Ph.D. Dissertation Defense Talk: Measuring Harms and Empowering Users: Case Studies in Online Advertising and Generative AI
Speaker: Tina Yeung, Advisor: Franziska Roesner, Supervisory Committee: Franziska Roesner (Chair), Benjamin Mako Hill (GSR, Communication - Department of), Joseph Calandrino (CMU), Tadayoshi Kohno, Emily Tseng (Human Centered Design and Engineering), Abstract: The internet and generative AI were both promised as democratizing technologies – tools that would empower people to do and create more in their everyday lives. But, these ecosystems share an important flaw: companies have converged on strategies that leverage users’ data, time, and attention (and more), often at the cost of people's digital safety and well-being. As researchers, one of the hardest things about trying to improve these ecosystems for users is their opacity – many online and generative AI companies engage in behavior that is (intentionally) obfuscated from anyone trying to examine them. I focus on two main threads across my research: uncovering the harms caused by online advertising platforms and generative AI companies. And second, I…
Tuesday, June 2, 2026, 10:00 AM – 11:00 AM.
Ph.D. Dissertation Defense Talk: Bridging Language and Disability Lenses in the Design of Deaf and Hard-of-Hearing Communication Access Technologies
Speaker: Aashaka Desai, Advisors: Richard Ladner, J. Mankoff, Supervisory Committee: Richard Emil Ladner (Chair), J. Mankoff (Chair), Amy J. Ko (GSR, Information School), Danielle Bragg (Microsoft Research), JON E FROEHLICH, Alex Lu (Microsoft Research), Abstract: Deaf and hard-of-hearing (DHH) individuals communicate in many different ways -- using sign, speech, writing, touch and more. In designing technologies for DHH individuals, most research takes a disability lens, exploring how technologies can support this wide range of communication access needs. However, engagement with language and language-related factors is limited. My dissertation argues that a language lens can be generative in designing for DHH communication accessibility, allowing us to better understand multilingual and multimodal realities and build technologies for both language access and communication access. To demonstrate this, I present three studies exploring DHH communication online: exploring speechreading in video-calls,…
Tuesday, June 2, 2026, 12:00 PM – 1:00 PM.
Ph.D. Dissertation Defense Talk: The Science of Synthetic Data for Language Models: Search, Verification, and Scaling
Speaker: Jaehun Jung, Advisor: Yejin Choi, Supervisory Committee: Yejin Choi (Chair), Aylin Caliskan (GSR, Information School), Zaid Harchaoui (Statistics), Pang Wei Koh, Abstract: The capabilities of large language models are fundamentally tied to their training data. As the demand for high-quality data outpaces the supply of naturally occurring human text, the field has increasingly relied on synthetic data as a scalable alternative. However, simply generating more data is insufficient; naive scaling quickly saturates. In this talk, I argue that meaningfully scaling synthetic data requires three synchronized components: generating candidate data through principled search, verifying its quality with provable guarantees, and amplifying the latent quality dimensions that gate generalization.I will present a research program organized around these three pillars:
- Search: I will introduce iterative synthesis methods that decouple what constitutes good data from who generates it, enabling weak models to…
Thursday, June 4, 2026, 8:30 AM – 9:30 AM.
Ph.D. Dissertation Defense Talk: Physical and Computational Approaches Towards More Scalable Molecular Systems
Speaker: Ashley Stephenson, Advisors: Luis Ceze, Jeff Nivala, Karin Strauss, Supervisory Committee: Jeffrey Nivala (Chair), Jorge A Marchand (GSR, Chemical Engineering), Luis H Ceze, Sheng Wang, Abstract: The ability to understand and engineer biological systems depends on efficiently manipulating and interpreting molecular information. Design-Build-Test-Learn (DBTL) cycles remain limited by bottlenecks in both experimental workflows and computational analysis. This thesis addresses these complementary challenges through both physical laboratory automation and machine learning methods for interpreting nanopore sequencing signals from chemically diverse biopolymers.
First, I present work on digital microfluidic automation using the PurpleDrop platform, enabling programmable droplet manipulation for applications including DNA data storage and aptamer discovery. This work demonstrates the potential of integrated hardware-software systems for automated experimentation while highlighting challenges in…
Thursday, June 4, 2026, 1:00 PM – 2:00 PM.
Instruction Ends - Spring 2026
Dates of Instruction
Instruction ends.
Event interval: Single day event. Year: 2026. Quarter: Spring. Event Types: Academics.
