RSCA in Five: Faculty Short Talks on AI/Ethics

Artificial intelligence (AI) is increasingly integrated into everyday life, from digital voice assistants to autonomous vehicles and education, without sufficient discussions of their ethical implications. Join SJSU faculty as they explore the intersections of AI's potential technological benefits and privacy, bias, transparency, and accountability.

When: Friday, October 13, 2023, from 11:30 a.m. to 1:30 p.m.
Where: King Library, Room 213
Format: In-person event — lunch will be served

Register for the event on our RSVP form.

View the live stream on Vimeo.

SJSU welcomes the following faculty who will be presenting their research.

Bryce Westlake

Talk Title: Matching victims and offender in child sexual abuse videos and images using machine learning

Bryce Westlake headshotBryce Westlake, 

Associate Professor, Department of Justice Studies (Forensic Science), College of Social Sciences

For the past 15 years, Dr. Westlake has investigated the distribution of child sexual abuse material (i.e., child pornography) online. His work focuses on the development of automated tools to detect, collect, analyze, and match child sexual abuse videos and images disseminated online. He is the Director of the Silicon Valley Digital Forensics Laboratory and introduced the digital evidence concentration in forensic science at San Jose State University.


  • Ph.D. in Criminology, 2014, Simon Fraser University
  • M.A. in Criminology, 2011, Simon Fraser University
  • B.A. in Psychology/Sociology, 2007, The University of British Columbia


Areas of Interest/Keywords: child sexual abuse; automated detection; biometrics; internet; social network analysis

Recent Publications

  1. Westlake, B. & Guerra, E. (2023). Using file and folder naming and structuring to improve automated detection of child sexual abuse images on the Dark Web. Forensic Science International: Digital Investigation47, 301620. DOI: 10.1016/j.fsidi.2023.301620

Étienne Brown

Talk Title: Algorithmic Amplification and Democratic Equality

Etienne Brown photo

Étienne Brown, 

Assistant Professor, Department of Philosophy, College of Humanities and the Arts

Étienne Brown is an assistant professor of philosophy at San José State University. His research focuses on the political philosophy of online speech, with a current focus on content moderation and algorithmic amplification on social media platforms. Previously, he was a postdoctoral scholar at the University of Oxford and the Université de Montréal. His recent publications include “Free Speech and the Legal Prohibition of Fake News” (Social Theory and Practice), “The Only Reason to Do Anything: Online Trolling as a Disruption of Joint Action” (Routledge Handbook of Media Ethics) and Moral Judgement: An Introduction Through Anglo-American, German and French Philosophy (Rowman & Littlefield, 2022).


  • Ph.D. in Philosophy, 2016, Université Paris-Sorbonne
  • M.A. in Philosophy, 2011, University of Ottawa
  • B.Soc.Sc., 2009, University of Ottawa


Areas of Interest/Keywords: Equality, Democracy, Free Speech, Recommender Systems, Content Moderation, Artificial Intelligence

Recent Publications

  1. Brown, E. (2023). Free speech and the legal prohibition of fake news. Social Theory and Practice, 49(1), 29-55. DOI: 10.5840/soctheorpract202333179 

Mahima Agumbe Suresh

Talk Title: SaFeR: A Safety Framework for e-Scooter Riders

Mahima Agumbe Suresh photoMahima Agumbe Suresh,

Assistant Professor, Department of Computer Engineering, College of Engineering

Mahima Agumbe Suresh is an Assistant Professor at San Jose State University. She received her Ph.D. from the Department of Computer Science and Engineering at Texas A&M University in December 2015 following which, she was a postdoctoral researcher at Xerox Research Labs, India.


  • Ph.D. in Computer Science, 2015, Texas A&M University


Areas of Interest/Keywords: edge computing, machine learning, modeling and system design for cyber-physical systems and the Internet of Things

Recent Publications

  1. Subramanyam, R. P., Naik, A., & Suresh, M. A. (2023). Accident prediction on e-bikes using computer vision. 2023 IEEE Ninth International Conference on Big Data Computing Service and Applications (BigDataService), 186-190, DOI: 10.1109/BigDataService58306.2023.00040.

