Abstract: Implicit functions have long been a fundamental representation for both 2D and 3D objects in computer graphics, playing a significant role in the field's early development. With the rise of 3D deep learning and the rapid advancement of neural rendering techniques, implicit representations of 3D shapes have regained significant attention in recent years. In this talk, I will present several recent research projects focusing on implicit function-based 3D reconstruction and neural rendering. Furthermore, I will discuss potential future developments in this dynamic and rapidly evolving field.

Biography: Ying He is an Associate Professor at the College of Computing and Data Science, Nanyang Technological University, where he also serves as the Director of the Centre for Augmented and Virtual Reality. His research interests lie in geometric computation and analysis, with applications spanning computer graphics, 3D vision, computer-aided design, multimedia, and wireless sensor networks. Dr. He is an active member of the technical program committees for major conferences on geometric modeling and has served on the editorial boards of IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, and Computational Visual Media. He has also taken on key leadership roles as General/Program Co-Chair for several conferences, including Shape Modeling International (SMI) 2022, Solid and Physical Modeling (SPM) 2022 & 2023, Geometric Modeling and Processing (GMP) 2014 & 2021, and Computational Visual Media (CVM) 2020. For more information, please visit https://personal.ntu.edu.sg/yhe/

Location: NCS 115

Description:

As artificial intelligence and data science reshape the global information landscape, libraries are emerging as key players in both technological innovation and ethical stewardship. This international Zoom discussion brings together library professionals and educators from the U.S., Philippines, and Hong Kong to explore how institutions are integrating AI and data into their pedagogy and services.

Panelists will share concrete examples from their own libraries--ranging from data literacy initiatives to increasing discoverability. The conversation will also examine regional trends in librarianship, spotlighting how institutions in Asia are navigating the evolving role of data and AI.

Join us for a global conversation that highlights the transformative potential of libraries as hubs for innovation and critical inquiry in the age of AI.

Register for this free Zoom panel.

Panelists:

Ahmad Pratama is a Faculty Member and Associate Librarian at Stony Brook University Libraries, where he is working to build a comprehensive, campus-wide data literacy program within the Libraries. As the Data Literacies Lead, his work focuses on empowering students, faculty, and staff to critically and ethically engage with data and AI, including the development of a credit-bearing course in Critical Data & AI Literacies supported by an EDGE Fund Award from the Provost's Office. Previously, Dr. Pratama served as an Associate Professor of Information Technology, and his research and teaching explore the intersections of technology, policy, and society with a focus on data, AI, and innovation in higher education.

Dan Anthony Dorado is a full-time faculty member at the U.P. School of Library and Information Studies, where he teaches information technology, management and marketing, research methodology, and quantitative research. He was also the director of the Diliman Learning Resource Center under the Office of the Vice Chancellor for Student Affairs. Before that, he was an Information Specialist at the College of Engineering Library, in charge of the System and Network Administration and The Learning Commons. He completed his master's degree at the Technology Management Center in U.P. Diliman and is currently pursuing his PhD in Data Science. As a member of Sync.Bio.Optics laboratory and the Publics, Archives, and Data (PANDA) Lab, his research specialization covers Computational Methods, Open Education, Critical Data Studies, and Radical Statistics.

Ryun LEE is Associate University Librarian at The Chinese University of Hong Kong Library, leading Digital Initiatives and Library IT and Systems. He drives digital innovation through emerging technologies, particularly artificial intelligence to enhance services, streamline operations, and support CUHK's mission in research, education, and knowledge advancement. With a background in cataloging and digital repository development, Ryun leads projects in digitization, OCR, data visualization, text and network analysis, GIS, and digital scholarship. He actively promotes knowledge graph applications in Hong Kong studies and oversees efforts to digitize and preserve resources related to Hong Kong and Southern China. His recent work focuses on creating seamless digital experiences and developing data-driven infrastructure. He is currently exploring AI-driven approaches to digitization workflows and entity extraction, aiming to improve access, discovery, and long-term preservation of library materials.

The International Neuroethics Society (INS) Speaker Series on AI & Consciousness

Abstract: Colln Allen and I noted in our 2008 book Moral Machines: Teaching Robots Right From Wrong, that consciousness, a theory of mind, sociability, situational awareness and embodiment are all supra-rational (beyond reason) capabilities that contribute to making ethical decision Whether any of these can be fully instantiated in machines remains an open question. Nevertheless, moral decision making in the digital age will require an evolution in and refinement of specific skills for both humans and for AI. I call one of these evolutions in moral decision making capabilities tradeoff ethics and another a silent ethics. Aspects of this social, and not just technological evolution, will require research by neuroscientists.

Speaker Bio: Wendell Wallach has an international reputation as an expert on the ethics and governance of emerging technologies, particularly artificial intelligence and biotechnologies. He is also senior advisor to The Hastings Center and a scholar at the Yale University Interdisciplinary Center for Bioethics where he chaired Technology and Ethics studies for eleven years. Wallach's latest book, a primer on emerging technologies, is entitled, A Dangerous Master: How to keep technology from slipping beyond our control. He co-authored (with Colin Allen) Moral Machines: Teaching Robots Right From Wrong. Wallach has been referred to as, a Godfather of AI Ethics.

Pre-register here (required): https://umaryland.zoom.us/meeting/register/sPpiR_drR4-9JYDhI2NhJg
The Della Pietra Lecture Series is pleased to present this lecture by Scott Aaronson:

Abstract: Yes, scalable quantum computing should actually work! Sooner than many expect, which will create a huge headache when it breaks the encryption currently used to protect the Internet. But no, we don't think quantum computing can do most of what the popular articles promise in AI and optimization and so forth. Come to this talk to learn about why!

