Colloquia Series: Ryan Baker Series: Ryan Baker2018-01-19T06:00:00Z11 a.m.Lopata Hall, Room 101<p style="text-align: center;"><strong>Towards Development of Better Real-Time Sensor-Free Detectors of Student Affect</strong></p><p style="text-align: center;"><strong>Dr. Ryan Baker</strong></p><p style="text-align: center;">Associate Professor and Director of the Penn Center for Learning Analytics</p><p style="text-align: center;">University of Pennsylvania </p><p><strong>Abstract</strong></p><p><strong></strong>Over the last several years, my group has worked to develop sensor-free detectors of affect for a variety of online learning platforms, in times in partnership with research groups who also work using physical sensor data. In this talk, I will discuss our work to improve the speed of detector development and the quality of the resultant detectors, from our early work to develop the BROMP protocol and HART handheld app, to our more recent work to leverage deep learning. I will also briefly review the uses that we have found for our detectors, both in basic research on affect and engagement, and through embedding them into affect-sensitive interventions.</p><p><strong>Biography</strong></p><p>Ryan Baker is Associate Professor at the University of Pennsylvania, and Director of the Penn Center for Learning Analytics. His lab conducts research on engagement and robust learning within online and blended learning, seeking to find actionable indicators that can be used today but which predict future student outcomes. Baker has developed models that can automatically detect student engagement in over a dozen online learning environments, and has led the development of an observational protocol and app for field observation of student engagement that has been used by over 150 researchers in 4 countries. He was the founding president of the International Educational Data Mining Society, is currently serving as Associate Editor of two journals, has taught four MOOC instances, and was the first technical director of the Pittsburgh Science of Learning Center DataShop, the world's largest public repository for data on the interactions between learners and online learning environments. Baker has co-authored published papers with over 250 colleagues.<br/></p>
Mentor Collective Launch for Sophomores Collective Launch for Sophomores2018-01-25T06:00:00Z5:30 p.m.Lopata Gallery and Lopata Hall, Room 101<p><strong>​From Associate Dean Chris Kroeger: </strong>"We have partnered with an external group called <a href="/current-students/outside-classroom/Pages/mentor-collective.aspx">Mentor Collective</a>, which will help match our current students with WashU engineering alums. Our alums are eager to share their practical real-world experiences with our students. We believe their insights and advice can help our students better prepare for life after graduation. Please join Dean Bobick and our engineering alums to learn more information about the program while eating some free pizza." <a href="" style="background-color: #ffffff;">>> Register to attend the Launch Event (Free Pizza!)</a></p><p><strong>If you cannot attend this event, </strong>please sign up via <a href="" style="background-color: #ffffff;">>> Mentor Collective Registration</a>.<br/></p>Melanie Osborn,
Colloquia Series: Rahul Mangharam Series: Rahul Mangharam2018-01-26T06:00:00Z11 a.m.Lopata Hall, Room 101<p>​</p><p style="text-align: center;"><strong>Two Challenge Problems with Intelligent Physical Systems</strong></p><p><strong>Abstract</strong></p><p><strong></strong>This two-part talk describes opportunities at the intersection of machine learning, control systems and the use of formal methods for a new generation of safe and scalable Intelligent Physical Systems.</p><p><strong><em>1. Energy Systems: Bridging Machine Learning and Control Systems for Volatile Energy Markets</em></strong></p><p>In January 2014, the east coast (PJM) electricity grid experienced an increase in the price of electricity from $31/MWh to $2,680/MWh MWh - an 83x increase in 5mins. Demand response (DR) is becoming increasingly important as the volatility on the grid continues to increase. Current DR approaches are predominantly manual and rule-based or involve deriving first principles based models which are extremely cost and time prohibitive to build. To this end, we develop data-driven approaches that bridge machine learning and controls for volatile energy markets. Specifically, we present data-driven methods (1) for optimal experiment design of functional tests to learn dynamics of a real building subject to stringent operational constraints, (2) to synthesize control-oriented models for receding horizon control, and (3) to continuously improve the learned model in closed-loop with a real-time controller. Our algorithms generate predictive models using Random Forests and Gaussian Processes - where we can not only predict the state of the building but also generate control strategies with high confidence using only historical weather, schedule, set-points and electricity consumption data. We call this approach Data Predictive Control (DPC). We show that, for a realistic building model, control strategies generated by DPC are remarkably similar to Model Predictive Control (MPC), while being scalable, unlike MPC.