News & Events
Join Williams CS alumni Mary Imevbore ‘18 and Noah Grumman ‘16, PillPack software engineers, for an informational session or the CS Colloquium talk to learn more about opportunities with this company.
There will be snacks and swag, and students who attend one or more of these events may be invited to an on campus interview!
Thursday, October 11, Schow 030A @ 7:30pm
Info Session about life at PillPack
Friday, October 12; TCL 123 (Wege) @ 2:35pm
Computer Science Colloquium, “Engineering at a High Growth Startup: the (sometimes counterintuitive) things that we’ve learned in our time at a startup and wish we had known as undergraduates.” Colloquium credit for attending this event.
“Mapping the World with Deep Learning” – Facebook Tech Talk by Derrick Bonafilia ’17, Yitong Tseo ’17, Sam Blackshear ’10, and Baoxiang Yiang.
Satellites today are capable of capturing geo-referenced imagery of almost the entire globe at resolutions ups to 50cm per pixel. Using this imagery, things like buildings and roads can be located, usually within cm to meters of their actual location. However, this imagery is a massive dataset and it would take many lifetimes to map it all out by hand. Learn how Facebook is leveraging deep learning to massively speed up the process, and how we’re working with partners like CIESIN, the Bill and Melinda Gates Foundation, Humanitarian OpenStreetMap and the Red Cross to use this data for humanitarian efforts and to get it widely and freely available to anyone looking to make the world a better place.
Thursday, April 26 @ 8:00pm; Wege Auditorium (TCL 123)
“Algorithmic Magic: Behind the Scenes of Modern Computer Science”
Algorithmic advances have been responsible for some of the most remarkable applications of computation today, from search engines to machine learning to error-correcting codes, cryptography and scientific computing. Yet, even now, some of the most basic algorithmic questions remain unanswered, and among these are open problems with far-reaching implications for computer security and beyond.
In this talk, I will describe how computer scientists identify and abstract these key problems from a diversity of computing applications, and how some of these puzzles encapsulate deep questions about the nature of computation itself.
I’ll illustrate how computer scientists come up with fast algorithms, and what sorts of ideas are used, by focusing on the prominent problem of multiplying matrices. Many researchers have contributed to a decades-long race to find an optimal algorithm for this problem, which lies at the core of many applications. I’ll describe the surprising and clever ideas in play, and a promising new approach developed by myself and collaborators, that may have a chance to finally yield an optimal algorithm. No mathematical background will be assumed.
Dr. Umans received his undergraduate degree in Computer Science and Mathematics from Williams College and his Ph.D. in Computer Science from Berkeley in 2000. After spending two years as a postdoc in the Theory Group at Microsoft Research, he joined the Computer Science faculty at Caltech in 2002, where he is currently Professor of Computer Science. His research interests are in theoretical computer science, especially computational complexity, randomness in computation, and algebraic complexity and algorithms. He serves as an editor of the Journal of Computer and System Sciences, Algorithmica, Computational Complexity, ACM Transactions on Computation Theory, and Theory of Computing. He is a member of the scientific board of the Electronic Colloquium on Computational Complexity and the moderator for the Computational Complexity section of the arXiv. Dr. Umans is the recipient of an NSF CAREER award, an Alfred P. Sloan Research Fellowship, and a Simons Foundation Investigator award, as well as several best-paper and teaching awards.
Friday, April 20
Wege Auditorium (TCL 123) @ 2:35pm
Monday, October 30
TBL 211 @ 9:00pm
Lauren Yu ’16 presented “Predicting Expressive Bow Controls for Violin and Viola,” co-authored with Prof. Andrea Danyluk, at the 6th International Conference on Computational Intelligence in Music, Sound, Art, and Design. The conference took place in April in Amsterdam, The Netherlands. The paper, which was based on Lauren’s Honors Thesis, was honored as a Best Paper Candidate at the conference.
