Akshay Budhkar

Applied Research Scientist


Akshay works as an Applied Research Scientist on the Impact team where he focuses on engagements with companies mainly in the area of Natural Language Processing (NLP). Akshay uses open source datasets to improve prediction performance on NLP tasks using transfer learning.


Before joining Georgian Partners, Akshay worked in a variety of roles in software, data science and machine learning. Working as a Data Scientist at Street Contxt, Akshay used NLP to design prediction machines for augmenting the financial communication platform between buy- and sell-sides, for which he received the NSERC Experience Award for innovative research in 2016. At FarmLogs, he developed software to help farmers track the activity on their farms, irrigation, and processing climate information.


Akshay holds an MSc. in Computer Science at the University of Toronto, affiliated with the Vector Institute. As part of his Master’s, he worked on innovative products at the intersection of healthcare and machine learning such as a Google Home assistant to help people with dementia to make tea and a robotic dialogue agent that helps to detect cognitive diseases in children. Akshay graduated from the University of Waterloo with a Bachelor’s in Computer Engineering.

Did you know?

Akshay loves travel landscape photography and hiking. He is an avid Friends fan and won a city-wide Friends trivia competition. Akshay also plays chess and is an ardent cricket fan.

Contact Akshay

(416) 868-9696

Areas of Expertise

Natural Language Processing

Machine Learning

Computational Linguistics

Ethics in AI

Explainable AI


Top Hat

Top Hat is a mobile and web-based classroom response system that engages students and provides professors with real-time feedback on student understanding. Founded in 2009, Top Hat has been ranked as a top 10 app in the education category in Apple’s App Store. Using a BYOD approach, educators use Top Hat to conduct polls, quizzes, assign homework or run interactive tournaments.

Team: Justin LaFayette, Madalin Mihailescu, Margaret Wu