CS Colloquium

Spring 2021

Presented by the Computer Science Department
Wednesdays 12:00 - 12:50pm, Online
All lectures free and open to all
Email Dena Peacock for Zoom link

How does AI Perceive You?

Nina Marhamati
Assistant Professor
Computer Science Sonoma State University


Have you ever wondered how Siri, Alexa, or any chat-bot perceives you? We are interested in answering this question by making it possible to receive feedback from interactions with AI. Understanding the human message and emotion when approaching a machine is a valuable psychological experience and can tell us a lot about ourselves and our society. In collaboration with the Art Department, we are using AI methods to create a reaction to people’s interaction with machines.  The interaction received through sensory inputs is processed by the machine and the content of the interaction is decoded. Using deep learning models for natural language processing, the emotional state of the interaction is detected from the content. The detected state is used to visualize, in 2D or 3D, what the machine has perceived from the interaction. The final product will give the user a personalized interaction with the machine through a piece of art that reflects the user's emotion. This product can be combined with VR equipment and used for providing more realistic experience for game players, online training participants, or interaction with chat-bots.

Juneau: Managing and Guiding Data Science

Zachary Ives
Adani President's Distinguished Professor and Department Chair, Computer and Information Science Department
University of Pennsylvania


How do we promote large-scale data science and data sharing, e.g., in the sciences or across organizations? Many modern data science applications have been leveraging data lakes: schema-agnostic repositories of data files and data products, which offer limited organization and management capabilities. There is a need to build a new generation of data science environments, which leverage data lakes so scientists and analysts can find tables, schemas, workflows, and datasets useful to their task at hand. Juneau incorporates search and management solutions into the Jupyter Notebook data science platform, to enable scientists to augment training data, find potential features to extract, clean data, and find joinable or linkable tables. Our core methods also generalize to other settings where computational tasks involve execution of programs or scripts.

Addressing Climate Change through Drone Swarms

Emily Spahn
Software Engineer


Climate change is a major issue of concern worldwide. Trees are currently among the best ways to capture carbon. DroneSeed has been a leader in mass reforestation by drone, and is uniquely able to reforest after wildfires. We'll explore the evolution of technological needs to support this goal. Let's talk about how we went from the idea of combining biology with the emerging drone industry, to arrive at the realities of a startup putting seeds on the ground in post-wildfire environments.

Distributed Cache Invalidation at Scale

Greg Cooper
Software Engineer


Dr. Cooper will describe some of the challenges involved in building a large-scale distributed cache invalidation system and will present the design for one such system, called Thialfi, which was built and operated at Google for most of the past decade. He will also discuss the limitations of that design and touch on ways in which modern infrastructure allows improvements to it. The work is joint with Atul Adya, Phil Bogle, Dennis Geels, Brice Hulse, Larry Kai, Vishesh Khemani, Nick Kline, Colin Meek, Amanda Moreton, Daniel Myers, and Michael Piatek.

Machine Learning Enhanced Video Accessibility for Blind and Low Vision Individuals

Ilmi Yoon
Professor, Computer Science Dept.
San Francisco State University


The blind or visually impaired often miss out on the visual information conveyed through videos. The vast majority of online video material is currently not accessible to millions of visually-impaired people who would significantly benefit from improved access to videos for education, employment, and entertainment purposes.

This work addresses two major issues:

  1. Enhancing video accessibility for blind or visually-impaired individuals.
  2. Generating well-structured training data to advance the state of the art in video understanding.

Spring 2021 Short Presentations Of Student Research



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