Harvineet Singh

AI Researcher

San Francisco, California, United States10 yrs 10 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Ph.D. in Data Science with a focus on responsible machine learning.
Developed frameworks for monitoring AI model performance in healthcare.
Recognized as a Future Leader in Responsible Data Science.

Stackforce AI infers this person is a Data Science expert with a focus on Healthcare AI solutions.

Contact

Skills

Core Skills

Machine LearningData ScienceHealthcare

Other Skills

Generative AIBenchmarkingApplied ResearchData AnalysisElectronic Health Records (EHR)Natural Language Processing (NLP)Statistical InferenceMachine Learning AlgorithmsStatisticsPropensity ModellingArtificial Intelligence (AI)Python (Programming Language)Causal InferenceMLOpsComputer Vision

About

I am an experienced data scientist with a Ph.D. in Data Science from NYU and a strong foundation in responsible machine learning, causal inference, and robust AI systems. Presently, my work at UCSF involves developing frameworks to monitor models in deployment for performance shifts and diagnose root causes of model failures in real-world applications. In addition to my academic contributions, my industry experience includes designing and deploying predictive models at Adobe Research, benchmarking fairness methods at Amazon Science, and optimizing ad ranking pipelines at Microsoft Research. My work has led to impactful publications, patents, and leadership roles such as General Chair for the Machine Learning for Health Symposium. I was recognized as a Future Leader in Responsible Data Science by the University of Michigan in 2022 and was a research fellow at the Center for Research on Computation and Society at Harvard University.

Experience

10 yrs 10 mos

Total Experience

2 yrs 7 mos

Average Tenure

1 yr

Current Experience

Qualified health

Machine Learning Scientist

Jun 2025 – Present · 1 yr · Palo Alto, California, United States · On-site

Generative AIBenchmarkingApplied ResearchData AnalysisMachine LearningData Science

University of california, san francisco

Postdoctoral Scholar

Jul 2023 – Jun 2025 · 1 yr 11 mos · San Francisco, California, United States

Develop frameworks to evaluate machine learning models across clinical applications, with a focus on improving their reliability and fairness.

Applied ResearchElectronic Health Records (EHR)Natural Language Processing (NLP)Statistical InferenceMachine Learning AlgorithmsStatistics+7

Amazon web services (aws)

Research Intern

Jun 2022 – Oct 2022 · 4 mos · Tübingen, Baden-Württemberg, Germany

Benchmarked fairness methods in a large-scale study across tabular datasets and model classes. Explored reasons for the success of tree-based learners for achieving minmax-fairness in practice.

Applied ResearchResearch SkillsLarge Language Models (LLM)Supervised LearningUnixMachine Learning Algorithms+15

Microsoft

Research Intern

Jun 2021 – Aug 2021 · 2 mos

Investigated methods to improve ad serving pipelines built using contextual bandit models. Developed a causal feature importance metric to improve robustness of models.

Applied ResearchResearch SkillsSupervised LearningMachine Learning AlgorithmsBenchmarkingOptimization+12

Harvard university

Summer Research Fellow

Jun 2020 – Aug 2020 · 2 mos

As a summer research fellow at the Center for Research on Computation & Society at Harvard University, developed methods to evaluate reinforcement learning policies in dynamic environments. Developed a robust optimization-based method applicable to bandits and MDPs achieving informative evaluations.

Applied ResearchResearch SkillsMachine Learning AlgorithmsBenchmarkingOptimizationAnalytical Skills+10

New york university

Graduate Student Researcher

Sep 2018 – Oct 2023 · 5 yrs 1 mo · Greater New York City Area

As a PhD student at NYU's Center for Data Science, worked on responsible ML projects to design and evaluate machine learning systems and data collection strategies for health applications. Studied fairness and robustness of models in dynamically-changing settings.

Applied ResearchElectronic Health Records (EHR)Computer VisionNatural Language Processing (NLP)Statistical InferenceStatistical Data Analysis+14

Adobe

3 roles

Member of Technical Staff

Jul 2015 – Aug 2018 · 3 yrs 1 mo · Bengaluru Area, India

Devised machine learning models for user behavior prediction and recommender system tasks. Developed prototypes and worked with product engineering teams to transfer technologies to Adobe’s
digital marketing solutions.

Applied ResearchSupervised LearningStatistical InferenceDeep Neural Networks (DNN)Machine Learning AlgorithmsUnsupervised Learning+16

Research Intern, Adobe Research India Lab

May 2014 – Jul 2014 · 2 mos · Bengaluru Area, India

Proposed model for predicting users' purchase propensity on e-commerce sites from clickstream data.
Worked on data from email-based subscription services gathering insights for designing effective email campaigns for recovery of abandoned shopping carts on e-commerce sites

Applied ResearchResearch SkillsSupervised LearningUnixMachine Learning AlgorithmsBenchmarking+17

Research Intern, ATL

May 2013 – Jul 2013 · 2 mos · Noida Area, India

Worked as a summer intern on a project related to providing social media targeting insights to brands for better user engagement using text mining and information extraction techniques on user-generated content

Supervised LearningMachine Learning AlgorithmsModel TrainingProblem SolvingMachine Learning