Research Bio

Hi,

My name is Abhinav Sinha (email: s.abhinav.sinha "at" gmail "dot" com). Thank you for visiting my research website. I was previously a postdoctoral research scholar at the Decision, Risk and Operations division of the Graduate School of Business at Columbia University, where I work with Prof Yash Kanoria and Prof Fanyin Zheng. I received my PhD in Electrical Engineering from the University of Michigan, Ann Arbor in 2017 where I was advised by Prof Achilleas Anastasopoulos. I also received a Masters in Mathematics whilst at University of Michigan. Prior to that I received a dual-degree (Bachelors with honours and Masters) in Electrical Engineering from the Indian Institute of Technology Bombay, Mumbai in 2012, along with Minors in Computer Science.

My resume can be found here.

My research lies at the intersection of econometrics of two-sided platforms, economics of strategic agent interaction and resource allocation on distributed networks. I have experience of both empirical and modeling research. I am currently working on a demand estimation project with the aim of optimizing assortment size in online e-retail platforms. In general, with too large an assortment size, a platform can avail inventory logistics and procurement cost benefits by reducing assortment size. However, we focus on the customer-side performance and design a structural estimation methodology that can estimate the choice paralysis effect faced by customers, whereby presenting customers with a larger set of products actually reduces their likelihood of making a purchase. We are using customer click and purchase data from Allmodern, an online retailer of home-goods. During my PhD, I worked on theoretical network resource allocation problems in the presence of strategic decision-makers, where I focused on the mechanism design and game theoretical problems that arise in this setting. Along the way I developed modeling expertise in the areas of game theory, stochastic control, distributed optimization, and probability.

In addition to my research, I was also fortunate to teach the PhD course "B9323: Introduction to Econometrics and Statistical Inference", at the Columbia Business School (Fall 2018).

Selected Research & Teaching

Working paper(s)

  • "Optimizing assortment size in online platforms". A. Sinha, Y. Kanoria, F. Zheng and Z. Lai.

      • Latest version of the working paper.

      • Two recent conference presentations: slides from INFORMS 2019 (Seattle) and slides from MSOM 2019 (Singapore).

Selected list of publications

  • "Distributed mechanism design with learning guarantees for private and public goods problems". A. Sinha and A. Anastasopoulos (accepted, to appear in IEEE Transactions on Automatic Control).

  • "A systematic process for evaluating structured perfect Bayesian equilibria in dynamic games with asymmetric information". D. Vasal, A. Sinha and A. Anastasopoulos. IEEE Transactions on Automatic Control, 64.1 (2018): 81-96.

  • "Incentive Mechanisms for Fairness among Strategic Agents". A. Sinha and A. Anastasopoulos. IEEE Journal on Selected Areas in Communication - Game Theory for Networks, 35.2 (2017): 288-301.

  • "Mechanism design for resource allocation in networks with intergroup competition and intragroup sharing". A. Sinha and A. Anastasopoulos. IEEE Transactions on Control of Networked Systems 5.3 (2017): 1098-1109.

  • "A distributed mechanism for public goods allocation with dynamic learning guarantees". A. Sinha and A. Anastasopoulos. Proceedings of the 12th workshop on the Economics of Networks, Systems and Computation. ACM, 2017.

  • "A practical mechanism for network utility maximization for unicast flows on the internet". A. Sinha and A. Anastasopoulos. Proceedings of the International Conference on Communications, June 2015, pp. 5679–5684.

  • "A general mechanism design methodology for social utility maximization with linear constraints". A. Sinha and A. Anastasopoulos. ACM SIGMETRICS Performance Evaluation Review, vol. 42, no. 3, pp. 12–15, 2014.

  • "Online linear optimization via smoothing". J. Abernethy, C. Lee, A. Sinha, and A. Tewari. Proceedings of the 27th Conference on Learning Theory, 2014, pp. 807–823.

  • "Optimal power allocation for a renewable energy source". A. Sinha and P. Chaporkar. 2012 National Conference on Communications (NCC), Kharagpur, 2012, pp. 1-5.

Tutorial(s)

  • "Mechanism Design for Network Allocation Problems". Tutorial presented by A. Anastasopoulos and A. Sinha at IEEE International Conference on Communications, May 2018.

Thesis

  • "Mechanism Design with Allocative, Informational and Learning Constraints". Abhinav Sinha, 2017. University of Michigan, Ann Arbor.

Teaching experience

  • Instructor for the PhD course "B9323: Introduction to Econometrics and Statistical Inference" at Columbia Business School (Fall 2018).

      • Appreciate letter from the Vice Dean for Curriculum and Instruction at Columbia University.

  • Co-taught the undergraduate course "EECS:301 Probabilistic Methods in Engineering" with Prof Sandeep Pradhan at University of Michigan (Spring 2017).

  • Co-taught the graduate course "EECS:501 Probability and Random Processes" with Prof Sandeep Pradhan at University of Michigan (Spring 2016).

References

  • Yash Kanoria, Sidney Taurel Associate Professor of Business in the Decision, Risk and Operations division at Columbia Business School. Email: ykanoria@columbia.edu.

  • Fanyin Zheng, Assistant Professor of Business in the Decision, Risk and Operations division at Columbia Business School. Email: fanyin.zheng@columbia.edu.

  • Jacob Abernethy, Assistant Professor in the School of Computer Science in the College of Computing at the Georgia Institute of Technology. Email: prof@gatech.edu.

  • Achilleas Anastasopoulos, Associate Professor in the Electrical Engineering and Computer Science department at the University of Michigan, Ann Arbor. Email: anastas@umich.edu.