Nakul Yadav, PhD

Co-Founder

United States8 yrs 7 mos experience

Key Highlights

  • Stanford and Cornell trained data scientist.
  • Expertise in ML and AI for time series analysis.
  • Contributed to high-impact neuroscience publications.
Stackforce AI infers this person is a Data Scientist specializing in Healthcare and Neuroscience with strong ML capabilities.

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Skills

Core Skills

Data ScienceMachine LearningNeuroscience

Other Skills

Decision SciencesPython (Programming Language)DjangoGPT4XGBoostClinical Trial DataPythonStreamlitSeleniumChatGPTSQLStatistical Data AnalysisData IntelligencePublic SpeakingPresentation Skills

About

Stanford and Cornell trained data scientist. Currently, I am a research scientist at Stanford working towards building tools to analyze high dimensional neural data, with extensive expertise in using ML and AI to uncover patterns in time series analysis. Previously, I was a data scientist and consulting associate at Charles Rivers Associates, providing data driven insights into strategy and business development in Life Sciences. In this time, I have contributed towards development of LLM backed RAG products for primary market research, worked with data science across clients such as Eli Lilly and Pfizer, and applied machine learning methods to provide insights into clients needs ranging from opportunity assessment using EHR data and clinical trial analysis to strategy and forecasting of newly developed drugs using Python/SQL/PowerBI. I finished my PhD in Computational and Systems Neuroscience jointly at Cornell University and The Rockefeller University where my thesis utilized advanced statistics and machine learning to understand neural architecture across brain regions, published in highest impact journals (Yadav et al., Nature 2022, Hsiao, Yadav et al., Cell 2020). I completed my Bachelors in Engineering at Indian Institute of Technology (IIT) in India prior to this. My work was recognized by various awards from graduate school, undergraduate school and neuroscience societies across the world.

Experience

8 yrs 7 mos
Total Experience
2 yrs 1 mo
Average Tenure
3 mos
Current Experience

Healthleap ai

Founding Data Scientist

Feb 2026Present · 3 mos

Ambit inc.

Data Scientist

Oct 2024Feb 2026 · 1 yr 4 mos · New York, United States

Stanford university

Research Scientist

Mar 2024Oct 2024 · 7 mos · Palo Alto, California, United States · Hybrid

Charles river associates

Data Scientist

Nov 2022Feb 2024 · 1 yr 3 mos · New York City Metropolitan Area

  • Built a retrieval augmented (RAG) pipeline for clients for primary and secondary market research documents using GPT4 deployed in Django framework (backend).
  • Built predictive classification models (XGBoost) in clinical trial data to identify 11 out of 200 features that predict patient’s success and build forecasting models to predict patients’ response using these features for trial enrollment.
  • Deployed a Streamlit (Python) based app for extracting relevant SEC filing data for rare drugs and summarization of filing reports using Selenium and ChatGPT for internal R&D initiatives.
  • Mapping patient journey for rare disease using insurance claim data (SQL Snowflake, Python) for early intervention opportunity assessment and reducing comorbidity related spending by ~$10k per patient.
Decision SciencesPython (Programming Language)Data ScienceMachine Learning

Weill cornell graduate school of medical sciences

PHD Candidate

Aug 2017Oct 2022 · 5 yrs 2 mos · New York, New York

  • Thesis : Cortical-subcortical network interactions and their role in memory processing
  • Advisors : Dr. Priya Rajasethupathy, Rockefeller University
  • Dr. Conor Liston, Weill Cornell Medical School
  • Investigating the contribution of neocortex with 2-photon recording during a virtual reality based memory retrieval paradigm, analyzing complex dataset and building theoretical models on inferred network architecture
  • Proficiency with building optical tools, large scale data analysis and physiology research
  • Publication
  • 1) Yadav et al., Feature representations in the prefrontal cortex drive memory recall. Nature 2022
  • 2) Hsiao, Yadav et al, A Thalamic Orphan Receptor Drives Variability in Short-Term Memory, Cell 2020
Statistical Data AnalysisMachine LearningNeuroscienceData Science

Education

Weill Cornell Graduate School of Medical Sciences

Doctor of Philosophy - PhD — Neuroscience

Indian Institute of Technology, Guwahati

Bachelor of Technology - BTech — Engineering Physics

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