 Artifact Evaluation
    • 2023: Numerical Linear Algebra with Applications, Wiley
    • 2021: IEEE Signal Processing Letters
  • 2022
    • Reviewer, Berkeley SURF Research Applications
    • Graduate Visit Day Co-organizer, Scientific Computing
  • 2019-20
    Caltech Board of Control
    • Served on the student panel adjudicating cases of academic dishonesty.
  • 2019
    Student Chair, Caltech CS Student-Faculty Conference
    • Read our final report here.

Volunteering

  • Ongoing
    Judge for the following science contests:
    • 2023, 2022: Alameda County Science Fair
    • 2022: USA Young Physicists Tournament
    • 2020: Blair Middle School Science Fair
  • Oct-Dec 2021
    • CRS Science Ambassador: Gave virtual science presentations to students at Washington Elementary, Richmond
  • Jan-Mar 2021
    • Virtual Be a Scientist Mentor: Coached BUSD students through science projects weekly
  • Spring 2020
    • Caltech RISE Tutor: Tutored high school students from Pasadena Unified School district.