Jacob Danovitch

Education

Carleton University

Ottawa, Canada

B.S. in Computer Science (Honors) | Minor in Psychology | Cum. GPA: 4
  • Accepted to OCICS 5-year masters track (concentration in data science).
  • Coursework in deep learning, information retrieval, knowledge graphs.
  • Dean's List: 2017 - Present.

Experience

Microsoft Search, Assistance, and Intelligence

Seattle, USA

Data Scientist Intern
  • Received return offer for data scientist internship beginning May 2020.
  • Contributing to deep learning projects in MSAI.

Carleton University

Ottawa, Canada

Teaching Assistant
  • Fall '19: Storytelling with Data. Assisting journalism students in-class with data science tools.
  • F/W '18-19: Discrete Structures I, Introduction to Computer Science I.

Microsoft Cortana

Seattle, USA

Software Engineering Intern
  • Implemented dashboard and backend Azure-SQL library for feedback collection application.
  • Patent pending for contributions to project extracting insights from Outlook emails using deep learning.

Medimo Labs

Toronto, Canada

Software Development Intern
  • Contributed to medical data visualization application.
  • Implemented client-facing dashboard and search functionality with React.js.

Publications

Danovitch, J. (2019). Trouble with the Curve: Predicting Future MLB Players Using Scouting Reports. Poster session to be presented at the 2019 Carnegie Mellon Sports Analytics Conference, Pittsburgh, PA.

Danovitch, J., & SalahEldeen, H. (2019). ReMemBERT: Recurrent Memory-Augmented BERT for Conversational Text Classification. Technical report in preparation.

Lynch, B., Danovitch, J., & Davies, J. (2018). Towards a Computational Approach to Conceptual Metaphor. Unpublished conference paper accepted as abstract to CogSci 2019, Montreal, CA.

Research

Disinformation in Canadian Political Discourse

Carleton Data Science Institute

Under Prof. Majid Komeili & Prof. Michael Christensen
  • Constructing novel dataset of malicious tweets surrounding newsworthy Canadian events.
  • Senior thesis: Analyzing stylistic variations of malicious tweets using deep learning.

Neural Relevance Matching for News Discussions on Social Media

Carleton Data Science Institute

Prof. Majid Komeili
  • Constructing large-scale dataset of article/comments pairs from Reddit posts.
  • Using deep learning to match social media comments to relevant news articles.