CSE Colloquia Series: Victor Bahlhttps://engineering.wustl.edu/Events/Pages/CSE-Colloquia-Series-Victor-Bahl.aspx948CSE Colloquia Series: Victor Bahl2017-04-28T05:00:00Z11 a.m.Lopata Hall, Room 101<p style="text-align: center;">​<strong>Distributed Video Analytics the Perfect Edge Computing Application</strong><br/></p><p style="text-align: center;"><strong>Victor Bahl </strong></p><p style="text-align: center;">Director of the Mobility & Networking Research (MNR) Group</p><p style="text-align: center;">Microsoft Research<br/></p><p rtenodeid="21"><strong>Abstract</strong></p><p>The virtues of edge computing have been expounded in the research community but deployment has been slow.  Reflecting on this, we have been working on a compelling video analytics application for edge computing   Our motivation for pursuing this is based on the observation that cities worldwide have deployed millions of cameras for planning and security purposes. These cameras record images 24x7x365, mostly storing them for possible analysis at a later time.  The time lag between capturing and analyzing is a limitation of the technology and cost.  We believe that near real-time video analytics of live video streams is compelling for many important reasons and a perfect application of edge computing.   Unfortunately existing state-of-the-art video analytics systems are costly, insufficient, and often require manual intervention.  Large-scale automated video analytics is a grand challenge for the research community and for those of us who work on big data systems. Privacy regulations, bandwidth constraints and latency naturally lead us to design and develop systems where video is analyzed across both edge and cloud clusters.  In this talk I will describe our hybrid edge-cloud video analytics infrastructure and a pilot system that we are deploying in the City of Bellevue in Washington, USA.</p><p><strong>Biography</strong></p><p>Victor Bahl is a Distinguished Scientist and the Director of Mobility & Networking in Microsoft Research.  In this role he advises Microsoft's CEO and senior leadership team on long-term vision and strategy related to networked systems, mobile computing, wireless systems, cloud computing, and datacenter networking. He heads a high-powered group that executes on this vision through research, technology transfers to product groups, industry partnerships, and associated policy engagement with governments and research institutes around the world.  Dr. Bahl has published over 125 scientific papers, authored over 130 issued patents, and won numerous technical and leadership awards incl. a test-of-time award, three best paper awards, two awards from the United States FCC, distinguished service and lifetime technical achievement awards from ACM SIGMOBILE , distinguished alumni award and a IEEE outstanding leadership award.  Over the years he has developed seminal technologies including white space networking (2010), edge-based cloud computing (2009), mesh networking (2005), multi-radio wireless systems (2001), Wi-Fi hot-spots (2000), and indoor localization systems (1999).  Under his direction his group has had game changing impact on Microsoft's cloud computing infrastructures both in their datacenter and in wide-area networking.  Dr. Bahl is the founder of ACM SIGMOBILE, MobiSys and several other conferences. He is a Fellow of ACM, IEEE, and AAAS.<br/></p>
CSE Doctoral Student Seminar: Anthony Cabrera and James Orrhttps://engineering.wustl.edu/Events/Pages/CSE-Doctoral-Student-Seminar-Anthony-Cabrera-and-James-Orr.aspx913CSE Doctoral Student Seminar: Anthony Cabrera and James Orr2017-04-28T05:00:00Z12:30 p.m.2 p.m.Lopata Hall, Room 101<p><strong>"DIBS: A Benchmarking Suite for Data Integration, Wrangling, and Cleansing"​</strong></p><p><strong>Anthony Cabrera </strong><br rtenodeid="3"/>Adviser: Roger Chamberlain<br/></p><p>Analyzing big data is a task encountered across disciplines. Addressing the challenges inherent in dealing with big data necessitate solutions that cover its three defining properties: volume, variety, and velocity. However, what is less understood is the treatment of the data that must be completed even before any analysis can begin. Specifically, there is often a non-trivial amount of time and resources that are utilized to the end of retrieving and preprocessing big data. This problem, known collectively as data integration, is a term frequently used for the general problem of taking data in some initial form and transforming it into a desired form. Examples of this include the rearranging of fields, changing the form of expression of one or more fields, altering the boundary notation of records and/or fields, encrypting or decrypting records and/or fields, parsing non-record data and organizing it into a record-oriented form, etc. In this work, we present our progress in creating a benchmarking suite that characterizes a diverse set of data integration applications.<br/></p><p><strong>"Towards Adaptive Cyber-Physical Systems"<br/></strong></p><p><strong>J</strong><strong>ames Orr<br/></strong>Adviser: Chris Gill</p><p>Recent advances in parallel real-time theory and platforms have allowed for previously unachievable temporal and computational resolution in high-performance cyber-physical applications such as real-time hybrid structural testing.  However, these approaches suffer from rigidity and pessimism of resource allocation due to <em>a priori</em> analysis that is static at run-time. <br/></p><p>To address those limitations we propose a new approach to exploit <em>parallel real-time elasticity</em> of online resource tradeoffs between computational and temporal resolution of different parts of the system. In doing so, we aim to use the slack between the allotted worst-case and actual behavior of individual sub-systems <em>adaptively</em>, to improve precision in managing computational resolution, temporal resolution, or both.  This ongoing work lays the groundwork for a concurrency platform architecture that can exploit parallel real-time resource elasticity dynamically, towards more adaptive cyber-physical systems.<br/></p><p><br/></p>
