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Events for April 22, 2013
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Astani CEE. Dept Seminar
Mon, Apr 22, 2013 @ 11:00 AM - 12:00 PM
Sonny Astani Department of Civil and Environmental Engineering
Conferences, Lectures, & Seminars
Speaker: Mohammad Ebtehaj , University of Minnesota
Talk Title: Hydro-meteorological Inverse Problems via Sparse Regularization
Abstract: The past decades have witnessed a remarkable emergence of new sources of multi-scale multi-sensor geophysical data such as precipitation, evapotranspiration, soil moisture, and vegetation. These data provide a unique opportunity to better understand land surface hydro-meteorological processes and to improve our environmental forecast skills. For precipitation, these data typically include global spaceborne active and passive sensors and regional ground-based radars. Focusing on the non-Gaussian and heavy tailed statistical structure of precipitation data, new frameworks are presented that address optimal retrieval, fusion and resolution enhancement of multi-sensor rainfall data. These frameworks rely on recent advancements in computational methods for sparse solutions of inverse problems. Compared to the existing classic methodologies, the results of the proposed approaches promise improved posterior estimates of precipitation fluxes to be used for more accurate prediction of extreme land surface hydro-geomorphic events, such as floods and landslides. Future extension of the proposed approaches to data assimilation problems and other land surface applications are also discussed.
Biography: Mohammad Ebtehaj is a doctoral candidate in the Department of Civil Engineering and the Saint Anthony Falls Laboratory at the University of Minnesota. He will complete his degree in June 2013 with a double major -- PhD in civil engineering and M.Sc. in mathematics. He is currently a NASA Earth and Space Science Fellow (NESSF) and a University of Minnesota Doctoral Dissertation Fellow (DDF). He received his B.Sc. in civil engineering from Iran University of Science and Technology (IUST) in 1999, where he also received two M.Sc. degrees in environmental and earthquake engineering in 2001 and 2007, respectively. He has worked in industry for almost seven years as a design civil engineer in his country. His research interests are in computational geophysics, focusing on remote sensing hydro-meteorological inverse problems, specifically statistical and mathematical characterization of precipitation images from ground and space sensors. His work ââ¬ÅAdaptive Fusion and Sparse Estimation of Multi-sensor Precipitationââ¬Â received the 2011 outstanding student paper award of the American Geophysical Union.
Host: Astani CEE Dept.
Location: Kaprielian Hall (KAP) - 209
Audiences: Everyone Is Invited
Contact: Cassie Cremeans
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Biomedical Engineering Seminars (BME 533)
Mon, Apr 22, 2013 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Heidi Gensler, BME, Graduate Research Assistant, Biomedical Microsystems Laboratory , Advisor: Ellis Meng; Winner of BME's highest award for PhD students, the Grodins Graduate Award (2013)
Talk Title: A Wireless Implantable MEMS Micropump System for Site-specific Anti-cancer Drug Delivery
Host: David D'Argenio
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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Magneto-electric Nanoparticles for Enabling Personalized NanoMedicine
Mon, Apr 22, 2013 @ 02:00 PM - 03:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Sakhrat Khizroev, Florida International University
Talk Title: Magneto-electric Nanoparticles for Enabling Personalized NanoMedicine
Abstract: The use of nanoparticles is often considered as an enabling force of personalized nanomedicine (PNM). Using nanoparticles to precisely navigate a drug through the patient’s body and control its dosage and composition as well as to detect even minute disease-caused changes in the surrounding cellular microenvironment can make personalized treatment a reality. However, the fundamental physics that underlies the nanoparticles’ characteristics in the perspective of the intrinsic interaction with the patient’s body in the aforementioned applications is poorly exploited. Our recent discovery of the unprecedented capabilities of magneto-electric nanoparticles (MENs) helps fill this gap. MENs could be used as energy-efficient and dissipation-free field-controlled nano-vehicles for targeted delivery and on-demand release of anti-Cancer and anti-HIV drugs as well as nano-stimulators for field-controlled non-invasive treatment of patients with central nervous system (CNS) disorders. Further, the intrinsic coupling between electric and magnetic forces within MENs enables molecular specificity that provides an entirely new dimension even to conventional state-of-the-art diagnostic methods such as MRI, PET-CT, the emerging diagnostic technique of magnetic nanoparticle imaging (MNI), and others. The talk will present the MEN applications developed in the Khizroev laboratory to treat and diagnose Cancer, HIV, Parkinsons Diseases and other dementia.
