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Industrial Panel 2024

Ken Chan, Stephen Lewis Bianamara, Harishchandra Ramadas, Jordan Weaver, Ursula Whitcher
Thursday, April 25, 2024 - 4:30pm to 6:00pm
PDL C-38

In a recent AMS Survey of New Doctorate Recipients, 33 percent accept positions in government, business and industry.  What are these jobs like?  How do you find them?  And, are they interesting jobs?  To provide insight into these questions, we will hold our annual Industrial Panel Discussion featuring four UW alums from the PhD program.  The speakers will be  Ken Chan, Stephen Lewis Bianamara, Harishchandra Ramadas, Jordan Weaver, Ursula Whitcher.   All are invited to attend!

Harish Ramadas graduated with a PhD in mathematics from the University of Washington in 2017, where his research focus was probability and discrete optimization. He then spent a little over 3 years working as a data scientist at Palantir while based in Palo Alto, CA, where he worked closely with customers in diverse fields including cancer research, aerospace, energy and public health. In 2020, he joined the machine learning team at GRAIL, a biotech company in Menlo Park, CA, where he develops models for detecting multiple types of cancer early using cell-free DNA in blood plasma.

Ursula Whitcher is an Associate Editor at Mathematical Reviews (MathSciNet), a division of the American Mathematical Society. In addition to editing math reviews in areas from algebraic geometry to the history of mathematics, Ursula is the editor of and a regular contributor to the AMS Feature Column. A past recipient of the Mathematical Association of America's Merten Hasse prize for exposition, Ursula volunteers as an editor for the MAA's American Mathematical Monthly and the Association for Women in Math's journal La Matematica, and has published poetry and short fiction in venues including Analog, Asimov's Science Fiction Magazine, and the Lambda-Award-nominated anthology Rosalind's Siblings. Prior to joining the AMS in 2016, Ursula received a PhD in algebraic geometry from the University of Washington in 2009, was a postdoc at Harvey Mudd College, and earned tenure from the University of Wisconsin-Eau Claire. 

Kenneth Chan is currently a Principal Data Scientist at Indeed, where he builds and maintains tools for data analytics and machine learning operations (MLOps). He earned his PhD at the University of New South Wales in Australia, and was a postdoc in mathematics at the University of Washington. When he is not working on MLOps, he makes time to continue research in noncommutative algebra.

Jordan Weaver is a recent graduate, having finished her PhD at UW last year. As a student, Jordan studied algebraic combinatorics with Sara Billey. During that time, she also completed UW's data science option and participated in two data science internships. For the last year, she has been a data scientist at Microsoft, specifically working on the ranker for Bing's image search results.

Stephen Bianamara (née Lewis) studied geometric measure theory under Prof. Toro, graduating in 2014. After a brief stint as a post-doc at UMN, Stephen moved back to Seattle and joined Panopto, a mid-stage startup focusing on educational Video Content Management. Stephen eventually built out and was the owner for in-video search, allowing students and teachers to search into the actual contents of videos rather than just associated metadata, and began building out a fledgling AI product suite including automatically identifying and labeling sections of the video ("Smart Chapters"). After Panopto sold, Stephen joined a pre-seed startup named EchoMark, an AI based information security company. Though it's a bit of a cliché in the startup world, Stephen's work can best be described there as "wearing many hats", where any given day might include learning from customers what their needs are, tuning AI models, designing robust and secure systems, or discovering a new combinatorial sequence (true!). Stephen is extremely grateful for his PhD studies, where he learned how to learn fast and independently, handle complex projects and ambiguity, and write technical explanations efficiently but precisely.

This talk will be hosted by Sara Billey and Alex Wang

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