Education

• Ph.D in Computer Science, Boston University, 2017
  • Focus: Machine Learning and Deep Learning

Work experience

• 2025 - Present: Member of Technical Staff (research)
  • Anthropic
  • Area of Expertise: Code RL
• 2023 - 2025: Research Engineer, Tech Lead
  • Google DeepMind
  • Area of Expertise: Large Language Models, Generative AI, Gemini Training
• 2021 - 2023: Applied Scientist, Tech lead
  • Amazon Lab126
  • Area of Expertise: Natural Language Processing, Large Language Models, Multi-Task Learning, Transfer Learning, Few-Shot Learning, Generative AI
• 2017 - 2021: Machine Learning Engineer
  • Twitter
  • Area of Expertise: Personalization/Ranking, Natural Language Processing (NLP), Representation Learning
• 2016: Adjunct Faculty and Researcher
  • Stevens Institute of Technology
  • Teaching Data Science and Machine Learning course
  • Research on forming efficient teams
• 2015: ML Scientist
  • 128 Technology
  • Research on using machine learning for traffic modeling and traffic congestion avoidance. In addition, research on using unsupervised and supervised anomaly detection analysis using network traffic feature distributions, clustering methods, and neural networks.

Skills

• Reinforcement Learning
• LLM post-training

Publications

Teaching

Introduction to Computer Science I

Fundamentals of Computing Systems

Introduction to CS II

Introduction to Algorithms

Probability in Computing

CS 506: Data Science Tools

Speaking Engagements

• Department of Computer Science - University of Colorado Boulder, Deep Learning in Industry
• Debug Summit 2021, my work on using machine learning for Search and Recommendation
• NLP Summit 2021, my work on Alexa Conversations
• Saint Louis University, computer science department, my work on Machine Learning for Reommendations and Ranking
• Global #ArtificialIntelligence Conference, my team’s work on task-based dialog systems, YouTube
• Lyft meetup Trend/Event Detection and Recommendation @Twitter
• Writing a research paper, Boston University

Service and leadership

PC member:

• WIT: Workshop On Deriving Insights From User-Generated Text @KDD2021
• North American Chapter of the Association for Computational Linguistics NAACL 2019
• LXAI ICML 2019
• IEEE Transactions on Knowledge and Data Engineering, TKDE 2018
• WIML, NIPS 2017

Organizer and Mentor

• Mentor for IGLUcontest at NeurIPS Conference
• Organizer and Presenter, Girls Who Code, 2018, 2019
• Inclusion and Diversity committee member, Twitter, 2019-2021
• Graduate Student Representative and ambassador, Boston University, Sep 2011 – May 2017
• Organizer: ICML 2021, NAACL 2020, ICLR 2021

External Reviewer:

• KDD-2019
• ICDE-2018
• TKDE 2017
• KDD-2017
• WWW-2017
• WSDM-2017
• ICDM-2016
• CIKM-2016
• WWW- 2016
• INFORMS Journal on Computing (IJOC)-2016
• WSDM-2016