Rhonda Holberton

Rhonda Holberton photoRhonda Holberton, 

Associate Professor, Department of Art & Art History, College of Humanities and the Arts

Rhonda Holberton utilizes technology as a medium to reconcile the biological body with geologic time, revealing their material and environmental impacts both on individual entities and on a planetary scale. Her subtle animations, digital interventions, sculptures and installation pieces move between the material and the immaterial, the authentic and synthetic, and pay special attention to the phenomenology of climate change in order to imagine ways we might collectively write more inclusive rules for digital platforms. Holberton has exhibited widely, including at CULT Aimee Friberg (San Francisco), RMIT Gallery (Melbourne); La Becque | Résidences d’artistes  (La Tour-de-Peilz, Switzerland);  FIFI Projects (Mexico City); Yerba Buena Center for the Arts (San Francisco); Holberton’s work is included in the permanent collections of the Whitney, SFMOMA, and the McEvoy Foundation, as well as various private collections. 


  • M.F.A. in Fine and Studio Arts, 2012, Stanford University
  • B.F.A. in Sculpture, 2007, California College of the Arts


Areas of Interest/Keywords: Digital Stewardship, AI & Ethics, VR, Environmental Justice

Magdalini Eirinaki

Talk Title: Recommender Systems: The good, the bad, and the ugly

Magdalini Eirinaki photoMagdalini Eirinaki, 

Professor, Department of Computer Engineering, College of Engineering

Dr. Magdalini Eirinaki is a Professor at the Computer Engineering Department and the program Director for the Master’s in Artificial Intelligence program. Her research work covers recommender systems, machine learning, data mining, social graphs, and deep learning applications. Dr. Eirinaki is the recipient of the 2019 Newnan Brothers Award for Faculty Excellence, the 2017 Applied Materials Award for Excellence in Teaching and many of her students have been finalists in the California State University student research awards over the past decade. Her most recent research projects focus on the use of AI in various application domains, including medical diagnosis, recommender systems, and cybersecurity. 


  • Ph.D. in Computer Science (Informatics), 2006, Athens University of Economics and Business
  • M.Sc. in Advanced Computing, 2000, Imperial College
  • B.Sc. in Computer Science (Informatics), 1998, University of Piraeus


Areas of Interest/Keywords: recommender systems, machine learning, social network analysis, graph mining, deep learning

Recent Publications

  1. Eirinaki, M., Varlamis, I., Dahihande, J., Jaiswal, A., Pagar, A. A., & Thakare, A. (2022). Real-time recommendations for energy-efficient appliance usage in households. Fronters in Big Data5, 972206. DOI: 10.3389/fdata.2022.972206

Gheorghi Guzun

Gheorghi Guzun photoGheorghi Guzun, 

Assistant Professor, Department of Computer Engineering, College of Engineering

Gheorghi Guzun has been a faculty member in the Department of Computer Engineering at San Jose State University since 2017. His research interests include various aspects of data management, such as, data analysis and exploration, data compression, large-scale indexing, information retrieval, and machine learning. Many of his projects are focused on scalability and performance of large data management systems, with a special interest in hardware-driven software design for data analytics, and intelligent systems. Dr. Guzun is a recipient of the CAREER award from the National Science Foundation.


  • Ph.D. in Electrical and Computer Engineering, 2016, University of Iowa
  • B.Eng., 2010, Technical University of Moldova


Areas of Interest/Keywords: Data management algorithms and systems that accelerate big data analytics through scalable indexing; Data compression; Machine learning algorithms.

Recent Publications

  1. Vats, A., Guzun, G., Anastasiu, D. C. (2022). CLP: A platform for competitive learning. European Conference on Technology Enhanced Learning, 615-622.