Campus Spotlight

Dragutin Petkovic, Ph.D., Professor of Computer Science

Keynote for 2025 IEEE CCWC

Dragutin Petkovic (IEEE Life Fellow since 2018, IEEE Fellow since 1998) received Ph.D. degree in electrical engineering from UC Irvine in 1983 in the area of biomedical image analysis, and B.S. and M.S. degrees in electrical engineering and multidisciplinary studies respectively from University of Belgrade, Serbia with emphasis on image and signal analysis. He is currently a professor of computer science at San Francisco State University (SFSU) since 2003 where he was computer science department chair from 2003 to 2015. In 2019, he founded and co-leads the multidisciplinary SFSU Graduate Certificate in Ethical Artificial Intelligence together with SFSU Department of Philosophy and School of Business. He was a founder and Director of SFSU Center for Computing for Life Sciences from 2005 till 2018 and collaborated on multiple NIH grants with Stanford University in the areas of Artificial Intelligence (AI) for bioinformatics. He held positions at VMware as a Senior Director, Applications, and as senior manager and researcher at IBM Almaden Research center, San Jose (1983-2000). His research focus included content based retrieval (he was founder of trend-setting IBM Query by Image Content QBIC project). For last 10 years his work combines AI and ease of use and has a goal to bring technology closer to people and users. Due to his concerns about the state of the ethics and trustworthiness of AI systems and their possibly negative implications to society, his recent focus is on explainable and trustworthy AI to which he contributes by papers, books, workshops, talks and by education of broader community via SFSU Certificate in Ethical AI.

Title For Talk: GenAI and Education: challenges, opportunities and some thoughts

Abstract: GenAI emerged as the fastest growing commercial technology with broad, strong and disruptive potential to affect all aspects of society: from business and education to everyday things we do. Recent IMF study on impact of AI on work predicts that 40% of jobs will be affected by GenAI, and for the first time most of those will be white collar jobs. GenAI is everywhere and easy to use, available 7/24, but it has its challenges and limitations. It also has very disruptive impact on education. This talk will have 3 parts: we will cover at very high level how GenAI work, then use this knowledge to summarize its issues, challenges and limitations, and then talk about its impact on education with some thoughts and educational experiences form speaker’s teaching at SFSU.

IEEE CCWC Keynote 2025 delivered by Dragutin Petkovic

Read more about the IEEE CCWC 2025 keynote vie the conference site

Wes Bethel, Associate Professor of Computer Science

Wes Bethel, associate professor of Computer Science, is the principal investigator of a research project that will study methods for automating the generation of software tools and processes for the purpose of constructing software that builds machine learning models.  

The work is in support of an effort funded by U.S. Department of Energy’s Office of Fusion Energy Sciences to leverage artificial intelligence (AI)/machine learning tools to reduce computational time-to-solution for specific physics calculations, with the ultimate objective of being able to predict plasma behavior in real time in fusion tokamak devices.  

Bethel, who joined SF State in 2022 after a career as a computer scientist at Lawrence Berkeley National Laboratory, has assembled a team of Computer Science graduates and undergraduates (V. Cramer, C. Pestano, A. del Rio and S. Verma), and other faculty (Computer Science Lecturer Lothar Narins) to study this problem. The SF State team is part of a larger multi-institutional effort led by J. Wright at the Massachusetts Institute of Technology and includes researchers from the Princeton Plasma Physics Laboratory and Lawrence Berkeley National Laboratory. 

The key idea behind the team’s approach is to leverage recent advances in cloud-based AI tools, such Large Language Model implementations such as OpenAI’s ChatGPT and GitHub’s Copilot to quickly produce code that builds other AI models and model validation processes. The intent is to reduce the time to solution for trained models from years to weeks.  

Bethel looks forward to reproducing this work on other computational challenges within the SF State scientific community.

Wes Bethel

Graduate Certificate in Ethical Artificial Intelligence

The Certificate in Ethical Artificial Intelligence (AI) is designed to offer professionals and graduate students the opportunity to acquire a deeper grasp of the ethical, legal and policy issues and implications of developments in artificial intelligence, addressing areas of impact including pharmaceutical and healthcare research and distribution, business application practices in data and finance, law enforcement, live and social media, information and news development and filtering, autonomous transportation (including automobiles and mass transit), the availability and distribution of government services and other sectors in society.

The program consists of three courses and a short research report on a specific application of ethical issues to AI. The award of the certificate means the holder has completed the required courses and research project at an acceptable level of academic accomplishment. The certificate indicates to potential employers and to other academic programs that the holder has achieved a foundation in the basic principles of artificial intelligence, the latest developments in AI and their ethical implications for society.

To learn more about the Graduate Certificate in Ethical Artificial Intelligence (AI), visit the Lam Family College of Business (LFCoB) Graduate Certificate in Ethical Artificial Intelligence page, or the Bulletin page.

Carlos Montemayor, Ph.D., Professor of Philosophy

Montemayor, C. (2023) The Prospect of a Humanitarian Artificial Intelligence: Agency and Alignment

In this open access book, Carlos Montemayor illuminates the development of artificial intelligence (AI) by examining our drive to live a dignified life.

He uses the notions of agency and attention to consider our pursuit of what is important. His method shows how the best way to guarantee value alignment between humans and potentially intelligent machines is through attention routines that satisfy similar needs. Setting out a theoretical framework for AI Montemayor acknowledges its legal, moral and political implications and takes into account how epistemic agency differs from moral agency.

Through his insightful comparisons between human and animal intelligence, Montemayor makes it clear why adopting a need-based attention approach justifies a humanitarian framework. This is an urgent, timely argument for developing AI technologies based on international human rights agreements.

Read more on the Department of Philosophy website

Carlos Montemayor
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