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Caltech Computes

Disrupting Science and Engineering with Computational Thinking

Saturday, Nov 12, 2016 8:00 am - 7:00 pm
Beckman Institute Auditorium

Join us for a day-long event that will explore the ways in which computational thinking is disrupting science and engineering, creating entirely new disciplines with "CS+X". From developing new paradigms for computation—quantum computing and DNA computing—to pushing the boundaries of machine learning and statistics in ways that transform fields like astronomy, chemistry, neuroscience, and biology, Caltech faculty are pioneering new disciplines at the interface of computer science, and science and engineering. 

Regular price $ 150.00


7:30- 8:30 a.m.

Check-in and continental breakfast

8:30 a.m.

Welcome and Opening Remarks

Lee Fisher (BS ’78)
Past President, Caltech Alumni Association (2015-16)


Caltech Computes
Adam Wierman
Professor of Computing and Mathematical Sciences;
Executive Officer for Computing and Mathematical Sciences;
Director, Information Science and Technology
Engineering and Applied Science

Adam Wierman is a founding member of the Rigorous Systems Research Group (RSRG) and maintains a popular blog called Rigor + Relevance. His research interests center around resource allocation and scheduling decisions in computer systems and services. He received the 2011 ACM SIGMETRICS Rising Star award, the 2014 IEEE Communications Society William R. Bennett Prize, and has been coauthor on papers that received of best paper awards at ACM SIGMETRICS, IEEE INFOCOM, IFIP Performance (twice), IEEE Green Computing Conference, IEEE Power & Energy Society General Meeting, and ACM GREENMETRICS.

Session I  9:00 – 10:45 a.m.

A System Composed of People and Machines for Collecting and Organizing Visual Information
Pietro Perona
Allen E. Puckett Professor of Electrical Engineering

Pietro Perona studies vision. He is interested in the engineering challenge of building machines that can see and in the scientific question on how brains compute useful information from images. At the moment his research group focusses on visual recognition and the visual perception of behavior. In collaboration with D. Anderson and M. Dickinson in the division of Biology he develops computer vision systems for measuring the behavior of laboratory animals. In the past his research has contributed to the theory of partial differential equations for image processing and boundary formation, and to modeling the early visual system's function.
Automatically Improving Automation Using Big Data
Yisong Yue
Assistant Professor, Computing and Mathematical Sciences

Yisong Yue is director of Decision, Optimization, and Learning at the California Institute of Technology (DOLCIT), which brings together experts in machine learning, optimization, applied math, statistics, control, robotics, and human-computer interaction. Its goal is to work on creating a world where intelligent systems seamlessly integrate learning and planning, as well as automatically balance computational and statistical tradeoffs in the underlying optimization problems. Yue was previously a research scientist at Disney Research and before that, he was a postdoctoral researcher in the Machine Learning Department and the iLab at Carnegie Mellon University.
Exploring Space in Cyberspace
George Djorgovski
Professor of Astronomy; Director, Center for Data Driven Discovery

George Djorgovski is an astrophysicist whose work encompassed a broad range of topics, from globular star clusters to the forming galaxies, quasars, supermassive black holes, and their evolution. He was one of the founders of the Virtual Observatory framework, the principal investigator of three digital sky surveys, and is currently working on the establishment of astroinformatics, a discipline bridging astronomy and applied computer science and information technology. His principal scientific focus has gradually shifted toward the ways in which information and computation technologies are changing the ways we do science and scholarship in general, and the emergence of a new scientific methodology for the computationally enabled, data rich science in the 21st century.

Session II  11:10 – 12:30 p.m.

Synthetic Biology
Programming Cellular Behavior Using DNA
Richard Murray (BS ’85)
Thomas E. and Doris Everhart Professor of Control and Dynamical Systems and Bioengineering; Engineering and Applied Science

Richard Murray is a leading expert in the field of control theory, an interdisciplinary branch of engineering and mathematics that deals with the behavior of dynamic systems and how they may be modified. Most recently, Murray has worked with computer scientists to explore the potential role of control theory in biological, biochemical, and biomolecular applications. His research group is primarily focused on synthetic biology, with additional focus on electromechanical systems and the software that sits on top of them. In July of this year, Murray was named to the Defense Innovation Advisory Board, a 15-member panel established to advise the Department of Defense that includes Reid Hoffman, co-founder of LinkedIn, and Marne Levine, chief operating officer of Instagram.
A Future Written by Molecular Programmers
Lulu Qian
Assistant Professor of Bioengineering Biology and Biological Engineering

Lulu Qian’s interests lie in engineering molecular systems with intelligent behavior: specifically, exploring the principles of molecular programs in nature with the end goal of recreating synthetic molecular programs that approach the complexity and sophistication of life itself. To this end, she works on designing and constructing nucleic-acid systems from scratch that exhibit programmable behaviors from the basic level—such as recognizing molecular events from the environment, processing information, making decisions, and taking actions—to the advanced level, such as learning and evolving.

