Experience

D. E. Shaw Research

• United States
• Research Services
• 100 - 200 Employee

• ML Research Engineer

  • Aug 2022 - Present



D. E. Shaw Research

• United States
• Research Services
• 100 - 200 Employee

• Machine Learning Intern

  • Jun 2021 - Aug 2021

  Working on problems involving generative models and small molecules. Working on problems involving generative models and small molecules.



D. E. Shaw Research

• United States
• Research Services
• 100 - 200 Employee

• Machine Learning Intern

  • May 2020 - Feb 2021

  Worked on problems involving protein structure prediction and deep learning. Worked on problems involving protein structure prediction and deep learning.



Harvard University

• United States
• Higher Education
• 700 & Above Employee

• Teaching Fellow

  • Jan 2020 - May 2020

  Undergraduate teaching fellow for Stat 111 (Statistical Inference) in Spring 2020 and CS 121 (Introduction to Theoretical Computer Science) in Fall 2020. Held office hours and sections for students, graded problem sets and exams. Undergraduate teaching fellow for Stat 111 (Statistical Inference) in Spring 2020 and CS 121 (Introduction to Theoretical Computer Science) in Fall 2020. Held office hours and sections for students, graded problem sets and exams.



Dana-Farber Cancer Institute

• United States
• Hospitals and Health Care
• 700 & Above Employee

• Undergraduate Cancer Biology Researcher

  • Dec 2018 - Feb 2020

  Worked on new Bayesian statistical methods for inferring branching process models of cancer growth. Implemented inference methods using Markov Chain Monte Carlo, encapsulated code in a user-friendly R package. Co-first author on paper published in Bioinformatics. Worked on new Bayesian statistical methods for inferring branching process models of cancer growth. Implemented inference methods using Markov Chain Monte Carlo, encapsulated code in a user-friendly R package. Co-first author on paper published in Bioinformatics.