Distinguished Lecture Series
2015-2016 Speakers
Rastislav Bodik
Professor of Computer Science & Engineering
University of Washington
Program Synthesis
October 1, 2015
Abstract:
Program synthesis is the contemporary answer to automatic programming. Recognizing that programming is about gaining problem understanding, synthesis shifts focus from automation to intelligently assisting the programmer. Non-programmers benefit, too, because programs can model hardware, end-user intentions, educational exercises, and biological mechanisms, all within reach of synthesis. Synthesis is pragmatic about algorithmics of code generation. It searches a universe of candidates for a correct program, sidestepping the elusive domain theories needed for top-down program derivation. I will show examples of programmer interaction, explain how to scale algorithms to large systems, and outline problems in adopting synthesis outside computer science. I will conclude by inviting you to share your thoughts on what advances will lead us to a future in which computational thinking *is* programming.
Bio:
Rastislav Bodik is a Professor of Computer Science and Engineering at the University of Washington. He holds a Dipl.-Ing. degree in Computer Engineering from Technical University in Kosice, Slovakia (1992), and a PhD degree in Computer Science from the University of Pittsburgh (1999). He was a Professor at UC Berkeley until 2015 and Assistant Professor at the University of Wisconsin-Madison from 2000-2002. His recent work has focused on developing methods for algorithmic program synthesis by combining principles of programming languages, compilers, human-computer interaction, and formal methods. His group developed Sketch, the first algorithmic synthesizerfor imperative programs and applied synthesis to parallel document layout engines, ultra-low-power computer architectures, and executable biology. His previous work included static and dynamic program analysis, hardware support for program analysis, and dynamic compilation
Cynthia Dwork
Distinguished Scientist
Microsoft Research
Theory for Society
October 8, 2015
Abstract:
As technology reaches increasingly deeply into our everyday lives, changing the fabric of society woven by our interactions — with one another, with government, with the corporate world — design decisions have increasing impact on basic social values such as privacy, fairness, and protection from physical and emotional harm. Complexity of this type requires mathematically rigorous notions that allow us to quantify these goods and their loss, to explore fundamental trade offs and limitations, and to lay the theoretical groundwork for what can be achieved. This talk describes efforts of this type in two areas: privacy-preserving data analysis and fairness in classification, and touches on an agenda for future directions.
Bio:
Cynthia Dwork, Distinguished Scientist at Microsoft Research, is renowned for placing privacy preserving data analysis on a mathematically rigorous foundation. A cornerstone of this work is differential privacy, a strong privacy guarantee frequently permitting highly accurate data analysis. Dr. Dwork has also made seminal contributions in cryptography and distributed computing, and is a recipient of the Edsger W. Dijkstra Prize, recognizing some of her earliest work establishing the pillars on which every fault-tolerant system has been built for decades. She is a member of the National Academy of Sciences and the National Academy of Engineering, and a Fellow of the American Academy of Arts and Sciences.
Vipin Kumar
Regents Professor & William Norris Endowed Chair in Large Scale Computing
Department of Computer Science & Engineering
University of Minnesota
Understanding Global Change: Opportunities & Challenges for Data Driven Research
November 5, 2015
Abstract:
This talk will present an overview of research being done in a large interdisciplinary project on the development of novel data driven approaches that take advantage of the wealth of climate and ecosystem data now available from satellite and ground-based sensors, the observational record for atmospheric, oceanic, and terrestrial processes, and physics-based climate model simulations. These information-rich datasets offer huge potential for monitoring, understanding, and predicting the behavior of the Earth's ecosystem and for advancing the science of global change. This talk will discuss some of the challenges in analyzing such data sets and our early research results.
Bio:
Vipin Kumar is a Regents Professor at the University of Minnesota, where he holds the William Norris Endowed Chair in the Department of Computer Science and Engineering. Dr. Kumar's research interests include data mining, high-performance computing, and their applications in Climate/Ecosystems and Biomedical domains. He has authored over 300 research articles, and has coedited or coauthored 11 books including widely used text books ``Introduction to Data Mining'' and ``Introduction to Parallel Computing''. Dr. Kumar co-founded SIAM International Conference on Data Mining and served as a founding co-editor-in-chief of Journal of Statistical Analysis and Data Mining (an official journal of the American Statistical Association). Dr. Kumar is a Fellow of the ACM, IEEE and AAAS. Kumar's foundational research in data mining and its applications to scientific data was honored by the ACM SIGKDD 2012 Innovation Award, which is the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD).
Edward Adelson
John & Dorothy Wilson Professor Of Vision Science
Department Of Brain And Cognitive Sciences
Computer Science & Artificial Intelligence Lab
Massachusetts Institute Of Technology
Sensing Surfaces with GelSight
November 12, 2015
Abstract:
Our world is full of surfaces, and their fine scale geometry is important to how they look and feel for both robots and humans. I’ll describe a novel tactile sensor called GelSight that produces skin that is as soft as human skin but which has resolution hundreds of times better. It is based on an elastomer with special optical properties viewed by an embedded camera. With Gelsight we can build soft robot fingertips that measure shape, texture, shear, and slip with unprecedented sensitivity. The same technology can also be used measure 3D geometry at microscopic scales. Most optical techniques struggle when trying to measure the fine 3D geometry of specular or transparent materials (like metal or glass), but GelSight handles all materials with equal ease, delivering a pure shape-based signal. The technology is simple, and may be useful in many fields, such as dermatology, dentistry, industrial inspection, forensics, and biology.
Bio:
Professor Edward Adelson has authored numerous papers in the fields of human perception, computer vision, image processing, computer graphics, and computational photography. Recently he has been working on artificial touch sensing, with application to robotics and microscale 3D measurement. His honours include The Rank Prize in Opto-electronics, the Adolph Lomb Medal, two IEEE “test of time” awards in computer vision, and election to the NAS.