Biography: Sakhrat Khizroev is an inventor with an expertise in nanomagnetic/spintronic devices with a current research focus on nanotechnology applications in Personalized Nanomedicine and Information Processing. He is a tenured Professor of Electrical and Computer Engineering and a Professor and Vice Chair at the Department of Immunology of Herbert Wertheim College of Medicine at FIU. He is also the founding Director of Center for Personalized NanoMedicine at the Institute of Neuro-Immune Pharmacology. From 2006 to 2010, Dr. Khizroev was a tenured Professor at the Department of Electrical Engineering, University of California, Riverside (UCR), where his group conducted several groundbreaking demonstrations in the area of nanoelectronics and nanodiagnostics. Perpendicular magnetic recording (PMR), three-dimensional (3-D) magnetic memory and Nanolasers for 5-nm diagnostics, low-damping spin-oscillator devices are among the pioneering and patented technologies which emerged under the supervision of Professor Khizroev. Prior to his academic career, Prof. Khizroev spent almost four years as a Research Staff Member with Seagate Research (1999-2003) and one year as a Doctoral Intern with IBM Almaden Research Center (1997-1998). He holds over 30 granted US patents and many international patents. He has authored over 120 refereed papers, 1 book and many book chapters in the broad area of nanomagnetic/spintronic devices. He is a Fellow of National Academy of Inventors (NAI). He has acted as a guest science and technology commentator on television and radio programs across the globe. He has served as an Editor for IEEE Transactions on Nanotechnology, Nanotechnology, and IEEE Transactions on Magnetics and sits on editorial boards of several Science and Technology journals. Khizroev received a BS in Quantum Electronics and Applied Physics from Moscow Institute of Physics and Technology, a MS in Physics from the University of Miami, and a PhD in Electrical and Computer Engineering from Carnegie Mellon University in 1992, 1994, and 1999, respectively.
Host: Mary Eshaghian-Wilner, Alice C. Parker
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Annie Yu
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CS Distinguished Lecture: Lise Getoor (University of Maryland College Park): Statistical Relational Learning and Graph Identification
Mon, Apr 22, 2013 @ 03:30 PM - 05:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Lise Getoor, University of Maryland College Park
Talk Title: Statistical Relational Learning and Graph Identification
Series: CS Distinguished Lectures
Abstract: Within the machine learning and data mining communities, there is a growing interest in learning structured models from input data that is itself structured, an area often referred to as statistical relational learning (SRL). In this talk, Iââ¬â¢ll give a brief overview of SRL, discuss its relation to graph analysis, extraction, and alignment, and its importance in the context of big data analytics. Iââ¬â¢ll then describe our recent work on "graph identification", the process of inferring a graph or network from observational data. Graph identification requires a combination of entity resolution (determining when two references refer to the same underlying entity), link prediction (inferring missing relationships in the data), and collective classification (inferring attribute values of the entities). This form of structured prediction allows us to infer missing information and correct mistakes -- a vital first step before further network analysis is performed. I will overview two approaches to graph identification: 1) coupled conditional classifiers (C^3), and 2) probabilistic soft logic (PSL). I will describe their mathematical foundations, learning and inference algorithms, and empirical evaluation, showing their power in terms of both accuracy and scalability. These methods support emerging information extraction and database techniques to realize the promise of extracting actionable knowledge from large-scale data in the wild. I will conclude by highlighting connections to privacy in social network data and other big data challenges.
Biography: Lise Getoor is an Associate Professor in the Computer Science Department at the University of Maryland, College Park and University of Maryland Institute for Advanced Computer Studies. Her research areas include machine learning, and reasoning under uncertainty; in addition she works in data management, visual analytics and social network analysis. She is a board member of the International Machine Learning Society, a former Machine Learning Journal Action Editor, Associate Editor for the ACM Transactions of Knowledge Discovery from Data, JAIR Associate Editor, and she has served on the AAAI Council. She was conference co-chair for ICML 2011, and has served on the PC of many conferences including the senior PC for AAAI, ICML, KDD, UAI and the PC of SIGMOD, VLDB, and WWW. She is a recipient of an NSF Career Award and was awarded a National Physical Sciences Consortium Fellowship. Her work has been funded by ARO, DARPA, IARPA, Google, IBM, LLNL, Microsoft, NGA, NSF, Yahoo! and others. She received her PhD from Stanford University, her Masterââ¬â¢s degree from University of California, Berkeley, and her undergraduate degree from University of California, Santa Barbara.
Host: Leana Golubchik
Location: Seaver Science Library (SSL) - 150
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
