Upcoming Department Events

To submit an event for consideration, or sign up a speaker, please see this page.
Friday, October 24, 2014 - 9:00am to 4:45pm
CITP event (Event Website)
Friend Center Convocation Room
(Hosted by: Center for Information and Technology Policy)

Web Privacy and Transparency Conference

[ View Event Abstract ]

Everything we do on the web is tracked and profiled. What types of data are companies collecting? Who are they trading it with? And how is this data used for personalizing our online experience and treating different users differently? What are the algorithms used for targeting ads, as well as prices, news recommendations, and so forth? A quickly emerging area of computer science research aims to bring transparency to privacy-impacting practices on the web via empirical measurement. This conference will discuss the state of the art in this field and the research agenda for the next few years as well as questions of policy — how should laws utilize the results of measurement, and what new laws do these studies suggest? Can self-regulation be effective, and how can web services work together with transparency researchers to foster a healthy public dialog?

Please RSVP on event website.

 

Monday, November 3, 2014 - 4:30pm to 5:30pm
CS Department Colloquium Series
Computer Science Small Auditorium (Room 105)
Host: Sebastian Seung

Machine Learning for Robots: Perception, Planning and Motor Control

Daniel Lee (University of Pennsylvania )
[ View Event Abstract ]
Daniel LeeMachines today excel at seemingly complex games such as chess and Jeopardy, yet still struggle with basic perceptual, planning, and motor tasks in the physical world.  What are the appropriate representations needed to execute and adapt robust behaviors in real-time?  I will present some examples of learning algorithms from my group that have been applied to robots for monocular visual odometry, high-dimensional trajectory planning, and legged locomotion. These algorithms employ a variety of techniques central to machine learning: dimensionality reduction, online learning, and reinforcement learning.  I will show and discuss applications of these algorithms to autonomous vehicles and humanoid robots.
Daniel Lee
 
 
 
 
 
 
 
 
 
 
 
 
Daniel Lee is the Evan C Thompson Term Chair, Raymond S. Markowitz Faculty Fellow, and Professor in the School of Engineering and Applied Science at the University of Pennsylvania. He received his B.A. summa cum laude in Physics from Harvard University in 1990 and his Ph.D. in Condensed Matter Physics from the Massachusetts Institute of Technology in 1995.  Before coming to Penn, he was a researcher at AT&T and Lucent Bell Laboratories in the Theoretical Physics and Biological Computation departments.  He is a Fellow of the IEEE and has received the National Science Foundation CAREER award and the University of Pennsylvania Lindback award for distinguished teaching. He was also a fellow of the Hebrew University Institute of Advanced Studies in Jerusalem, an affiliate of the Korea Advanced Institute of Science and Technology, and organized the US-Japan National Academy of Engineering Frontiers of Engineering symposium.  As director of the GRASP Robotics Laboratory and co-director of the CMU-Penn University Transportation Center, his group focuses on understanding general computational principles in biological systems, and on applying that knowledge to build autonomous systems.
Tuesday, November 4, 2014 - 10:00am to 5:00pm
CITP event (Event Website)
Friend Center Convocation Room
(Hosted by: Center for Information and Technology Policy)

Trusting Human Safety to Software: What Could Possibly Go Wrong?

[ View Event Abstract ]

The conference will focus on the need for affirmative, preventative measures to be put in place to prevent physical harm from code-based machines and systems. Planned topics include medical devices and automotive software.

 

Please RSVP on event website.