CSE Dissertation Proposal: Yajie Yanhttps://engineering.wustl.edu/Events/Pages/CSE-Dissertation-Proposal-Yajie-Yan.aspx965CSE Dissertation Proposal: Yajie Yan2017-05-02T05:00:00Z1:30 p.m.3 p.m.Jolley Hall, Room 309<p rtenodeid="9"><strong>"Medial Axis Computation and Application"​</strong></p><p><strong>Yajie Yan</strong><br/>Adviser: Tao Ju</p><p>Medial axis is a classical shape descriptor. It captures both the geometry and topology of a shape compactly. Therefore medial axis is a useful tool for analyzing shapes in several fields, including biology, computer vision and computer graphics. Though its value is well appreciated, robust computation has been lacking because medial axis is sensitive to noise on the shape's boundary and difficult to approximate. We contribute to the community by tackling these two challenges. First, we define a novel significance measure to de-noise the medial axis of a 3D shape. Second, we propose a scalable and accurate method for approximating the medial axis of an important class of shapes, the digital shapes. Finally, we argue that medial axis has the potential to help solve real  world problems. Particularly, we propose to recover the correct structure of a complex crop root system using medial axis.<br/></p>
Groundbreaking Ceremony: Jubel & McKelvey Hallshttps://engineering.wustl.edu/Events/Pages/Jubel-Hall-Groundbreaking.aspx524Groundbreaking Ceremony: Jubel & McKelvey Halls2017-05-05T05:00:00Z4 p.m.<ul><li>Anabeth and John Weil Hall<br/></li><li>Henry A. and Elvira H. Jubel Hall (Engineering)<br/></li><li>Gary M. Sumers Welcome Center<br/></li><li>James M. McKelvey, Sr. Hall (Engineering)<br/></li><li>Mildred Lane Kemper Art Museum Expansion<br/></li><li>Ann and Andrew Tisch Park<br/></li></ul>
CSE Dissertation Defense: Hang Douhttps://engineering.wustl.edu/Events/Pages/CSE-Dissertation-Defense-Hang-Dou.aspx966CSE Dissertation Defense: Hang Dou2017-05-08T05:00:00Z10 a.m.12 p.m.Jolley Hall, Room 309<p rtenodeid="8"><strong>​"Efficient Geometric Approaches for Mining Protein Structure from Cryo-EM Density Maps"</strong></p><p><strong>Hang Dou</strong><br/>Adviser: Tao Ju<br/></p><p>A protein's 3D structure is the key to understanding its biological function. In recent years, cryo-electron microscopy or cryo-EM has established itself as a mainstream technique to capture proteins' structure at near-native conditions. However the vast majority of cryo-EM data are at medium (5-10A) or low (>10A) resolutions, which is insufficient to capture a protein's atomic structure. Fortunately, at such resolutions, some intrinsic structures of a protein, such as secondary structure elements (SSEs) and smooth C-alpha backbone fragments (SCBFs), can be recognized or robustly detected. In this dissertation, we present efficient protein fitting pipelines to recover a protein's atomic structure given the protein's cryo-EM density map by leveraging the intrinsic structure information detected from the density map. Specifically, we first compute the correspondences between the protein features (SSEs or SCBFs) detected from the cryo-EM density map and those extracted from the template model. Then we fit the template model into the cryo-EM density map guided by the obtained correspondences.<br/><br/></p>
Commencement: Engineering Student Recognition Ceremonyhttps://engineering.wustl.edu/Events/Pages/Engineering-Student-Recognition-Ceremony.aspx567Commencement: Engineering Student Recognition Ceremony2017-05-18T05:00:00Z1:30 p.m.Field House, Athletic Complex<p>Students (undergraduate, graduate and PhD) should arrive for lineup before 12:45 p.m. in the lower level hallway. Upon arrival, students should obtain a name card and complete the information requested on the back. <span style="line-height: 25.6px;">Students should carry (not wear) hoods.</span><br/></p><p><strong>Reception locations following the ceremony:</strong></p><ul><li><strong>Biomedical Engineering: </strong>Whitaker Hall</li><li><strong>Computer Science & Engineering:</strong> Sever Plaza</li><li><strong>Electrical & Systems Engineering:</strong> Green Hall </li><li><strong>Energy, Environmental & Chemical Engineering:</strong> Brauer Hall </li><li><strong>Mechanical Engineering & Materials Science:</strong> Lopata Hall<br/></li></ul><div><a href="/current-students/student-services/Pages/commencement.aspx">>> View more details.</a><br/></div>Kim Shilling, 314-935-6100
Commencementhttps://engineering.wustl.edu/Events/Pages/All-University-Commencement-2017.aspx568Commencement2017-05-19T05:00:00Z8:30 a.m.Brookings Quadrangle<p>Engineering students lineup along Louderman Hall. <span style="line-height: inherit;">PhD stude</span><span style="line-height: inherit;">nts assemble with the Graduate School next to Wilson Hall.</span>​</p>
No Classes (Independence Day)https://engineering.wustl.edu/Events/Pages/End-summer-session.aspx697No Classes (Independence Day)2017-07-04T05:00:00ZEngineering Student Services, (314) 935-6100