Alessandro Checco

Alessandro Checco is an Assistant Professor in the Computer Science Department at University of Rome La Sapienza. His research focuses on crowdsourcing, distributed systems, and privacy-preserving technologies, bridging theoretical computer science with practical applications that consider human factors in technological systems. He has established himself as a significant contributor to the field of human computation and privacy-aware systems.

His educational background includes:

• 2020: Fellowship of Higher Education from The University of Sheffield, Higher Education Academy
• 2015: Ph.D. in Mathematics from Hamilton Institute (Design of decentralised algorithms applied to channel/code selection and convex optimisation for throughput fairness of 802.11 networks)
• 2010: M.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction)
• 2009: Erasmus Scholarship at Universiteit Gent, Department of Telecommunications
• 2007: B.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction)

Checco's research spans multiple areas at the intersection of computer science and social implications of technology. He is particularly interested in Crowdsourcing for Human Computation, Distributed Private Recommender Systems, Information Retrieval, Data Privacy, Distributed Systems, User Data Obfuscation in Web Systems, Societal and Economic Analysis of Online Work, Crowd Workers Unionisation, and Algorithmic Bias. His work often examines how technological systems can be designed to respect user privacy while maintaining functionality, and how crowd work can be structured to be more equitable for workers.

His recent publications demonstrate a clear evolution in research focus, beginning with foundational work in wireless networks and distributed algorithms, then shifting toward human computation and privacy-preserving systems. His most recent work increasingly addresses the societal implications of crowd work, including investigations into crowd worker unionization and cooperative models. Several publications examine gender bias in algorithmic systems, reflecting growing attention to fairness and ethical considerations in his field.

Among his notable achievements:

• All That Glitters is Gold-An Attack Scheme on Gold Questions in Crowdsourcing (Best Paper Award)

Checco has secured significant research funding and led important projects including the H2020-funded FashionBrain project as Research Director and the EPSRC-funded BetterCrowd project as Research Associate. His work on the FashionBrain project demonstrates his ability to lead large-scale, interdisciplinary research initiatives. He has also received the Technology Innovation Development Award (TIDA) from Science Foundation Ireland.

His research has practical applications across multiple domains including recommendation systems (BLC: Private Matrix Factorization Recommenders), peer review assistance using AI, smart farming technologies, and cooperative models for crowd workers (CrowdCO-OP). He has developed frameworks for understanding worker behavior in crowdsourcing platforms and created methods for improving quality control in human computation systems.