Akshay Agrawal Email & Phone Number

California, United States

Building the world's best programming environment for working with data: https://github.com/marimo-team/marimo.

Stanford, Ca, Us

Advised by Stephen Boyd. I published a book that introduces a framework for vector embedding, generalizing 100 years of methods. I also helped develop two major open source projects for convex optimization and data science, CVXPY and PyMDE, with over half a million monthly downloads.

Los Gatos, Ca, Us

Optimal container packing on shared datacenters

Mountain View, California, Us

Optimization and machine learning for motion planning and control of autonomous vehicles.

Mountain View, Ca, Us

As a team member of Google Brain, I worked on TensorFlow, an open-source library for machine learning. Specifically, I worked on the core graph runtime, eager execution, and model inference on TPUs.

Stanford, Ca, Us

Under the supervision of Professor Stephen Boyd, I helped design and implement version 1.0 of CVXPY, a Python-embedded DSL for convex optimization, and accelerated the classical von Neumman alternating projections algorithm for finding a point in the intersection of convex sets, a subroutine with which cone problems can be readily solved. Applications include machine learning, radiation treatment planning, finance, control, and more.

Stanford, Ca, Us

Held a weekly tutorial section and helped draft the final exam for this graduate course in convex optimization, taught by Professor Stephen Boyd.

Stanford, Ca, Us

Mentored a dozen groups in creating applied AI and machine learning projects, edited Professor Percy Liang’s lecture notes, held office hours, and graded assignments and final papers.

Mountain View, Ca, Us

Applied techniques from data science, machine learning, and mathematical optimization to better understand Google workloads and provided actionable recommendations on how to better provision hardware for Google data centers. Pipeline deployed in production. (Python)

Stanford, Ca, Us

Held office hours and graded for CS109, Probability for Computer Scientists, a required class in probability taught by professor Mehran Sahami and Chris Piech.

Mountain View, Ca, Us

Devised a methodology to conduct fleet-wide analyses of distributed operations passing through the storage stack, and applied it to optimize Colossus, Google File System’s successor, and chunkservers. Developed reporting and analytics tools for investigations into tail latencies. Findings led to an estimated 6 percent reduction in disk read system calls across the fleet. All coding done in C++ and Python.

Stanford, Ca, Us

As an undergraduate researcher in the Stanford InfoLab, I discovered insights about and learned from large datasets. I helped compile the first large-scale, human-tagged open dataset describing affect in discussion forums in Massive Open Online Courses, and used machine learning and information retrieval techniques to prototype an intelligent intervention system that automatically detects and mitigates confusion in said forums. The work was published in the 8th International Conference on Educational Data Mining.

Stanford, Ca, Us

As part of Stanford's CS198 program, I lead and teach a weekly discussion session to a group of 8 to 12 students enrolled in Stanford's introductory computer science class. I coach these students throughout the quarter, grading their assignments and providing feedback in 1:1 sessions. Additionally, I hold office hours in which I help students debug their programs.

Stanford, Ca, Us

As a teaching assistant for an online version of Stanford's "CS144: An Introduction to Computer Networking", offered through the university's online class portal class.stanford.edu, I fielded questions from students and helped ensure that the course functioned smoothly.

Mountain View, Ca, Us

Researched and implemented policies to reduce garbage collection on flash devices. Simulations on production workloads consistently reduced overhead by 50 percent, and findings resulted in changes to the production codebase. All coding done in C++.

Mountain View, Ca, Us

As an intern on the production kernel team, I designed and developed each of the following:• Memory allocator that raises alerts when memory is misused. It recognizes and provides safeguards against buffer overflows, forbidden memory access, and improper treatment of address alignment.• Memory validation tool retrieves information about a memory mapping containing a specific address for a specific process.• Routine that ingests sequential files while guaranteeing that parsing will occur as atomically as supported by the sequential file interface.• Routine that makes weighted choices based upon a probability distribution.I also developed an automated test suite that exercises the kernel's cryptographic key retention service, reproducing, patching, and documenting kernel vulnerabilities along the way.All coding was done in C.

As staff writer (2010 – 2012), produced print and online content, including articles, pages, and multimedia. Named "Outstanding All-Around Staff Writer," and author of news article nominated for the NSPA Story of the Year. A selection of published works can be viewed here: http://www.debugmind.com/my-portfolio/journalism/As news editor (2011 – 2012), led production of both print and online news content. Assigned stories and deadlines, edited content, and managed news staffers. As webmaster (2011 – 2012), facilitated Joomla-to-Wordpress migration, redesigned and launched site, and monitored availability throughout 2011 – 2012. Site named “Best of the West” student news online publication by JEANC, Oct. 15, 2011.

As CFO of an eBay-sponsored student-run company that manufactured, marketed, and sold duct-tape wallets, responsible for proposing business models, selling stock, allocating, approving, and tracking funds, and liquidating assets.

Doctor Of Philosophy - Phd, Electrical Engineering

Master'S Degree, Computer Science

Bachelor Of Science (Bs), Computer Science (Mathematics Minor)

High School Diploma