I'm a Deep Learning Engineer at NVIDIA, working on Riva Speech Skills, as well as other Speech, NLP and Deep Learning related projects. I graduated from University of California, Berkeley with a Bachelors of Science in Electrical Engineering & Computer Science, focused on Machine Learning. In the past I worked at Google, Berkeley AI Research, and Brilliant Inc. In my free time, I produce music, sketch, and game.
Due to privacy concerns, please contact me on LinkedIn for additional contact information.
Non-Degree• Sep '21 - Present
B.S. Electrical Engineering and Computer Science • Aug '16 - May '20
Research Engineer• April '22 – Present
Deep Learning Engineer• July '20 – Feb '22
Researcher & Grader • Jan '19 - Jan '20
Software Engineer Intern • May '18- Aug '18
President & Project Lead • May '17- Dec'19
Course Author• May '17- Aug'18
Ashwin Balakrishna*, Brijen Thananjeyan*, Jonathan Lee, Arsh Zahed, Felix Li, Joseph E. Gonzalez, Ken GoldbergConference on Robot Learning (CoRL), 2019. Oral Presentation. PDF
Ashwin Balakrishna*, Brijen Thananjeyan*, Jonathan Lee, Arsh Zahed, Felix Li, Joseph E. Gonzalez, Ken GoldbergReal World Sequential Decision Making Workshop at the International Conference on Machine Learning (ICML), 2019. PDF
My work cetralizes around a combination of Deep Learning, Speech Processing, and Reinforcement Learning. In the past, I've worked on proejcts involving Computational Music, NLP, Text-To-Speech, Model Based Reinforcement Learning, and Dynamics Estimation. I'm fluent in TensorFlow, PyTorch, and various other ML frameworks.
Used uncertainty estimation to create an active learning framework for physics estimation. Achieved a >50% decrease in required data. Paper and code pending publication.
Inferred style-embeddings from text to improve generated speech. Second network trained from text, pitch, and rhythm embeddings. Improved F0 Frame Error by 8% with audible improvement.
Invented a generalized class of metrics over the space of policies for a given Markov Decision Process. Trained a Siammesse Network to compare tasks, with distance related to the distance between optimal policies of the two tasks. Can be used for improved exploration of policy initialization in a meta-learning setting.
Simultaneously and independently optimize all solutions on the Pareto front. Implement and improve the existing MO-CMA-ES algorithm to operate a Baxter robot quickly and adaptively in production for a multi-objective problem such as collision avoidance.
Designed and implemented original Phase-Functioned LSTMs with autoencoders in Python/TensorFlow to generate music wth repeated patterns using the Magenta framework.
Chrome Extension chat bot to help browse the web using voice commands.
I like to put my digital signal processing skills to a more creative use with electronic music production. I mostly produce for myself, so I haven't published much of my works yet, but here's an inside look at some of the projects I'm proud of or working on.
If you find something I've worked on interesting, feel free to get in touch. Please contact me through LinkedIn if you do not already have my contact info. I look forward to working with you!