Colloquium Archive

Build Your Own Game Engine

Scott Gordon
Dept. of Computer Science, Sacramento State University


Video games today are built using engines such as Unity, Unreal, Lumberyard, CryEngine, and dozens of others.  The engine handles the basic tasks common to all games: 3D real-time rendering, object and scene-graph management, lighting, cameras, animation, etc.  Perhaps you've used an engine to make your own game, but have you ever thought of building your own engine?  It's a fun and challenging project that appeals to aspiring hard-core coders.  Dr. Scott Gordon is a professor at Sacramento State University, where students in his Game Architecture course build video games atop his own game engine "TAGE".  But a few of his most ambitious students opt instead to first build their own engine from scratch.  In this talk, Dr. Gordon describes how game engines are organized, and how to build your own.

Non-invasive blood glucose monitoring using breath volatile organic compounds

Sudhir Shresta
Dept. of Engineering Science, Sonoma State University


We are developing a smart breath glycemia reader (BGR), a breathalyzer-type hand-held device, that can predict blood-glucose levels from human breath. The device has a microcontroller, volatile organic compound (VOC) sensors, a rechargeable battery, and a wireless chip. We are currently collecting data from patients with type-2 diabetes. We aim to use the data to train machine learning (ML) models and implement into the device for real-time glycemia predictions. Diabetes is a major health problem in the United States that affects more than 122 million people. It requires continual management of blood glucose (BG) to avoid acute and long-term complications, yet, about half of patients with type-2 diabetes do not adhere to their BG treatment plan. Our device, when fully developed, will give patients an accessible modality to read the glycemic status without having to prick their fingers and allow them to test as many times as they desire and easily track their BG history. This will help address the nonadherence and improve BG management among patients with type-2 diabetes.

Fall 2022 Short Presentations Of Student Research


Short presentations of research carried out by Sonoma State Computer Science Students.

Fall 2022 Short Presentations Of Student Research


Short presentations of research carried out by Sonoma State Computer Science Students.

Probabilistic Methods in Computer Science, Data Science, and Public Health

Aravind Srinivasan
Professor of Computer Science
University of Maryland, College Park, MD


Probabilistic methods---randomized algorithms as well as the stochastic modeling of inputs to a problem---play a fundamental role in computer science and data science. We will discuss some of their foundational aspects, along with key applications in public health and in the Internet economy. We will cover aspects including the Lovasz Local Lemma, data science in E-commerce and Internet advertising, fairness, and probabilistic methods in the control of infectious diseases. The talk will be accessible to a broad computer-science audience.