Friday, June 5, 2026.
For more info visit www.washington.edu. Final Examinations - Spring 2026
Dates of Instruction
Week of final examinations for spring quarter.
Event interval: Ongoing event. Year: 2026. Quarter: Spring. Event Types: Academics.
Saturday, June 6, 2026 – Friday, June 12, 2026.
For more info visit www.washington.edu. Information session: Professional Master's in Computer Science
Click here to register for an upcoming session!
The Allen School’s Professional Master’s Program (PMP) is a part-time program designed for software professionals in the Puget Sound region interested in acquiring critical skills to move into positions and projects of greater responsibility and impact. Courses meet one weekday evening per week and are taught in-person on the UW Seattle campus.
Online information sessions are a low-barrier opportunity for prospective students to learn more about the PMP and ask questions directly to program staff. We will share information about PMP courses and learning outcomes and an overview of the application process, including tips for preparing your materials. We hope you will join us!
Event interval: Single day event. Online Meeting Link: https://washington.zoom.us/meeting/register/s-JzzqWOTAyCx4f1Huaepg. Accessibility Contact: masters@cs.washington.edu. Event Types: Academics. Information Sessions.
Monday, June 8, 2026, 5:00 PM – 6:00 PM.
Zoom.
For more info visit www.cs.washington.edu. Ph.D. Dissertation Defense Talk: Application Defined Networks
Speaker: Xiangfeng Zhu, Advisors: Arvind Krishnamurthy, Ratul Mahajan, Supervisory Committee: Arvind Krishnamurthy (Chair), Ratul Mahajan (Chair), Akshay Gadre (GSR, Electrical and Computer Engineering), Stephanie Wang, Danyang Zhuo (Duke), Abstract: Modern microservice applications turn in-process calls into RPCs that traverse complex stacks for delivery, security, routing, and observability. Today’s stacks rely on general-purpose protocols and out-of-process proxies, which repeatedly parse, buffer, and reconstruct messages at each hop. This “RPC tax” can more than double latency and CPU consumption.
This talk presents Application Defined Networks, a compiler-driven approach that specifies application networks declaratively and synthesizes optimized, application-specific communication stacks. I will discuss MeshInsight for explaining service mesh overhead, AppNet for compiling network functions into optimized deployments, and FlatRPC, which co-designs message layout, delivery semantics, and in-network…
Tuesday, June 9, 2026, 3:00 PM – 4:00 PM.
Ph.D. Dissertation Defense Talk: Beyond Shape: Construction-Aware Languages for Design-for-Fabrication
Speaker: Amy Zhu, Advisors: Adriana Schulz, Zachary Tatlock, Supervisory Committee: Adriana Schulz (Chair), Zachary Tatlock (Chair), Afroditi Psarra (GSR, Digital Arts and Experimental Media), GILBERT L BERNSTEIN, Abstract TBA.
Thursday, June 11, 2026, 2:00 PM – 3:00 PM.
Quarter Break - Summer 2026
Dates of Instruction
Break between spring and summer quarters.
Event interval: Ongoing event. Year: 2026. Quarter: Summer. Event Types: Academics.
Saturday, June 13, 2026 – Sunday, June 21, 2026.
For more info visit www.washington.edu. Information Session: Graduate Certificate in Modern AI Methods
The graduate certificate in Modern Artificial Methods is a new program offered by the Paul G. Allen School of Computer Science & Engineering at the University of Washington. The work-compatible, one-year program is designed to support recent graduates and industry professionals in using, implementing, and understanding in-depth artificial intelligence and machine learning tools and applying them in the workplace. The certificate is designed for those with STEM or business backgrounds, with courses in prominent areas of AI, including computer vision and natural language processing. Classes meet in-person on the University of Washington campus in Seattle.
Modern AI Methods program highlights: Build knowledge and skills in core and emerging areas AI and ML for a rapidly-evolving workplace , Become more than a consumer of these technologies: understand how they work, their advantages, and their limitations , Connect with a cohort of local professionals in STEM while developing marketable skills , Learn from…
Event interval: Single day event. Online Meeting Link: https://www.cs.washington.edu/academics/graduate/certificate-modern-ai/program-overview/information-sessions/. Accessibility Contact: Taylor Kessler Faulkner, cert-modern-ai@cs.washington.edu. Event Types: Academics. Information Sessions.
Monday, June 15, 2026, 5:00 PM – 6:00 PM.
Zoom.