</p><p><strong><em>2. Autonomous Systems: A Driver's License Test for Driverless Vehicles</em></strong></p><p>Autonomous vehicles (AVs) have already driven millions of miles on public roads, but even the simplest maneuvers such as a lane change or vehicle overtake have not been certified for safety. Current methodologies for testing and verification of Advanced Driver Assistance Systems (ADAS) such as Adaptive Cruise Control cannot be directly applied to determine AV safety as the AV actively makes decisions using its perception, planning and control systems for both longitudinal and lateral motion. These systems increasingly use machine learning for which it is fundamentally hard to derive safety guarantees across a range of driving scenarios and environmental conditions. New approaches are needed to bound and minimize the risk of AVs to assure the public, determine liability and insurance pricing and ensure the long term growth of the domain.</p><p>So what type of evidence should we require before giving a driver's license to an autonomous vehicle? I will describe our research in the design of an autonomous vehicle computer-aided design toolchain, which captures formal descriptions of driving scenarios in order to develop an AV safety case. Rather than focus on a particular component of the AV, like adaptive cruise control, the toolchain models the end-to-end dynamics of the AV in a formal way suitable for testing and verification.</p><p><strong>Biography</strong></p><p>Rahul is an Associate Professor in the Dept. of Electrical & Systems Engineering and Dept. of Computer & Information Science at the University of Pennsylvania. His interests are in cyber-physical systems at the intersection of formal methods, machine learning and controls. He is the Penn Director for the Department of Transportation's $14MM Mobility21 University Transportation Center. He also directs Penn's Embedded Systems Masters Program. </p><p>Rahul received the 2016 US Presidential Early Career Award (PECASE) from President Obama for his work on Medical Cyber-Physical Systems. He also received the 2016 Department of Energy's CLEANTECH Prize (Regional), the 2014 IEEE Benjamin Franklin Key Award, 2013 NSF CAREER Award, 2012 Intel Early Faculty Career Award and was selected by the National Academy of Engineering for the 2012 US Frontiers of Engineering. He was the Stephen J. Angelo Assistant Professor from 2008-2013. He received his Ph.D. in Electrical & Computer Engineering from Carnegie Mellon University where he also received his MS and BS in 2007, 2002 and 2000 respectively.<br/></p>
Cybersecurity Graduate Programs Information Session Graduate Programs Information Session2018-01-30T06:00:00ZTBA<p><a href="/Programs/Pages/cybersecurity.aspx">>> Cybersecurity Programs​</a></p>
Skandalaris Center for Entrepreneurship Summer Internship Applications Due Center for Entrepreneurship Summer Internship Applications Due2018-02-09T06:00:00Z<p>Open to all undergraduate students from all majors, the <a href="">Skandalaris</a> summer internship is a good opportunity for students interested in entrepreneurship and innovation.</p><p style="color: #212121; font-family: wf_segoe-ui_normal, "segoe ui", "segoe wp", tahoma, arial, sans-serif, serif, emojifont; font-size: 15px;"></p><p>Through off-campus experiences, interns will hear from speakers who are leaders in their industry, including experienced entrepreneurs, venture capitalists, and campus partners and go on site visits to entrepreneurial organizations and neighborhoods. This includes visiting the city’s interesting and diverse, though sometimes economically challenging, neighborhoods. Locations may include co-working spaces, incubators, taking a tour, or spending time with a local entrepreneur working to address the challenges and promote the opportunities in the neighborhood.</p>Skandalaris Center,
Colloquia Series: Baba Vemuri Series: Baba Vemuri2018-02-09T06:00:00Z11 a.m.Lopata Hall, Room 101<p>​Event details coming soon.<br/></p>
Cybersecurity Graduate Programs Information Session for BS/MS Candidates Graduate Programs Information Session for BS/MS Candidates2018-02-14T06:00:00Znoon2 p.m.Lopata Hall, Room
Center for Engineering MechanoBiology Summer Research Program Deadline for Engineering MechanoBiology Summer Research Program Deadline2018-02-16T06:00:00Z<p><a href="">​The Center for Engineering MechanoBiology (CEMB)</a> 2018 Summer Research Experience for Undergraduates Program is now accepting applications for students to pursue innovative research with a National Science Foundation Science and Technology Center.<br/></p><p><strong>Program Dates: </strong>May 29 – August 3, 2018<br/><strong>Deadline:</strong> February 16, 2018<br/> <strong>Apply online</strong>: <a href=""></a> </p><p><strong>Research areas: </strong>molecular biology; cell and tissue mechanics in plants and animals; bioengineering; biochemistry; biophysics; computational biology; biomedical devices; nanoscale science and engineering<br/></p><p><strong>Locations:</strong> University of Pennsylvania or Washington University in St. Louis<br/><br/> <strong>Benefits:</strong> </p><ul><li>Competitive Stipend<br/></li><li>Summer Housing<br/></li><li>Travel assistance (if eligible)<br/></li><li>Social Activities<br/></li><li>Learn from leading scientists<br/></li><li>Meet other motivated students from throughout the U.S.<br/></li></ul> Patience Graybill,
Cybersecurity Graduate Programs Information Session Graduate Programs Information
Cybersecurity Graduate Programs Info Session via Facebook Live Graduate Programs Info Session via Facebook Live2018-02-21T06:00:00Z1 p.m.1:30 p.m.
Colloquia Series: Xiaofeng Wang Series: Xiaofeng Wang2018-02-23T06:00:00Z11 a.m.Lopata Hall, Room 101<p>​Event details coming soon.<br/></p>
PhD Visit Day Visit Day2018-03-02T06:00:00ZGraduate Student Services,