Rebecca Wright, the director of Barnard’s CS program, is a recipient of the 2019 Distinguished Service Award for her 11-year leadership of DIMACS, particularly in continuing and expanding the research and educational missions of DIMACS, for promoting diversity in computer science, and for using her expertise in privacy and security to help shape public policy on a national level.
Jana’s proposal aims to improve security, reliability and robustness of infrastructure software.
Ray seeks to improve the reliability of deep-learning applications used in safety-critical systems such as autonomous cars, medical diagnosis and malware detection.
CompilHer is an educational technology podcast with the aim of encouraging high school girls to pursue computer science in college and beyond. The podcast is produced by computer science majors Surbhi Lohia (BC ’19) and Madeline Wu (BC ’19).
The interviews consist of women from various backgrounds who are involved in computer science and technology. Topics covered range from how to get started with computer science, what it’s like to be a CS major, to how to land an internship or job in the tech industry. Check out the podcast at https://anchor.fm/compilher or on Spotify.
There will be a Launch Party on Friday, April 26th from 2PM to 4PM at the CSC Student Lounge (5th floor) in the Milstein Center on Barnard’s campus. Everyone is invited to come network and mingle with the podcast’s guests and other CS and technology clubs from the Columbia community. (Event details here.)
Below is a Q&A with one of the producers, Madeline Wu:
Why produce this type of podcast on women in CS?
We knew that interest in computer science drops most drastically for girls in high school and wanted to find a creative solution to target that pain point. We also noticed that most existing podcasts about women in tech are about women who are already in the tech field, and thus wouldn’t be as relatable for a high school audience with limited CS experience.
Is this a class assignment or a personal project?
This project was done as a senior social action project through the Athena Scholars Program at Barnard. We’re happy to have chosen a project that is both personal and impactful!
Will you be producing more episodes?
We are currently wrapping up Season 1 in New York City. After graduation, we’ll be located in Seattle and NYC so we have yet to determine the future of CompilHER but want to make it work!
How did you choose your interviewees?
We wanted to choose relatable, yet aspirational role models for our target demographic of high school girls. We decided to tap into our own community of CS at Columbia and interview senior CS women about their experiences. We also tried to encompass a diverse range of backgrounds, experiences, and interests within tech.
What was the most surprising thing you’ve learned from your interviews?
You are never too young or inexperienced to make an impact! By starting small and learning how to ask, our podcast guests have been able to accomplish so much and receive the support they needed along the way!
If there’s one takeaway you want people to have, what is it?
We want high school girls to know that CS is for everyone, and that there is a whole community of amazing women in tech out there who want to support each other!
Learn the science behind movie magic in this talk with Nora Wixom BC’13, a visual effects director at Lucasfilm. Nora will be talking about the technology used to create the computer graphics and visual effects of movies. Nora has worked as a technical director on films such as Jurassic World, Captain America: Civil War, and Star Wars: Episode 8. Nora graduated from Barnard in 2013 with a degree in Computer Science, with a focus on Vision and Graphics.
The computer science department adds two more faculty members. With research and teaching experience in algorithmic game theory, machine learning, and computational genomics, these new CS faculty are facilitating research and learning in their respective computer science fields.
Tim Roughgarden
Professor, Computer Science
Postdoctoral researcher, UC Berkeley, (2004)
PhD Computer Science, Cornell University, (2002)
MS Mathematics, Cornell University, (2002)
MS Computer Science, Stanford University (1998)
BS Applied Mathematics, Stanford University (1997)
Tim Roughgarden works on algorithmic game theory and on the design, analysis, applications, and limitations of algorithms. He comes to Columbia from Stanford University, where he was a computer science professor for 15 years.
Much of his recent research explores the intersection of computer science and economics, with applications ranging from network routing to online advertising to spectrum auctions. Looking at economics through the computer science lens motivated a number of new questions that had gone unasked, shared Roughgarden. Some topics he has worked on include the price of anarchy (that is, approximation guarantees for game-theoretic equilibria), auction and mechanism design theory, and social network analysis. Other subjects that are on his radar are contract theory and blockchains.
In the fall Roughgarden will teach a randomized algorithms course, as well as an undergrad class on the intersection of computer science and economics that will cover everything from cryptocurrencies, auctions for advertising, and routing protocols. He is toying with the idea of a more advanced class on the foundations of blockchain technology with a particular emphasis on game theory.
Check latest online casino directory with free no deposit casino promo codes
He is in the midst of building up his research group, and has one new PhD student and one new postdoc arriving in the fall.
David Knowles
Assistant Professor, Computer Science
Core Faculty Member, New York Genome Center
Postdoctoral researcher, Stanford University (2018)
PhD Machine Learning, University of Cambridge, (2012)
MSc Bioinformatics and Systems Biology, Imperial College London (2008)
MEng Engineering, University of Cambridge (2007)
David A Knowles holds a joint appointment as a core faculty member at the New York Genome Center.
Knowles’ interests lie in the interface between Bayesian inference and machine learning. While at his postdoc at Stanford a lot of the work he did applied Bayesian statistical techniques in computational genomics.
Part of his research looked at questions around how genetic differences between people influence their disease risk. One study examined how chemotherapy patients could be sensitive to treatment depending on their genetic makeup, in terms of cardiac side effects. Knowles is also interested in various neurological diseases – ALS, autism, Alzheimer’s – and how to study these diseases using patients’ genetic data and patient-derived model systems such as induced neurons and organoids.
“There is some work in this area, but I think it is particularly important in biology where you want to understand how much uncertainty there is in the model and in your predictions because (like with the chemotherapy and cardiac side effects research) we want to know how certain we are that the patient will have a cardiac side effect if given a chemotherapy drug,” shared Knowles.
In the fall he will teach a class on how modern machine learning is used in genomics. The Knowles Lab opened in January and is looking for grad and postdocs. Postdocs have the option to work in the wet lab and computational side.
Add to GMail