Tejas Ramdas

Cornell University

Tejas Ramdas

Strategy · Organization theory · Statistics

Portrait of Tejas Ramdas
Cornell University
S.C. Johnson College of Business
Statistics and Data Science
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Ph.D. in Management, Cornell University, August 2026
Ph.D. candidate in Statistics, expected December 2026

I study how firms compete through innovation search, and how technological breakthroughs change the possibilities for invention.

My research examines how firms move into new areas of invention and shape the opportunities available to other firms. I also study coordination and common knowledge in collectives of AI agents.

My statistics research develops methods in explainable AI, causal machine learning, and natural language processing, with applications in finance and law.

Job market paperCV (PDF)

Selected research

All research

Management research

Strategy, innovation search, organizations, and AI coordination.

Job market paper

Generative Inventions and Search Incursions

Tejas Ramdas and Gautam Ahuja

Search incursion in inventive space. The maps illustrate patent-text comparisons; classification comes from blinded text review.
Search incursion in inventive space. The maps illustrate patent-text comparisons; classification comes from blinded text review.
Observed search-incursion rates across technological-distance bins. The fitted curve is descriptive; intervals are unadjusted.
Observed search-incursion rates across technological-distance bins. The fitted curve is descriptive; intervals are unadjusted.

How do firms use technological breakthroughs to move beyond their own inventive experience and toward areas of strength for other firms?

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Working paper

Shaping the Search Landscape

Tejas Ramdas

Prior knowledge relationships and the timing of follow-on search. The central artifact illustration is conceptual.
Prior knowledge relationships and the timing of follow-on search. The central artifact illustration is conceptual.

How does the first firm to build on a breakthrough shape the inventive paths and opportunities available to firms that follow?

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All management research

Statistics research

Statistical methods, explainable AI, finance, and constitutional text.

Working paper

Bellwether Trades

Tejas Ramdas and Martin T. Wells

From trade sequences to forecasts and trade-level influence. Conceptual schematic.
From trade sequences to forecasts and trade-level influence. Conceptual schematic.

Explainable AI identifies which trades influence a model's price forecast and how that influence depends on trading context.

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All statistics research

Education & experience

Full CV

Education

  1. Ph.D. in Statistics

    Cornell University
    Advisor: Martin T. Wells

  2. Ph.D. in Management

    Cornell University, S.C. Johnson College of Business
    Advisor: Gautam Ahuja

  3. M.S. in Applied Mathematics

    University of Colorado Denver

  4. M.A. in Economics

    University of Colorado Denver

  5. B.E. in Mechanical Engineering

    Visvesvaraya Technological University
    With Distinction

Professional experience

  1. Morgan Stanley

    Summer Associate, Wealth Management Analytics, Data and Innovation

  2. Research Associate, HBS

    Strategy Unit

  3. Accenture

    Associate Software Engineer, following B.E.

  4. National Aerospace Laboratories

    Undergraduate Researcher, Experimental Aerodynamics Division

Teaching

Theory, evidence, and independent judgment.

Teaching assistant experience across 15 MBA, graduate, and undergraduate courses.

  • Strategy Formulation and Competitive Analysis
  • The Strategic Management of Technology and Innovation
  • Learning, Inference and Decision Making with Data
Teaching approach and experience

Contact

Get in touch

tr336@cornell.edu
320 Tata Innovation Center, Cornell Tech
11 East Loop Road
New York, NY 10044