A network-based SIR simulation of a COVID-19 outbreak. A network-based SIR simulation of a COVID-19 outbreak.

Research

My research focuses on pricing and auctions, specifically providing complexity bounds and designing effective algorithms for determining viability of mechanisms in the dual settings of social welfare and revenue maximisation. This stimulating and active area of research has an abundance of open problems and deep implications for the world outside of academia.

My work on the Product-Mix Auction (PMA), a multi-unit, multi good auction initially proposed by Paul Klemperer for the Bank of England to provide liquidity to financial institutions during the crisis of 2007-8, focuses on finding effective algorithms to solve the auction with respect to social welfare and revenue maximisation. An implementation for social welfare is available here. In related work, I also study how bidder demand can be learnt via queries to a demand or valuation oracle, allowing bidders to participate in PMAs without having to understand the bidding language used.

I am also interested in mechanisms that maximise the benefits of scarce resources in low to middle income countries (LMICs). In response to the COVID-19 pandemic, I co-founded the project Test and Contain, which considers the problem of utilising limited testing resources in an optimal way so as to minimise the impact on the health and livelihoods of those who are hardest hit in LMICs. This project is supported by an ACM SIGecom GCEC’20 grant. For more information, watch the 1 minute poster video submitted to GCEC’20 (received best poster video award).

Publications

Substitutes markets with budget constraints: solving for competitive and optimal prices arXiv PDF
Simon Finster, Paul Goldberg and Edwin Lock.
WINE 2023: The 19th Conference on Web and Internet Economics, 2023
Solving Strong-Substitutes Product-Mix Auctions link arXiv
Elizabeth Baldwin, Paul W Goldberg, Paul Klemperer and Edwin Lock.
Mathematics of Operations Research, 2023
Welfare-Maximizing Pooled Testing link arXiv
Exemplary track paper award
Simon Finster, Michelle González Amador, Edwin Lock, Francisco Marmolejo-Cossío, Evi Micha, Ariel D. Procaccia.
24th ACM Conference on Economics and Computation, 2023
Learning Strong Substitutes Demand via Queries (journal version) link arXiv
Paul W Goldberg, Edwin Lock and Francisco Marmolejo-Cossío.
ACM Transactions on Economics and Computation, 2022
Optimal Testing and Containment Strategies for Universities in Mexico amid COVID-19 link arXiv PDF
Luis Benavides-Vázquez, Héctor Alonso Guzmán-Gutiérrez, Jakob Jonnerby, Philip Lazos, Edwin Lock, Francisco J. Marmolejo-Cossío, Ninad Rajgopal and José Roberto Tello-Ayala.
EAAMO'21: The ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, 2021
Learning Strong Substitutes Demand via Queries link arXiv
Nominated for best paper
Paul W Goldberg, Edwin Lock and Francisco Marmolejo-Cossío.
WINE 2020: The 16th Conference on Web and Internet Economics, 2020
Characterising and recognising game-perfect graphs link arXiv
Stephan Dominique Andres and Edwin Lock.
Discrete Mathematics and Theoretical Computer Science (DMTCS), vol. 21:1, #6 2019

Working Papers

The Computational Complexity of the Housing Market arXiv PDF
Edwin Lock, Zephyr Qiu and Alexander Teytelboym.
ArXiv preprint, 2024
Maximising the Benefits of an Acutely Limited Number of COVID-19 Tests arXiv
Jakob Jonnerby, Philip Lazos, Edwin Lock, Francisco Marmolejo-Cossío, C. Bronk Ramsey, Meghana Shukla and Divya Sridhar.
ArXiv preprint, 2020

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