Speaker: Scott Aaronson is Schlumberger Chair of Computer Science at the University of Texas at Austin, and founding director of its Quantum Information Center. He received his bachelor's from Cornell University and his PhD from UC Berkeley. Aaronson's research has focused mainly on the capabilities and limits of quantum computers. His first book, Quantum Computing Since Democritus, was published in 2013 by Cambridge University Press. He received the National Science Foundation's Alan T. Waterman Award, the United States PECASE Award, the Tomassoni-Chisesi Prize in Physics, and the ACM Prize in Computing, and is a Fellow of the ACM and the AAAS and a member of the National Academy of Sciences. He blogs at Shtetl-Optimized, https://www.scottaaronson.com/blog.

Location: Della Pietra Family Auditorium (SCGP 103)
The Future of Learning: Rethinking Practice in a Changing World

Thursday, March 26, 2026 (Workshops)
Friday, March 27, 2026 (Symposium)

Open to Stony Brook University Faculty, Staff, and Graduate Students. Hosted by the Center for Excellence in Learning and Teaching, Office of the Provost.

Thursday, March 26, 2026
Workshop: AI Tools and Techniques
  • Open to all faculty & staff
  • Hands-on, exploratory
  • Registration only limited to the size of the room
  • Location: In-person, TBD
  • Time: 10 AM - 12 PM
  • Registration required

Friday, March 27, 2026
Keynote: Teaching and Thinking with AI
  • Faculty, TAs, postdocs, and academic staff
  • In-person on-campus conference venue
  • Location: SAC Balroom
  • Time: 9 AM - 3 PM
  • Registration required

Keynote Speaker: José Antonio Bowen

José Antonio Bowen has been leading innovation and change for over 40 years at Stanford, Georgetown and the University of Southampton (UK), as a dean at Miami University and SMU and as President of Goucher College. Bowen has worked as a musician with Stan Getz, Dave Brubeck, and many others and his symphony was nominated for the Pulitzer Prize in Music (1985).
Bowen holds four degrees from Stanford and has written over 100 scholarly articles and books, including the Cambridge Companion to Conducting (2003), Teaching Naked (2012 and the winner of the Ness Award for Best Book on Higher Education), Teaching Naked Techniques with C. Edward Watson (2017) and Teaching Change: How to Develop Independent Thinkers using Relationships, Resilience and Reflection (Johns Hopkins University Press, 2021).
Bowen has appeared in The New York Times, Forbes, The Wall Street Journal, and has three TED talks. Stanford honored him as a Distinguished Alumni Scholar (2010) and he has presented keynotes and workshops at more than 300 campuses and conferences 46 states and 17 countries around the world. In 2018, he was awarded the Ernest L. Boyer Award (for significant contributions to American higher education). He is a senior fellow for the American Association of Colleges and Universities.

Register here.
Recently, large-scale language data combined with modern machine learning techniques have shown strong value as means for studying human psychology and behavior. For example, language alone has been shown predictive in mental health, personality, and health behaviors. However, many applications for such language-based assessments have readily available and important data beyond language (i.e. extra-linguistics), such as predicting the subjective well-being of a community using tweets, where one can take into account their age, education, and demographic attributes. Language may capture some characteristics while extra-linguistic variables captures others. We believe that effectively integrating linguistic and extra-linguistic data can yield benefits beyond either independently. In this thesis, we develop methods which effectively integrate extra-linguistic data with language data focused primarily on social scientific applications. The central challenge is dealing with the size and heterogeneity of, often sparse and noisy, language data versus the, often low-dimensional and non-sparse, extra-linguistic variables. First, we consider structured extra-linguistics, like socioeconomic (income and education rates) and demographics (age, gender, etc.), and propose two integration methods, named residualized controls (RC) and residualized factor adaptation (RFA), to be used in county-wise prediction tasks. Demonstrating techniques that integrate information at both the model-level and data-level, we found consistently strong improvement over naively combining features, for example, increasing county level well-being predictions by over 12%. Next, we consider unstructured extra-linguistic data. In the first part, we incorporate social network connections and language over time to propose a novel metric for quantifying the stickiness of words - their ability to spread across friendship connections in a social network over time (or in other words, stick in ones vocabulary after seeing friends use it). We obtain which language features are more probable to disseminate through friendship and show such a metric is useful for predicting who will be friends and what content will spread. In addition, we analyze language content over time by proposing a novel dynamic content-specific topic modeling technique that can help to identify different sub-domains of a thematic scope and can be used to track societal shifts in concerns or views over time.

AI is everywhere -- and so are the privacy concerns that come with it. At its core, the most common forms of AI we use today are online digital services -- and thus inherit the usual privacy risks of any internet-based tool. However, AI also introduces a set of unique and evolving risks. We'll take a closer look at one of the newest developments in this area: indirect prompt injection -- a technique that can trick AI tools into revealing or extracting private information. You'll learn how this emerging form of AI manipulation works, why it matters, and how to protect yourself -- as well as how similar techniques are being used in academic contexts to manipulate systems and even mislead researchers.

Register for this Zoom workshop.

Unlock the power of AI in your job search! Join the Head of Indeed Job Search Academy and AI experts as they explore how to leverage cutting-edge AI tools to optimize your job search activities, enhance your resume, prepare for interviews, and conduct thorough
career research, as well as answer all your AI-related questions.
This virtual watch party session will equip you with the knowledge to stand out in today's competitive market.

https://forms.gle/TtWu3iDh9bmU3niD6