Luca de Alfaro

Luca de Alfaro

Professor

Computer Science and Engineering

Ph.D. Stanford University, 1998

  • Email: luca@ucsc.edu
  • Phone: +1 (650) 248-2856

Research

Reputation systems, game theory, formal methods and verification, machine learning, reinforcement learning.

Currently, I am working on applications of reinforcement learning to network protocols, on fairness in machine learning, on the psychology underlying crowdsourcing, and on cloud implementations of Wikipedia reputation systems.


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All the class homepages up to Spring 2020 included can be found on my legacy UCSC site.

CSE 30

Fall 2020

Academic curriculum vitae

Education

  • Ph.D., Computer Science, Stanford University, 1998.
  • M.S., Computer Science, Stanford University, 1997.
  • Doctorate, Systems and COmputer Engineering, Politecnico di Torino, 1995.
  • B.S., Electrical Engineering, Politecnico di Torino, 1990.

Employment

  • Professor, Computer Science and Engineering, UC Santa Cruz. Faculty at UC Santa Cruz since 2001.
  • Faculty visitor, then Staff Research Scientist, Google, 2008-2011 (on leave from UC Santa Cruz).

Honors

  • ESWEEK 2020 Test of Time Award for the paper Interface Theories for Component-Based Design, written with Thomas A. Henzinger, and originally published in the proceedings of the EMSOFT2001 Conference.
  • LICS 2020 Test of Time Award, for the paper Concurrent Omega-Regular Games, written with Thomas A. Henzinger, and originally presented in the IEEE Symposium on Logic in ComputerScience (LICS) 2000.
  • ACM SIGSOFT Impact Paper Award 2012, for the paper Interface automata, written with Thomas A. Henzinger, and originally publised in the proceedings of ESEC/FSE 2001.
  • Best paper candidate, AAAI Conference on Human Computation and Crowdsourcing (HCOMP), 2016.
  • Best paper award, 12th International Conference on Concurrency Theory (CONCUR) 2001.
  • NSF Early Faculty Career Award, 2001
  • Samuel Thesis Award, Stanford University, 1998.
  • Nomination for ACM Doctoral Dissertation Award, Stanford University, 1998.
  • Graduation Cum Laude, Politecnico di Torino, Italy, 1990.

Industry

Current Ph.D. Students

  • Molly Zhang
  • Jonathan Scott
  • Golam Md Muktadir
  • Suzanne da Câmara

Alumni

Postdocs

  • Krishnendu Chatterjee (2008-2009)
  • Maria Sorea (2005)
  • Marco Faella (2002-2005)
  • Mariëlle Stoelinga (2001-2004)

Ph.D.

  • Shenshen Liang (Ph.D. 2020)
  • Rakshit Agrawal (Ph.D. 2019)
  • Michael Shavlovsky (Ph.D. 2017)
  • Vassilis Polychronopoulos (Ph.D. 2017)
  • Maria Daltayanni (Ph.D. 2015)
  • Bo Adler (Ph.D. 2010)
  • Vishwanath Raman (Ph.D. 2010)
  • Pritam Roy (Ph.D. 2009)

Here are a few projects that have openings for students at the undergraduate level.

Fairness in Machine Learning

The project seeks to analyze ML algorithms and datasets with respect to the equity of the classification or output they give. This can be used both to study the fairness of ML algorithms, and to find classes of input for which the performance of the ML algorithms is weak.

We are developing the theory with graduate students and collaborators. We are seeking one undergraduate student with experience in data visualization, web-site building and cloud serving, and cloud (Google cloud preferred).

Wikipedia Reputation and Edit Analysis

The project consists in developing a reputation system for Wikipedia users and content (see publications on Wikipedia reputation and trust). At the moment, we are developing the basic infrastructure and algorithms. We will soon have openints for students with experience in Python, algorithms, and cloud computing.