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Events for January 24, 2017
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USC Stem Cell Seminar: Kathryn Anderson, Memorial Sloan Kettering Cancer Center
Tue, Jan 24, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Kathryn Anderson, Memorial Sloan Kettering Cancer Center
Talk Title: TBD
Series: Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC Distinguished Speakers Series
Host: USC Stem Cell
More Info: http://stemcell.usc.edu/events
Webcast: http://keckmedia.usc.edu/stem-cell-seminarWebCast Link: http://keckmedia.usc.edu/stem-cell-seminar
Audiences: Everyone Is Invited
Contact: Cristy Lytal/USC Stem Cell
Event Link: http://stemcell.usc.edu/events
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Recruiting Seminar
Tue, Jan 24, 2017 @ 11:00 AM - 12:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Shobeir Fakhraei, Ph.D. candidate at the Department of Computer Science, University of Maryland College Park
Talk Title: Collective Multi-relational Network Mining
Series: AI Seminar
Abstract: Our world is becoming increasingly interconnected and so is the data collected from it. Developing computational models capable of correctly representing the underlying interrelated structure and the heterogeneous characteristics of the real-world data is essential for representing and reasoning about it. Domains such as biology, online social networks, the World Wide Web, information networks, recommender systems, and scholarly networks are just a few examples that include explicit or implicit interdependent structures.
In this talk, I will present approaches to model heterogeneous interlinked data ranging from feature-based and embedding-based approaches to statistical relational learning methods that more explicitly model the dependencies between entities. I will discuss different methods of modeling node classification and link inference in networks for several domains and highlight the effect of two important aspects: (1) Heterogeneous entities and multi-relational structures, (2) joint inference and collective classification of the unlabeled data. I will also introduce a model for link inference that serves as a template to encode a variety of information such as structural, biological, social, and contextual interactions in various domains.
Biography: Shobeir Fakhraei is a Ph.D. candidate at the Department of Computer Science, University of Maryland College Park (UMD) and a visiting researcher at University of California Santa Cruz (UCSC). He holds two M.Sc. degrees specialized on Data Mining and Biomedical Informatics, and Computer Engineering, and has been recognized with awards such as outstanding graduate research assistant recognition award, and General Motors academic scholarship award. He has collaborated with several research teams in academia and industry including at Microsoft Research Redmond, Yahoo! Research Sunnyvale, Turi (Dato), Ifwe (Tagged), and Henry Ford Health System. His research interests include Machine Learning, Multi-Relational Graph Mining, Recommender Systems, Social Network Analysis, and Biomedical and Health Informatics
Host: Jose Luis Ambite and Kristina Lerman
Webcast: http://webcastermshd.isi.edu/Mediasite/Play/b53b0a1dfd3c44c8bda7a4001e8b3f101dLocation: Information Science Institute (ISI) -
WebCast Link: http://webcastermshd.isi.edu/Mediasite/Play/b53b0a1dfd3c44c8bda7a4001e8b3f101d
Audiences: Everyone Is Invited
Contact: Alma Nava / Information Sciences Institute
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The Office of Naval Research - Science and Technology in Support of the US Navy and Marine Corps
Tue, Jan 24, 2017 @ 11:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Ellen S. Livingston, Ph. D., Office of Naval Research, Arlington VA
Talk Title: The Office of Naval Research - Science and Technology in Support of the US Navy and Marine Corps
Abstract: The Department of Defense supports basic and applied research at universities and laboratories through the program offices of the three services: the Office of Naval Research (ONR), the Army Research Office (ARO), and the Air Force Office of Scientific Research (AFOSR). In this talk, we focus on opportunities at the Office of Naval Research and provide an introduction to ONR sponsored programs. We provide an overview of the areas of interest to ONR and show how to find programs and program managers in these areas. In addition, we will cover similar information about ARO and AFOSR. Finally, we briefly discuss the process for DURIP and MURI funding as well as the Vannevar Bush Faculty Fellowship funding process.