For more info visit www.cs.washington.edu. Juneteenth
Holidays
No classes. Most University offices and buildings are closed. Check with specific offices to confirm.
Event interval: Single day event. Year: 2026. Quarter: Summer. Event Types: Academics.
Friday, June 19, 2026.
For more info visit www.washington.edu. Instruction Begins - Summer 2026 - Full and A-term
Dates of Instruction
Instruction begins.
Event interval: Single day event. Year: 2026. Quarter: Summer. Event Types: Academics.
Monday, June 22, 2026.
For more info visit www.washington.edu. Information session: Professional Master's in Computer Science
Click here to register for an upcoming session!
The Allen School’s Professional Master’s Program (PMP) is a part-time program designed for software professionals in the Puget Sound region interested in acquiring critical skills to move into positions and projects of greater responsibility and impact. Courses meet one weekday evening per week and are taught in-person on the UW Seattle campus.
Online information sessions are a low-barrier opportunity for prospective students to learn more about the PMP and ask questions directly to program staff. We will share information about PMP courses and learning outcomes and an overview of the application process, including tips for preparing your materials. We hope you will join us!
Event interval: Single day event. Online Meeting Link: https://washington.zoom.us/meeting/register/s-JzzqWOTAyCx4f1Huaepg. Accessibility Contact: masters@cs.washington.edu. Event Types: Academics. Information Sessions.
Monday, June 22, 2026, 12:00 PM – 1:00 PM.
Zoom.
For more info visit www.cs.washington.edu. Information Session: Graduate Certificate in Modern AI Methods
The graduate certificate in Modern Artificial Methods is a new program offered by the Paul G. Allen School of Computer Science & Engineering at the University of Washington. The work-compatible, one-year program is designed to support recent graduates and industry professionals in using, implementing, and understanding in-depth artificial intelligence and machine learning tools and applying them in the workplace. The certificate is designed for those with STEM or business backgrounds, with courses in prominent areas of AI, including computer vision and natural language processing. Classes meet in-person on the University of Washington campus in Seattle.
Modern AI Methods program highlights: Build knowledge and skills in core and emerging areas AI and ML for a rapidly-evolving workplace , Become more than a consumer of these technologies: understand how they work, their advantages, and their limitations , Connect with a cohort of local professionals in STEM while developing marketable skills , Learn from…
Event interval: Single day event. Online Meeting Link: https://www.cs.washington.edu/academics/graduate/certificate-modern-ai/program-overview/information-sessions/. Accessibility Contact: Taylor Kessler Faulkner, cert-modern-ai@cs.washington.edu. Event Types: Academics. Information Sessions.
Monday, June 29, 2026, 12:00 PM – 1:00 PM.
Zoom.
For more info visit www.cs.washington.edu. Independence Day (Observed)
Holidays
No classes. Most University offices and buildings are closed. Check with specific offices to confirm.
Event interval: Single day event. Year: 2026. Quarter: Summer. Event Types: Academics.
Friday, July 3, 2026.
For more info visit www.washington.edu. Instruction Ends - Summer 2026 - A-term
Dates of Instruction
Instruction ends.
Event interval: Single day event. Year: 2026. Quarter: Summer. Event Types: Academics.
Wednesday, July 22, 2026.
For more info visit www.washington.edu. Instruction Begins - Summer 2026 - B-term
Dates of Instruction
Instruction begins.
Event interval: Single day event. Year: 2026. Quarter: Summer. Event Types: Academics.
Thursday, July 23, 2026.
For more info visit www.washington.edu. Ph.D. Dissertation Defense Talk: Towards Human-AI Symbiotic Spatial Perception
Speaker: Xia Su, Advisor: Jon E Froehlich, Supervisory Committee: JON E FROEHLICH (Chair), Jacob O. Wobbrock (GSR, Information School), Ranjay Krishna, Yang Zhang (UCLA), Abstract TBA.
Monday, August 10, 2026, 9:00 AM – 10:00 AM.
Instruction Ends - Summer 2026 - Full and B-term
Dates of Instruction
Instruction ends.
Event interval: Single day event. Year: 2026. Quarter: Summer. Event Types: Academics.
Friday, August 21, 2026.
For more info visit www.washington.edu. Quarter Break - Autumn 2026
Dates of Instruction
Break between summer and autumn quarters.
Event interval: Ongoing event. Year: 2026. Quarter: Autumn. Event Types: Academics.
Saturday, August 22, 2026 – Tuesday, September 29, 2026.
For more info visit www.washington.edu.