David A. R. Robin

David A. R. Robin's picture

M. Sc. student at ENS

Computer Science


Experience

  1. Research Internship : Neural network compression

    Technicolor AI Lab (acquired by Interdigital), San Francisco (CA)

    Feb - Aug 2019


    Research Internship with Swayambhoo Jain on neural network compression.

    Preprints :

    • Linear activation reconstruction (in progress, to be disclosed)
    • Targeted teaching (in progress, to be disclosed)
    • Inverse magic function (in progress, to be disclosed)

    Internship report :  [ html ][ pdf ][ slides ]

  2. Research Internship : Optimal Transport

    Massachussets Institute of Technology, Boston (MA)

    Jun - Aug 2018


    Research Internship with Philippe Rigollet (MIT) on reconstruction of cellular trajectories in gene expression space with optimal transport. The resulting toolkit for single cell RNA sequencing timeseries analysis is open source and available as a Python package.

    Waddington Optimal Transport : broadinstitute/wot (diverged since)

    Internship report (in french) :  [ html ][ pdf ][ slides ]

Teaching

  1. Guest Lecture : Neural network compression

    Deep Learning course by Marc Lelarge (INRIA - ENS), ENS Paris


    Introduction to neural network compression concepts and recent results, with a focus and practical session on activation reconstruction.

    Resources :  [ Lecture slides ][ Practical Session ][ Practical Session Solution ]

Education

  1. M. Sc. Computer Science

    Mathématiques, Vision & Apprentissage (MVA)

    École Normale Supérieure, Paris, 2018-2020


    Advanced mathematics and computer science, focused on Machine Learning

    Coursework includes:

    • Category theory
    • Network modelisation
    • Parallel programming
    • General Robotics
    • Convex optimization
    • Computer vision
    • Deep Learning
    • General Topology
    • Differential Geometry
    • Reinforcement Learning
    • Natural Language Processing
    • Optimal Transport
    • Graphical Models
    • Kernel Methods
  2. B. Sc. Computer Science

    École Normale Supérieure, Paris, 2017-2018


    Solid basis in modern mathematics and computer science.

    Coursework includes:

    • Mathematical Logic
    • Formal languages
    • Algebra
    • Cryptology
    • Information theory
    • λ-calculus and calculability
    • Processor's architectures
    • Operating Systems
    • Databases
    • Compilation
    • Randomized algorithms
    • Semantics and Verification
  3. CPGE MPSI-MP*

    Lycée Louis-le-Grand, Paris, 2015-2017


    Post-secondary program in advanced maths and physics leading to nationwide entrance examinations to the Grandes Écoles for scientific studies

  4. Baccalaureate in science

    Lycée Hoche, Versailles, 2015


    A-levels French equivalent

    Awarded with highest honours

Skills

Languages

I.T.

Projects

  1. Raspberry Pi 3 64-bit OS


    UNIX-like 64-bit micro-kernel with MMU handling, dynamic memory allocation, hardware interruptions, multi-processing, and basic filesystem for the Raspberry Pi 3 (before even Linux implements 64-bit support)

    Source code available on github: robindar/sysres-os

  2. SMT Solver


    Small SMT solver for equality theory decision procedures.

    Implements DPLL, two-watched literals, and is fully unit-tested.

    Source code available on github: robindar/semver-smt

  3. Rust compiler


    Compiler for a small (yet Turing-complete) subset of Rust.

    Borrow-checked and compiled down to x86 assembly.

    Source code available on github: robindar/compil-petitrust

  4. RISC V processor emulator


    "RISC V"-style basic processor emulator in Minijazz (Netlist superset) and Minijazz-to-C compiler. Supports few instructions but has a good build system and is unit-tested

    Source code available on gitlab: alpr-sysdig/processor

  5. Genetic algorithms for the Traveling Salesman Problem

    School project (TIPE)


    Genetic algorithm to find good solutions to the Traveling Salesman Problem and a testing structure around it to optimize meta-parameters like population size, mutation probability or crossover method

  6. Online portfolio

    https://www.robindar.com


    Headless Debian to practice web design and server administration

    Also acts as a personal Git server and occasional blog


Let's work together

If you have a project that you want to get started, think you need my help with something, or just fancy saying hi, send me a message, I'm always happy to help !

Message Me