Biography: Dr. Ellen Livingston manages the University Research Initiatives Program at the Office of Naval Research (ONR) in Arlington, VA. This program sponsors basic research through the Multidisciplinary Research Initiative, the Defense University Research Instrumentation Program, the Presidential Early Career Awards, as well as the Vannevar Bush Faculty Fellowship Program. From 2010 to 2014, she was the Associate Director for Ocean Science Research at ONR Global in London, UK. From 1996 to 2009, she served as the ONR Ocean Acoustics Program Manager, supporting high-quality, basic and applied research in underwater acoustics, including extensive at-sea experimental work. From 1985 to 1995, Dr. Livingston was an experimental research mathematician in the Acoustic Signal Processing branch of the Naval Research Laboratory in Washington, DC. She has been a member of the NATO Scientific Committee of National Representatives in La Spezia, IT, a Visiting Scientist in the Department of Ocean Engineering at MIT, and is a Senior Member of the IEEE Oceanic Engineering Society. She received her PhD in Mathematics from Washington University in St. Louis.
Host: Alan Willner, x04664, willner@usc.edu
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Gerrielyn Ramos
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CS Colloquium: Ruslan Salakhutdinov (Carnegie Mellon) - Learning Deep Unsupervised and Multimodal Models
Tue, Jan 24, 2017 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ruslan Salakhutdinov, Carnegie Mellon
Talk Title: Learning Deep Unsupervised and Multimodal Models
Series: NVIDIA Distinguished Lecture Series in Machine Learning
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
In this talk I will first introduce a broad class of unsupervised deep learning models and show that they can learn useful hierarchical representations from large volumes of high-dimensional data with applications in information retrieval, object recognition, and speech perception. I will next introduce deep models that are capable of extracting a unified representation that fuses together multiple data modalities and present the Reverse Annealed Importance Sampling Estimator (RAISE) for evaluating these deep generative models. Finally, I will discuss models that can generate natural language descriptions (captions) of images and generate images from captions using attention, as well as introduce multiplicative and fine-grained gating mechanisms with application to reading comprehension.
Part of NVIDIA Distinguished Lecture Series in Machine Learning.
Biography: Ruslan Salakhutdinov received his PhD in computer science from the University of Toronto in 2009. After spending two post-doctoral years at the Massachusetts Institute of Technology Artificial Intelligence Lab, he joined the University of Toronto as an Assistant Professor in the Departments of Statistics and Computer Science. In 2016 he joined the Machine Learning Department at Carnegie Mellon University as an Associate Professor. Ruslan's primary interests lie in deep learning, machine learning, and large-scale optimization. He is an action editor of the Journal of Machine Learning Research and served on the senior programme committee of several learning conferences including NIPS and ICML. He is an Alfred P. Sloan Research Fellow, Microsoft Research Faculty Fellow, Canada Research Chair in Statistical Machine Learning, a recipient of the Early Researcher Award, Google Faculty Award, Nvidia's Pioneers of AI award, and is a Senior Fellow of the Canadian Institute for Advanced Research.
Host: Yan Liu
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Preparing for the Engineering Career Fair
Tue, Jan 24, 2017 @ 04:00 PM - 05:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Viterbi Students, make a great first impression at the Career Fair no matter what your class standing! You will learn how to optimize your time, approach employers, and prepare for this event.
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: All Viterbi
Contact: RTH 218 Viterbi Career Connections
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Preparing for Technical Interviews- Presented by Intel
Tue, Jan 24, 2017 @ 05:00 PM - 06:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Join Intel Representatives as they go over insider tips on technical interviewing as well as the best strategies for success.
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: RTH 218 Viterbi Career Connections
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EE Viterbi Alumni & Industry Spotlight
Tue, Jan 24, 2017 @ 07:00 PM - 08:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Students will hear from alumni and industry representatives regarding their academic/professional experiences.
Free Pizza!
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: All Viterbi Undergraduate Students
Contact: RTH 218 Viterbi Career Connections
