Salman Azhar

Dr. Salman Azhar specializes in buying shares of pre-IPO unicorns from early investors. He has invested in over 200 startups spanning 25 years. Twelve of these have already gone public or been acquired.

Dr. Azhar is a General Partner of Azimuth Opportunity Fund and Executive in Residence at Duke University’s Fuqua School of Business. He has previously served as the Managing Director of Duke Capital Partners. He is an advisor to several funds. His former business partners and clients include Toyota, Sony, SAP, and numerous other prominent companies.

Dr. Azhar earned his MS and PhD in Computer Science from Duke as a James B. Duke Fellow (Duke’s most prestigious graduate award) and a BS in Math and Physics from Wake Forest University as a Carswell Scholar (Wake Forest’s highest undergraduate scholarship).

Current Appointments & Affiliations

Executive in Residence of Business Administration · 2019 - Present Fuqua School of Business

In the News

Published January 12, 2018

Students Connect Engineering and Entrepreneurship in Technology & Design Pathway

Published October 20, 2015

Salman Azhar Brings Silicon Valley Mentality to Duke

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Recent Publications

Computation of equilibriain noncooperative games

Journal Article Computers and Mathematics with Applications · September 1, 2005 This paper presents algorithms for finding equilibria of mixed strategy in multistage noncooperative games of incomplete information (like probabilistic blindfold chess, where at every opportunity a player can perform different moves with some probability) ... Full text Cite

Decision algorithms for multiplayer noncooperative games of incomplete information

Journal Article Computers and Mathematics with Applications · January 1, 2002 Extending the complexity results of Reif [1,2] for two player games of incomplete information, this paper (see also [3]) presents algorithms for deciding the outcome for various classes of multiplayer games of incomplete information, i.e., deciding whether ... Full text Cite

Lower bounds for multiplayer noncooperative games of incomplete information

Journal Article Computers and Mathematics with Applications · January 1, 2001 This paper extends the alternating Turing machine (A-TM) of Chandra, Kozen and Stockmeyer, the private and the blind alternating machines of Reif to model multiplayer games of incomplete information. We use these machines to provide matching lower bounds f ... Full text Cite

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Education, Training & Certifications

Duke University · 1994 Ph.D.

External Links

Google Scholar LinkedIn Profile GP at Azimuth