Hardik Bansal

CTO

New York, New York, United States2 yrs 10 mos experience
AI EnabledAI ML Practitioner

Key Highlights

  • Expert in Quantum Computing and Information.
  • Proven leadership as CTO and Co-Founder.
  • Strong background in Algorithms and Theoretical Computer Science.
Stackforce AI infers this person is a leader in Quantum Computing and Theoretical Computer Science.

Contact

Skills

Core Skills

Quantum ComputingQuantum InformationTheoretical Computer Science

Other Skills

Algorithm DesignAlgorithmsApplied MathematicsArtificial IntelligenceC++Complexity TheoryComputer ScienceConvex OptimizationData StructuresJavaLinear AlgebraMachine LearningNumerical OptimizationObservational AstronomyProgramming

Experience

Gathergov

2 roles

Chief Technology Officer

Promoted

Nov 2025Present · 4 mos · Bengaluru

Head of Engineering

May 2025Oct 2025 · 5 mos · Bengaluru

Frnd

CTO, Co-Founder

Apr 2019Dec 2023 · 4 yrs 8 mos · Bengaluru, Karnataka, India

Worldquant llc

2 roles

Senior Quantitative Researcher

Promoted

Jan 2018Sep 2018 · 8 mos

Quantitative Researcher

Jul 2016Dec 2017 · 1 yr 5 mos

University of maryland

Summer Research Intern

May 2015Jul 2015 · 2 mos · College Park, Maryland

  • 1.) We worked on to find best(maximum success probability) LOCC protocol to distinguish a set of states given an extra shared resource state.
  • 2.) We conjectured that teleportation based protocol is indeed the best SEP protocol and hence the best LOCC protocol. We have numerical evidence for it are currently working to prove it analytically using convex optimization and linear algebra techniques.
  • 3.) We also tried to understand the amount of entanglement required to implement perfect nonlocal measurements. We made use of various numerical optimization techniques to study this in detail

National university of singapore

Research Intern

May 2014Jul 2014 · 2 mos · Singapore

  • 1.) Studied and implemented C++ code to calculate different Classical complexity measures (like Parity Bound, Block Sensitivity, Randomized Complexity etc.) of all 4-bit boolean functions.
  • 2.) Studied Query complexity of important functions like Distributivity, Associativity testing etc. We were successful in giving tight bound of \theta(n^{1.5}) for query complexity of Distributivity testing in Learning Graph model.

Education

Indian Institute of Technology, Kanpur

Bachelor’s Degree — Computer Science and Engineering

Jan 2012Jan 2016

D.A.V. Public school.kota

High School

Jan 2007Jan 2012

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