Dan Barowy is a PhD candidate in the PLASMA Lab at the University of Massachusetts Amherst, supervised by Professor Emery Berger. His research interests are in new language abstractions, end user programming, and new debugging techniques, particularly for spreadsheets and with crowdsourcing. Daniel regularly collaborates with industry researchers, and has ongoing collaborations at Microsoft Research and IBM T.J. Watson. His work has appeared at PL (PLDI and OOPSLA) and HCI (CHI) venues and was selected as a Research Highlight for the June 2016 issue of Communications of the ACM. Daniel’s work on FlashRelate was also awarded PLDI 2015’s top honor for software artifacts, the Distinguished Artifact Award. Nearly all of Daniel’s research is available as open-source software (http://people.cs.umass.edu/~dbarowy).
A little Q & A with Dan:
How did you become interested in CS? Or in your area of study specifically?
I’ve dabbled in programming as long as I can remember, but I did not find my way into CS until after college. One of my hobbies at the time was brewing beer. Like many homebrewers, I wanted to control every aspect of the process, and that required doing a lot of calculations. I thought “a computer should be doing this,” so I set out to write a program to handle the details for me. But the program did not behave the way I expected. To my horror, I found that when I added 0.1 and 0.2 on a computer, the result was not 0.3. At some point, I discovered a paper titled “What Every Computer Scientist Should Know About Floating-Point Arithmetic” by David Goldberg that explained the problem. I had never considered before that the way one represents a number in a computer might affect the way you can use it. After that I was hooked.
What will you bring to Williams Computer Science Department?
The thing that drives all of my research and teaching is the idea that computing should be available to everyone. Computational devices are ubiquitous now. Nearly everyone has a cellphone. But unlocking the power of those machines requires years of dedicated effort studying programming. Such an undertaking is out of reach for most people. I want to enable people to program a computer without all that studying.
Radically simplifying programming tasks usually involves a tradeoff, though: the computer needs to be more autonomous. Much of my work involves trying to infer what you, as a computer user, want to do without having to pester you with all of the details. For example, you might want to transform some data in a spreadsheet. Usually, you have a to write a program to do that. I designed a tool–think of it as a kind of computerized programming buddy–that writes that program for you. All you need to do is to give it examples of what you want. This kind of work requires that we blend programming language research with AI, machine learning, and human interface design. It’s a lot of fun because few people have explored these combinations before.
I hope I can share my enthusiasm about these topics with Williams students. I find that interacting with undergraduates is energizing, because they often pose profound questions that longtime computer scientists unconsciously suppress, like “Is this good?” or “Why do we do this?” Sometimes I don’t have a good answer! Yet these questions are central to my research. Before coming to Williams, I crossed paths with many exceptional Williams CS alums, and their positive sentiments toward the college played an important role in my decision to pursue a career here. I am looking forward to working with students who might want to parlay questions like these into scholarly activities.
What are some of your favorite things?
My wife and I bonded over a shared interest in hiking and backpacking. We hiked the entire Appalachian Trail together after college, and we both love to explore new outdoor places together. She told me that living someplace with mountains was “non-negotiable.” Fortunately, I love mountains too, so the decision to work at Williams was easy to make because it is totally surrounded by mountains.
I also love good bread, and one of the activities I do to relax is baking. People who can bake bread that is both delicious and beautiful really amaze me. It seems that I am only able to accomplish one of those attributes at any given time, despite years of effort. But I will happily eat other people’s beautiful creations.
Finally, I would be remiss if I did not mention that I am an avid coffee drinker.
Are you excited about any specific aspect of living in the Berkshires or working at Williams?
I grew up in small towns. I am attracted to the idea that I can live someplace where people know and greet me when they see me. Nearly everyone I’ve spoken to at Williams says that this is one of the things that they like best about Williamstown. In fact, during my interview at Williams, one of the faculty took me to dinner at The Log, and during this, a number of people stopped by to say hello. It strikes me as a good fit.
Finally, if one has the opportunity to spend their life doing good and important work, I think they have an obligation to do so. The faculty at Williams College thinks broadly about computer science and its impact on the world, and the mission of the college is to instill such values in its students. This fact deeply resonates with me. I am thrilled to be joining the faculty at Williams, because I think that teaching and research are among some of the most important things that a person can do.