Session III  1:30 – 3:00 p.m.

Topological Quantum Computation
Xie Chen
Assistant Professor of Theoretical Physics
Physics, Mathematics and Astronomy

Xie Chen is a condensed-matter theorist who examines quantum-mechanical systems with a large number of degrees of freedom. She is interested in learning how the constituent degrees of freedom cooperate with one another to realize amazing emergent phenomena. In particular, she is focused on the unconventional behavior, especially the topological properties, of quantum many-body systems in the strongly interacting regime.
Quantum Entanglement Through the Lens of Complexity Theory and Cryptography
Thomas Vidick
Assistant Professor of Computing and Mathematical Sciences
Engineering and Applied Science

Thomas Vidick performs research at the boundary of computer science and quantum information theory. A lot of his work revolves around the computational aspects of quantum entanglement, a key "spooky" phenomenon in quantum mechanics. He likes to explore the properties of entanglement by asking questions: how can entanglement be used? What consequences can it have in complexity theory? Can it be harnessed to develop new secure schemes for cryptography?

Vidick's work in cryptography considers the challenges of developing cryptosystems, and more generally network protocols, that rely on the use of quantum devices (for improved efficiency, or security) but whose correctness can be certified without the need to rely on the trustworthiness of the quantum devices.

Session IV  3:30 – 5:30 p.m.

Algorithms in Economics
Federico Echenique
Allen and Lenabelle Davis Professor of Economics;
Executive Officer for the Social Sciences
Humanities and Social Sciences

Federico Echenique studies economic models of agents and markets to understand and determine their testable implications and the relationships between different theoretical constructs. In particular, he's investigating models of individual decision-making, of markets, and of other economic institutions. Echenique conducts research at the intersection of economics and computer science, in particular studying algorithmic solution to centralized markets. Examples of such markets are the assignment of medical school graduates to hospitals, and children to schools. Echenique's research also seeks to understand the computational assumptions and requirements behind many of the mathematical models used by economists.
Computational Design of Next-Generation Battery Electrolytes
Tom Miller
Professor of Chemistry

Tom Miller is an expert in the simulation and modeling of chemical and biological systems—with focus on solar-energy conversion, enzyme catalysis, membrane protein expression, and the design of improved battery materials. A central challenge in this effort is to understand molecular processes that span vastly different timescales and lengthscales. Miller is thus developing new strategies to leverage massively parallel computer architectures for the analysis of complex molecular systems. He is the recipient of numerous awards, including the Sloan Research Fellowship, the 2015 American Chemical Society Early-Career Award in Theoretical Chemistry, and the Associated Students of Caltech Teaching Award.
Greening the Grid through Optimization and Control
Steven Low
Professor of Computer Science and Electrical Engineering

Steven Low’s research is deeply involved with information and energy infrastructure, which have completely changed the way we live and work since their overlapping inceptions about 130 years ago. Research from his group is accelerating more than 1 TB of Internet traffic every second. While information infrastructure led to the Internet in the past few decades, the power network is only starting to undergo a drastic change on the order of magnitude of the information revolution that produced billion-dollar players like Google and Facebook. Low is developing technologies to help understand and guide this historic transformation. His group has pioneered a new computational approach to optimize power system operations, which was recently recognized by an award from the IEEE Power & Energy Society. His research on the smart grid starts by assuming that there will be a lot of renewables and distributed energy resources that are intelligent and strategic. Then he asks, ‘What are the new fundamental engineering and economic challenges that will arise?’
Schrödinger's Smoke
Peter Schröder
Shaler Arthur Hanisch Professor of Computer Science
and Applied and Computational Mathematics
Engineering and Applied Science

Peter Schröder’s research is in computer graphics, more specifically in geometric and physical modeling as used from computer animation to engineering simulations. He emphasizes geometric structures underlying the mathematics and uses them to build robust and efficient numerical algorithms. In early work he developed wavelet methods for scalable computations before co-founding the field of geometry processing. Since then he has focused on “Discrete Differential Geometry,” an area which seeks to design methods in the discrete computational setting which are true to the same theorems that classical (smooth) differential geometry knows. Differential geometry being the lingua franca of modern physics and mathematics a discrete version facilitates the direct translation of physical laws, for example, into the discrete realm of finite computations. This for example allowed Schröder and his collaborators to find a new way to employ the mathematics of quantum physics to simulate large-scale fluid motion—from smoke gently rising from a flame to the concentrated vorticity of a twister—with groundbreaking realism. His pioneering contributions have been most recently recognized when he was elected Fellow of the ACM (Association for Computing Machinery).

Closing Reception and Cocktail Party
5:30 – 6:30 p.m.

Additional Details

Questions? Contact: events-reg@alumni.caltech.edu

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