When:
Thursday, November 13, 2025
5:00 PM - 6:00 PM CT
Where: Online
Audience: Post Docs/Docs - Graduate Students
Cost: Free
Contact:
Wynante R Charles
(847) 467-8174
wynante.charles@northwestern.edu
Group: Department of Computer Science (CS)
Category: Academic
Alumni Panel Announcement
Thursday, November 13th • 5:00 PM CST
We are excited to announce that three distinguished alumni will be joining us for an Alumni Panel on November 13th at 5:00 PM CST. This is a valuable opportunity for students to learn about research careers in industry, hear professional insights, and ask questions about transitioning beyond graduate school.
Panelists
Victor (PhD ’22)
Victor earned his PhD in Computer Science from Northwestern University in 2022, under the advisement of Prof. Larry Birnbaum. His research focused on large language models for task-oriented dialogue, specifically Conversational Recommender Systems. After completing two research internships during his PhD, he joined Adobe Research as a Research Scientist, where he continues developing AI assistants for Adobe products. His work supports components of Adobe’s AEP AI Assistant and CJA Intelligent Captions, and he has published in top venues including ICLR, ACL, EMNLP, CHI, UIST, and VIS.
Danilo Neves Ribeiro (PhD ’23)
Danilo is an Applied Scientist at Amazon AWS, where he designs innovative solutions for information retrieval, reasoning, language model agents, and enterprise-oriented conversational systems. He earned his PhD in Computer Science from Northwestern University in 2023 and brings over three years of AI/ML research and industry experience to his current work.
Ethan Manilow (PhD ’23)
Ethan Manilow is currently a Senior Research Scientist at Google DeepMind on the Magenta Team. He finished my PhD in Computer Science, working under Bryan Pardo in the Interactive Audio Lab at Northwestern University. During his PhD, he spent two years as a Student Researcher with Magenta, and prior to that, he spent a year and a half as a Student Researcher at MERL on the Speech and Audio Team. His research focuses on developing machine learning systems that can listen to and understand musical audio, aiming to create tools that better assist artists.
We hope to see you there!