Note: No external trackers or scripts. Vinay Hiremath

About Me

I'm currently a computational neuroscience master's student. My primary research interests surround biological models of learning, including deep learning, with a focus on applications in language. Otherwise, a sampling of my interests includes linguistics, transportation infrastructure, veganism, and mindfulness.

Contact Details

Find me:
Zürich, Switzerland
Contact me:
mail <at> <domain>


ETH Zürich and University of Zürich
(Institute of Neuroinformatics)

MSc in Neural Systems and Computation Zürich, Switzerland --- Aug 2020 (est.)

Prospective research interests include biologically-inspired models of learning and computation, with a focus on natural language processing applications. Mentored by Shih-Chii Liu.

University of Michigan

BS in Computer Science, Cognitive Science, Minor in Mathematics Ann Arbor, MI --- December 2017

In the Honors program with a Computer Science GPA of 3.9/4.0. Was involved in a few research opportunities (see below).


University of Michigan

Research Assistant Ann Arbor, MI --- September 2016 - April 2017

Working with Prof. Rada Mihalcea and graduate students to develop better question-answering models using multi-modal data. We are using the MovieQA dataset, which consists of video clips and associated subtitles, scripts, etc. I am testing existing baseline models (Word2Vec, Skip-Thought) as well as discussing possible improvements with teammates.

University of Michigan

Research Assistant Ann Arbor, MI --- September 2016 - January 2017

Working with a graduate student in Prof. Honglak Lee's group on applying novel deep learning models to improve content-style disambiguation for text generation. I am helping to propose improvements on existing work (Skip-Thought, etc.), implement these improvements, and test the results on a variety of evaluation metrics.

University of Michigan

Research Assistant Ann Arbor, MI --- October 2014 - December 2014

Worked with Prof. Satinder Singh Baveja and Prof. Richard Lewis. I covered fundamental texts and papers in reinforcement learning (RL) such as the textbook by Sutton and Barto, Reinforcement Learning: An Introduction. I then implemented various RL algorithms, which were evaluated for performance using a variety of metrics for investigation by other lab members to develop more domain-agnostic RL systems.


University of Michigan

Instructional Aide (TA) Ann Arbor, MI --- Jan 2016 - Dec 2017

As a TA for EECS 445 (Intro. to Machine Learning) across three semesters, created projects and problem sets to provide students with practice on ML techniques taught in class. Held weekly discussion sections to review material and office hours for individual questions.


Engineering Intern San Francisco, CA --- May 2018 - August 2018

Worked at an early-stage startup building innovative software for privacy compliance, focusing on recent GDPR policy developments. Implemented connections with multiple data handlers (Stripe, etc.) to faciliate user data handling for clients.


Engineering Intern Palo Alto, CA --- May 2016 - August 2016

Worked with the Platforms team to modify all backend services for deployment on multiple datacenters, including handling dynamic configuration management, health checks, and Docker containerization using tools such as Consul by HashiCorp.


Backend Intern Ann Arbor, MI --- May 2015 - August 2015

Worked to implement new features for the backend written in Clojure. Gained experience in developing APIs, including interfacing with web/mobile clients and databases (PostgreSQL). Worked with ingesting large datasets including nationwide soil data, etc.