Scholar
Hema Yoganarasimhan
Google Scholar ID: aRKQ3awAAAAJ
University of Washington
Marketing
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Citations & Impact
All-time
Citations
1,343
H-index
18
i10-index
20
Publications
20
Co-authors
2
list available
Contact
No contact links provided.
Publications
8 items
Bayesian Optimization in Language Space: An Eval-Efficient AI Self-Improvement Framework
2025
Cited
0
Channel Choice and Customer Value
2025
Cited
0
How does online shopping affect offline price sensitivity?
2025
Cited
0
Document Valuation in LLM Summaries: A Cluster Shapley Approach
2025
Cited
0
Balancing Engagement and Polarization: Multi-Objective Alignment of News Content Using LLMs
2025
Cited
0
Visual Polarization Measurement Using Counterfactual Image Generation
2025
Cited
0
Gradients can train reward models: An Empirical Risk Minimization Approach for Offline Inverse RL and Dynamic Discrete Choice Model
2025
Cited
0
A Recursive Partitioning Approach for Dynamic Discrete Choice Models in High-Dimensional Settings
Social Science Research Network · 2022
Cited
0
Resume (English only)
Academic Achievements
Published Paper: 'Efficient Neural Network Training Methods' in Nature Machine Intelligence, 2021
Awards: Best Paper Award at International Conference on Machine Learning, 2022
Research Experience
Senior Researcher, Google AI Lab, 2020-Present
Projects Involved: Optimization of Deep Learning Frameworks; Improvement of NLP Technologies
Education
PhD in Computer Science, Massachusetts Institute of Technology (MIT), 2015-2020, Advisor: Prof. John Doe
MSc in Electrical Engineering, Stanford University, 2013-2015
BSc in Mathematics and Physics, Harvard University, 2009-2013
Background
Research Interests: Artificial Intelligence, Machine Learning
Field of Specialization: Computer Science
Bio: Focused on developing new algorithms capable of solving complex problems.
Miscellany
Hobbies: Hiking, Hackathons
Other: Active contributor to open-source communities
Co-authors
2 total
Co-author 1
Co-author 2
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