<html><head><meta http-equiv="Content-Type" content="text/html charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class="">Hello all-<div class=""><br class=""></div><div class="">Reminder about this talk tomorrow by Dr. Shijia Pan who is a post-doc at CMU. CS402 at 12:30pm with pizza beforehand. </div><div class=""><br class=""></div><div class="">Please let me know if you’re interested in talking 1-1 with her — she still has a couple afternoon slots left in her schedule.</div><div class=""><br class=""></div><div class="">All the best,</div><div class="">Margaret</div><div class=""><br class=""><div class="">
<div style="color: rgb(0, 0, 0); letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div class=""><div class=""><div style="orphans: 2; widows: 2;" class="">Margaret Martonosi</div><div style="orphans: 2; widows: 2;" class="">H. T. Adams '35 Professor of Computer Science.</div><div style="orphans: 2; widows: 2;" class="">Director, Keller Center for Innovation in Engineering Education</div><div style="orphans: 2; widows: 2;" class="">Princeton University <span style="text-align: -webkit-auto;" class="">■ </span><span style="text-align: -webkit-auto;" class=""><a href="mailto:mrm@princeton.edu" class="">mrm@princeton.edu</a> </span><span style="text-align: -webkit-auto;" class="">■ </span><span style="text-align: -webkit-auto;" class=""><a href="http://www.princeton.edu/~mrm" class="">http://www.princeton.edu/~mrm</a></span></div></div></div><div class=""><span style="text-align: -webkit-auto;" class=""><br class=""></span></div><div class=""><br class=""></div></div><br class="Apple-interchange-newline"><br class="Apple-interchange-newline">
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<div><br class=""><blockquote type="cite" class=""><div class="">Begin forwarded message:</div><br class="Apple-interchange-newline"><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;" class=""><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif; color:rgba(0, 0, 0, 1.0);" class=""><b class="">From: </b></span><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif;" class="">"Emily Lawrence" <<a href="mailto:emilyl@cs.princeton.edu" class="">emilyl@CS.Princeton.EDU</a>><br class=""></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;" class=""><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif; color:rgba(0, 0, 0, 1.0);" class=""><b class="">Subject: </b></span><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif;" class=""><b class="">[talks] Seminar-Dr. Shijia Pan, Thursday, September 27</b><br class=""></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;" class=""><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif; color:rgba(0, 0, 0, 1.0);" class=""><b class="">Date: </b></span><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif;" class="">September 17, 2018 at 10:51:21 AM EDT<br class=""></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;" class=""><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif; color:rgba(0, 0, 0, 1.0);" class=""><b class="">To: </b></span><span style="font-family: -webkit-system-font, Helvetica Neue, Helvetica, sans-serif;" class=""><<a href="mailto:talks@lists.cs.princeton.edu" class="">talks@lists.cs.princeton.edu</a>><br class=""></span></div><br class=""><div class=""><div class="WordSection1" style="page: WordSection1; font-family: HelveticaNeue; font-size: 14px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px;"><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Seminar Speaker<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Dr. Shijia Pan from Carnegie Mellon University<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Thursday, September 27, 2018 - 12:30pm<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Computer Science - Room 402<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Host: Margaret Martonosi<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class=""> <o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">“Indoor Human Information Acquisition from Physical Vibrations”<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class=""> <o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Abstract:<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">The number of everyday smart devices (such as smart TV, Samsung SmartThings, Nest, Google<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Home) is projected to grow to the billions in the coming decade. The Cyber-Physical Systems or Internet<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">of Things systems that consist of these devices are used to obtain human information for various smart<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">building applications. Different sensing approaches have been explored, including vision-, sound-, RF-,<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">mobile-, and load-based methods, to obtain various indoor human information. From the system<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">perspective, general problems faced by these existing technologies are their sensing requirements (e.g.,<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">line-of-sight, high deployment density, carrying a device) and intrusiveness (e.g., privacy concerns).<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class=""><o:p class=""> </o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">My research focuses on non-intrusive indoor human information acquisition through ambient<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">structural vibration, which is referred to as ’structures as sensors’. People’s interaction with structures in<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">the ambient environment (e.g., floor, table, door) induces those structures to vibrate. By capturing and<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">analyzing the vibration response of structures, we can indirectly infer information about the people and<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">their actions that cause it. However, challenges remain. Due to the complexity of the physical world (in<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">this case, both structures and people), sensing data distributions can change significantly under different<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">sensing conditions. Therefore, from the data perspective, accurate information learning through a pure<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">data-driven approach requires a large amount of labeled data, which is costly and difficult if not<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">impossible to obtain in real-world sensing applications. My research addresses these challenges by<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">combining physical knowledge and data-driven approaches. Specifically, my system can robustly learn<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">human information from limited labeled data distributions by iteratively expanding the labeled dataset.<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">With insights into the relationship between changes of sensing data distributions and measurable physical<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">attributes, the iterative algorithm guides the expansion order by measured physical attributes to ensure a<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">high learning accuracy in each iteration.<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class=""> <o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Bio:<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Dr. Shijia Pan is a postdoctoral researcher at Carnegie Mellon University. She received her Bachelor's<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">degree in Computer Science and Technology from University of Science and Technology of China and<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">her Ph.D. degree in Electrical and Computer Engineering at Carnegie Mellon University. Her research<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">interests include cyber-physical systems, Internet-of-Things (IoT), and ubiquitous computing. She worked<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">in multiple disciplines and focused on indoor human information acquisition through ambient sensing.<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">She has published in both top-tier Computer Science ACM/IEEE conferences (IPSN, UbiComp) and<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">high-impact Civil Engineering journals (Journal of Sound and Vibration, Frontiers Built Environment).<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">She is the recipient of numerous awards and fellowships, including Rising Stars in EECS, Nick G.<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Vlahakis Graduate Fellowship, Google Anita Borg Scholarship, Best Poster Awards (SenSys, IPSN), Best<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Demo Award (Ubicomp), Best Presentation Award (SenSys Doctoral Colloquium), and Audience Choice<o:p class=""></o:p></span></div><div style="margin: 0in 0in 0.0001pt; font-size: 11pt; font-family: Calibri, sans-serif;" class=""><span style="" class="">Award (BuildSys) from ACM/IEEE conferences.</span><o:p class=""></o:p></div></div><span style="font-family: HelveticaNeue; font-size: 14px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-stroke-width: 0px; float: none; display: inline !important;" class="">_______________________________________________</span><br style="font-family: HelveticaNeue; 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