CS Colloquium

Teed Rockwell

Stevenson 1300
Monday, September 22, 2025

For most of human history, human knowledge was considered to be something that was stored and captured by words. This began to change when Galileo said that the book of nature is written in the language of mathematics. It is now an assumption of both scientific and popular common sense that science provides knowledge about the world because it uses mathematical formulae called algorithms. The growing sophistication of computer science has reduced many of our most sophisticated mental processes to algorithms, causing white collar jobs to be replaced by computers at the same rate that blue collar jobs were once replaced by factory machinery. As a result, it is very difficult in our time to explain why anyone should bother to study knowledge which consists of stories, i.e. words, rather than mathematical formulae.

I will argue that the stories told by the humanities do more than just stir our emotions. They deliver genuine knowledge about aspects of reality that are beyond the comprehension of algorithmic knowledge. I will outline the basic elements of an algorithm that shows how we get knowledge out of these stories. The main challenge of creating algorithmic formulae is making them detailed and precise enough that they can be followed by machines. Stories, however, get their power from the richness of their ambiguity. Somehow we do learn from stories. Somehow, their imprecision makes them universal and profound, not empty and vague.

What is going on inside the minds of people who can correctly follow instructions that are too vague to be functioning algorithms? Can this sort of “know how” be duplicated mechanically by an algorithm? I will propose an explanation for this apparently inexplicable fact, based on connectionist algorithms that are the basis of modern AI.

Sarah Thornton

Stevenson 1300
Monday, October 6, 2025

The choices we make in our algorithms reverberate across society in many dimensions, changing our expectations of mobility, safety, employment and other aspects of life we value. These major societal changes will, in turn, be the result of a number of small engineering decisions that, when aggregated, determine the system behavior. In order for our technology to evolve in ways we desire, we must bridge the gap between individual engineering decisions and the societal impacts they create. This workshop discusses some of the challenges faced by engineers and proposes a value-centered approach, engaging stakeholders early in the process, identifying values and tensions that should be resolved.

Tapti Palit
UC Davis

Stevenson 1300
Monday, October 13, 2025

C and C++ remain two of the most widely used programming languages, powering everything from operating systems to critical infrastructure. However, their lack of built-in memory safety leaves applications vulnerable to exploitation, and memory corruption vulnerabilities cost the industry billions of dollars annually. To mitigate these risks, software defenses such as Control Flow Integrity (CFI) are deployed, but their effectiveness depends heavily on the precision of underlying program analysis.

In this talk, I will present my research on advancing program analysis techniques to improve software security. First, I will introduce the Invariant-Guided Pointer Analysis technique, which enhances the precision of CFI mechanisms by 59%, thus significantly improving its security guarantees. Then, I will discuss our lab's latest research on automatically transpiling C/C++ code into memory-safe languages, like Rust. Specifically, I will describe our hybrid approach, which combines Large Language Models (LLMs) with program analysis techniques to achieve high-accuracy C-to-Rust transpilation. Together, these efforts improve software security for legacy software and building a foundation for safer, more reliable software systems.

Oluwaseun Sanwoolu
University of Kansas

Stevenson 1300
Monday, October 27, 2025

What would it mean to align AI systems with Kant’s moral theory if they can’t be moral agents like humans? I argue that it is still possible. The first challenge is that Kant’s ideas are built for moral agents, but in the view I defend,  AI can still follow his basic test: create a rule for action and ask if it would work for everyone in such a situation. This gives us a way to design and check AI decision-making using the Formula of Universal Law.

The second challenge is that Kant’s approach can seem too rigid to handle different situations. I show that his framework can adapt to context-sensitivity through practical judgment. While AI lacks human judgment, it can use a functionally similar mechanism such as transformer models to factor in important details before acting. This means Kant’s ideas can still guide AI design in a way that is both consistent and flexible.

Dept Event

Overlook (Student Center, 3rd floor)
Monday, November 3, 2025

CS students, join us for Advise-a-palooza for Fall 2025 registration.

John P. Sullins III
Sonoma State University

Stevenson 1300
Monday, November 10, 2025

Sociotechnical risks are a reality of all technology design, and one that particularly matters in an organization like the Department of Defense.  We will look at a two-year project housed here at SSU where SSU faculty and students collaborated with Cal Poly SLO faculty and students to build a prototype application for helping DoD projects identify how best to utilize the responsible AI toolkit and NIST Framework as these applied to their particular projects.  We will also examine how LLMs present new problems for military AI applications.

Dept Event

Stevenson 1300
Monday, November 24, 2025

Short presentations of research carried out by Sonoma State Computer Science Students, and CS awards.

Dept Event

Stevenson 1300
Monday, December 1, 2025

Short presentations of capstone projects carried out by Sonoma State Computer Science Students