Wellesley CS Colloquium Series

Abstract


Bio
Andrew Chien is a Distinguished Professor of Computer Science and the Director of the CERES Center for Unstoppable Computing at the University of Chicago. He isalso the Editor-in-Chief of the ACM.

Abstract
The Laboratory Instrument Computer (LINC), created in the early 1960s at MIT, constituted a sea change from computing using large, off-line, remote, centrally-controlled computers to computers that were small, interactive and operated under the direct control of their individual users. The LINC revolutionized biomedical research, and was the gateway to personal computing. Mary Allen Wilkes was a member of the LINC development team. She will describe the dramatic transformation in biomedical research caused by the LINC, and its foreshadowing of the personal computers of today. She will also give a brief summary of the history of women in the computer field, and her experience in it in the 1960s. Ironically, the field may have been more open to women then than it is today.

Bio
Mary Allen Wilkes worked in the computer field for 11 years before turning to a career as a lawyer. As a computer programmer in the 1960s at MIT, she participated in the development of the LINC computer and wrote its system software, including its interactive operating system LAP6, one of the earliest such systems for a personal computer. Her work was recognized in Great Britain's National Museum of Computing's 2013 exhibition "Heroines of Computing" at Bletchley Park, and by the Heinz Nixdorf MuseumsForum in Paderborn, Germany, in its 2015-16 exhibition, Am Anfang war Ada: Frauen in der Computergeschichte (In the beginning was Ada: Women in Computer History). Wilkes is a graduate of Wellesley College and the Harvard Law School. She practiced law in the Boston area for over 35 years, including practice as a trial lawyer, an Assistant District Attorney for Middlesex County, an arbitrator for the American Arbitration Association, and an instructor in the Trial Advocacy Workshop at the Harvard Law School. She also served for eight years as a judge of the Annual Willem C. VIS International Commercial Arbitration Moot competition in Vienna, Austria, organized by Pace University Law School. Wilkes is the author of "Conversational Access to a 2048-Word Machine" about the LINC operating system (Comm. of the Association for Computing Machinery 13, 7, pp. 407–14, July 1970) and "Scroll Editing: an On-line Algorithm for Manipulating Long Character Strings," which describes the LAP6 document editing function (IEEE Trans. on Computers 19, 11, pp. 1009–15, November 1970).

Abstract
This talk with cover what going to graduate school is like for a PhD in Computer Science at an R1 institution. I will talk about my journey coming from CS at Wellesley to try to provide you more information to judge if a career in CS research may be a good fit for you too! In the second part of the talk, I’ll share my research on programming practices. My current focus is to use HCI and design methods to support individuals who do data science coding such as developing machine learning models or exploratory data analysis. Finally, I’ll cover some research opportunities for undergraduates that may interest you at my current institution (Carnegie Mellon University) and beyond.

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Mary Beth Kery (pronouns she/her) is a 4th year PhD student at the Human-Computer Interaction Institute at Carnegie Mellon University. She graduated with a BA in CS from Wellesley College in 2015. Portfolio of work at http://marybethkery.com/.

Abstract
Machine Learning is quickly becoming ubiquitous. It seems that everyone is either already applying it or wants to apply it. But what is machine learning exactly? Where is it being used? How can we separate the reality of machine learning’s promise from the hype? In this talk, I will introduce machine learning, describe some of its challenges – from scientific to social – and will then discuss work that my students (all undergraduates) and I have been approaching in areas as diverse as ecology and viola performance.

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Andrea Danyluk is a Mary A. and William Wirt Warren Professor of Computer Science at Williams College. Andrea is a member of CRA-W (the Computing Research Association on the Status of Women in Computing Research) and a co-director of CREU (Collaborative Research Experiences for Undergraduates) from 2009 to 2016.

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Ever wonder what happens to your checked bag when it goes into the bowels of the airport? Or what’s going on at a security checkpoint, and why? One-time Wellesley Computer Science Faculty member, Dr. Matthew Merzbacher, will talk about the history of explosives detection for aviation security and how computer science is used today. He will also share thoughts on how CS will be used going forward, career & internship opportunities with Smiths Detection, and discuss implications to civil liberties.

Bio
Matthew Merzbacher is the Director of Certification and Qualification at Smiths Detection.

Abstract
Automated decision-making — the use of predictive tools to assist in decision-making — is no longer the future. It's used to decide what your school districts might look like, where you go to college, whether you get loans for purchases, or even a job. Automated decision-making is used to decide whether police are deployed to your neighborhood, whether you're released on bail or not, what sentence you receive for a conviction, and whether you're released on parole.

We're now seeing the effects of automated decision-making at scale, and we're realizing that predictive methods, much like us humans, can be both accurate and wildly discriminatory. They mirror and amplify some of our biases while correcting for others. And they're far less transparent, especially when we use sophisticated tools from machine learning.

In this talk I'll lay out a fast growing research landscape in the area of fairness, accountabiltiy and transparency in decision-making. I'll also situate this discussion in a larger framework of philosophy, ethics and justice that affects and is affected by decision-by-algorithm.

Bio
Suresh Venkatasubramanian is a professor at the University of Utah. His background is in algorithms and computational geometry, as well as data mining and machine learning. His current research interests lie in algorithmic fairness, and more generally the problem of understanding and explaining the results of black box decision procedures. Suresh was the John and Marva Warnock Assistant Professor at the U, and has received a CAREER award from the NSF for his work in the geometry of probability, as well as a test-of-time award at ICDE 2017 for his work in privacy. His research on algorithmic fairness has received press coverage across North America and Europe, including NPR’s Science Friday, NBC, and CNN, as well as in other media outlets. He is a member of the Computing Coommunity Consortium Council of the CRA, a member of the board of the ACLU in Utah, and a member of New York City’s Failure to Appear Tool (FTA) Research Advisory Council.