Dr. Jason Altschuler

Assistant Professor

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Biography

Jason Altschuler is an Assistant Professor in the Department of Statistics and Data Science at the University of Pennsylvania, holding additional appointments in Computer Information Science and Electrical Systems Engineering. He earned his Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 2022, where he also obtained his M.S. in the same field in 2018 and a B.S. in Computer Science from Princeton University in 2016. His research interests encompass optimization, probability, machine learning, and data science, with a strong focus on optimal transport. Altschuler has contributed to various academic seminars and courses, guiding students in the latest developments in applied statistics, data science, and artificial intelligence. He is recognized for his research contributions, receiving several honors including the Sloan Research Fellowship in Mathematics and the ICS Paper Prize in 2025. Altschuler previously served as a Faculty Fellow at New York University during the 2022-2023 academic year and is actively involved in advancing research in computational methods and statistical theory.

Research Interests

Awards

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Sloan Research Fellowship

2025-01-01
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ICS Paper Prize

2025-01-01
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A.W. Tucker Finalist Prize

2024-01-01
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George M. Sprowls Award

2022-01-01
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Sigma PhD Fellowship

2020-01-01
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NSF Graduate Fellowship

2016-01-01
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James Hayes-Edgar Palmer Prize

2016-01-01
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Accenture Prize

2015-01-01

Requirements for University of Pennsylvania

Doctorate Program
Requirements
GPA Requirement
Required:3.6
GRE General
Verbal
Required:162
Quantitative
Required:162
Overall
Required:162
GMAT
Total Score
Required:728
Overall
Required:728
TOEFL
Total
Required:115
Prerequisites
Bachelor's degree or equivalent Strong quantitative background
Application Checklist
  • Academic Transcripts
  • Letters of Recommendation (2-3)
  • Resume/CV
  • Statement of Purpose
  • Essays
Specialization Notes

Wharton Doctoral programs cover fields like Finance, Marketing, Management, and Operations, Information and Decisions.