Sep 2022 – Mar 2023 · 6 mos · San Francisco Bay Area · Hybrid

• I led the design and implementation of Omnimizer, our scalable platform for efficient ML training and deployment, while exploring state-of-the-art model optimization research for future product iterations.

Oct 2021 – Sep 2022 · 11 mos · San Francisco Bay Area · Hybrid

• We built a scalable, accessible machine learning platform by redefining how we create and deploy deep neural networks in production. Our product is based on years of research into optimizing models for efficient deployment across a wide range of systems.

Jul 2021 – Oct 2021 · 3 mos · Somerville, Massachusetts, United States · Hybrid

• I collaborated with the research team to optimize deep learning models through neural network pruning and architecture search.

Jul 2020 – May 2021 · 10 mos · Vienna, Austria

• I collaborate with multiple researchers at TU Vienna (CPS Group) on efficient and interpretable machine learning.

Jun 2019 – Sep 2019 · 3 mos · San Francisco Bay Area · On-site

• During my time at Tesla, I lead the design and development of a lateral motion planner to improve autonomous highway driving in Tesla production cars. The software was incorporated into Tesla FSD at that time.

Jan 2019 – May 2019 · 4 mos · Greater Boston

• As a TA for 6.856 Randomized Algorithm, taught by Prof. David Karger, I led weekly office hours, oversaw grading, created new homework problems, and implemented a streamlined online submission portal.

Sep 2016 – Aug 2021 · 4 yrs 11 mos · Greater Boston

• My research focused on optimizing deep neural networks for resource-constrained applications, such as robotics and cloud computing. I developed novel techniques in model compression and pruning that improve the speed-accuracy trade-off and provide theoretical insights into network design and training.
• Before that, I worked on verification algorithms for safe autonomous driving and contributed to our AV research platforms (self-driving cars and wheelchairs) for testing and validation.

Jan 2017 – Feb 2017 · 1 mo · Singapore

• Research exchange with the Mobility Group at SMART, National University of Singapore.

Dec 2015 – Feb 2016 · 2 mos · Singapore

• I designed, developed, and implemented an automated velocity controller using a novel combination of traditional control techniques and machine learning.

Jun 2015 – Nov 2015 · 5 mos

• As a TA for Prof. George Haller, I restructured and extended the course content for the "Dynamics" lecture, which is a mandatory class for second-year Mechanical Engineering students. This included writing the accompanying course text and publishing its initial version.

Sep 2014 – Oct 2015 · 1 yr 1 mo

• Under the supervision of Prof. Raffaello D'Andrea, I co-led the implementation of a real-time operating system for the novel Distributed Flight Array (DFA), developed autonomous sensing and decision-making capabilities, and conducted research on self-assembly algorithms.

Aug 2014 – Dec 2014 · 4 mos

• As a TA for Prof. George Haller's "Dynamics" course, I co-led weekly recitations and exercises for 80-100 second-year Mechanical Engineering students.

Feb 2014 – Jul 2014 · 5 mos

• I led weekly recitation and exercise sessions for 20-30 students in "Computer Science I" (taught by Prof. Markus Gross). This is a first-year course in Mechanical Engineering covering C/C++ and basic algorithms.

Jan 2013 – Feb 2013 · 1 mo · Vienna, Austria

• I contributed to developing a novel magnetic gearbox, manufacturing prototypes, and assembling a testing facility while receiving training in operating industrial machines.