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SUNMONTUEWEDTHUFRISAT
Events for the -49th week of January
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TBA
Mon, Jan 16, 2017 @ 12:30 PM - 01:50 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: No Class (Martin Luther King, Jr. Holiday), No Class (Martin Luther King, Jr. Holiday)
Talk Title: No Class (Martin Luther King, Jr. Holiday)
Host: Qifa Zhou
Location: Olin Hall of Engineering (OHE) - 122
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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USC Stem Cell Seminar: Alex Meissner, Harvard Stem Cell Institute
Tue, Jan 17, 2017 @ 11:00 AM - 12:00 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Alex Meissner, Harvard Stem Cell Institute
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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CS Colloquium: Sungjin Ahn (University of Montreal) -Recent Advances and the Future of Recurrent Neural Networks
Tue, Jan 17, 2017 @ 11:00 AM - 12:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Sungjin Ahn, University of Montreal
Talk Title: Recent Advances and the Future of Recurrent Neural Networks
Series: CS Colloquium
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
Although the recent resurgence of Recurrent Neural Networks (RNN) has achieved remarkable advances in sequence modeling, we are still missing many abilities of RNN necessary to model more challenging yet important natural phenomena. In this talk, I introduce some recent advances in this direction, focusing on two new RNN architectures: the Hierarchical Multiscale Recurrent Neural Networks (HM-RNN) and the Neural Knowledge Language Model (NKLM). In the HM-RNN, each layer in a multi-layered RNN learns different time-scales, adaptively to the inputs from the lower layer. The NKLM deals with the problem of incorporating factual knowledge provided by knowledge graph into RNNs. I argue the advantages of these models and then conclude the talk with a discussion on the key challenges that lie ahead.
Biography: Sungjin Ahn is currently a postdoctoral researcher at the University of Montreal, working with Prof. Yoshua Bengio on deep learning and its applications. He received his Ph.D. in Computer Science at the University of California, Irvine, under the supervision of Prof. Max Welling. During his Ph.D. program, He co-developed the Stochastic Gradient MCMC algorithms and awarded two best paper awards from the International Conference on Machine Learning in 2012 and the ParLearning 2016, respectively. His research interests include deep learning (on recurrent neural networks, deep generative models), approximate Bayesian inference, and reinforcement learning.
Host: Yan Liu
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Epstein Institute Seminar
Tue, Jan 17, 2017 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Dr. Timothy Chan, University of Toronto
Talk Title: Inverse Optimization: Closed-Form Solutions, Geometry and Goodness of Fit
Host: Dr. Phebe Vayanos
More Information: January 17, 2017_Chan.pdf
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Michele ISE
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Writing Effective Resumes
Tue, Jan 17, 2017 @ 05:00 PM - 06:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Does your resume highlight the skills that will land an interview? Learn how to create a resume that will serve as the marketing tool that will get your foot inside industry's door!
Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: All Viterbi
Contact: RTH 218 Viterbi Career Connections
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Computer Science General Faculty Meeting
Wed, Jan 18, 2017 @ 12:00 PM - 02:00 PM
Thomas Lord Department of Computer Science
Receptions & Special Events
Bi-Weekly regular faculty meeting for invited full-time Computer Science faculty only. Event details emailed directly to attendees.
Location: Ronald Tutor Hall of Engineering (RTH) - 217
Audiences: Invited Faculty Only
Contact: Assistant to CS chair
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Spring PDP Info Session
Wed, Jan 18, 2017 @ 01:00 PM - 02:00 PM
Viterbi School of Engineering Graduate Admission, Viterbi School of Engineering Student Affairs, Viterbi School of Engineering Student Organizations
Workshops & Infosessions
Interested in earning your MS from Viterbi? How about starting a MS degree during your senior year? The Viterbi Graduate Admission team is hosting a Progressive Degree information session!
What are the details?
When: Wednesday, January 18th
Where: RTH 211
Who should attend?
All undergraduate students thinking about pursuing a MS degree through USC.
What is the Progressive Degree Program?
The Progressive Degree Program (PDP) gives continuing USC undergraduates another path to earning a Master's degree from USC. The main advantages to a Progressive Degree are:
1) Start graduate-level classes during your senior year
2) Reduce the units required for a Master's Degree
Where can you learn more?
More Progressive Degree information may be found by attending our information session and visiting USC Viterbi School of Engineering
Questions? Email the Viterbi Graduate Admission team at: viterbi.pdp@usc.eduLocation: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: Everyone Is Invited
Contact: Monica Graduate Admission
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Writing Effective Resumes
Wed, Jan 18, 2017 @ 04:00 PM - 05:00 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Does your resume highlight the skills that will land an interview? Learn how to create a resume that will serve as the marketing tool that will get your foot inside industry's door!
PLEASE BRING YOUR CURRENT RESUME!Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: All Viterbi
Contact: RTH 218 Viterbi Career Connections
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Get Connected Viterbi Involvement Fair
Thu, Jan 19, 2017 @ 11:00 AM - 12:00 PM
Viterbi School of Engineering Student Affairs
Student Activity
Would you like to join a club, organization, or design team this semester?
Come by the Get Connected engineering involvement fair Thursday, January 19 from 11:30 to 2:30 PM in the Epstein Family Plaza (E-Quad).
There will be plenty of booths for you to choose from! All you have to do is walk up and start talking with a representative to learn more about them.
You are bound to find at least one club, organization, or design team that is right for you, or you can just attend to learn more about the different clubs and resources that Viterbi has to offer. Hope to see you there!Location: Epstein Family Plaza (E-Quad)
Audiences: Undergrad
Contact: Christina Mireles Martin
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CS Distinguished Lecture: Vitaly Shmatikov (Cornell) - Machine Learning and Privacy: Friends or Foes?
Thu, Jan 19, 2017 @ 04:00 PM - 05:20 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Vitaly Shmatikov, Cornell University
Talk Title: Machine Learning and Privacy: Friends or Foes?
Series: CS Distinguished Lectures
Abstract: Recent advances in machine learning provide powerful new tools and juicy new targets for data privacy research. I will first show how to use machine learning against systems that partially encrypt data in storage while computing over it. Then, I will turn machine learning against itself, to extract sensitive training data from machine-learning models --- including black-box models constructed using Google's and Amazon's "learning-as-a-service" platforms. I will conclude with open research questions at the junction of machine learning and privacy.
Biography: Vitaly Shmatikov is a professor at Cornell Tech, where he works on computer security and privacy. He most recently served as the program chair of the IEEE Symposium on Security and Privacy ("Oakland").
Host: Aleksandra Korolova
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Get Connected for Maximum Job Search Success
Thu, Jan 19, 2017 @ 04:30 PM - 05:30 PM
Viterbi School of Engineering Career Connections
Workshops & Infosessions
Join us to get tips on how to make successful connections.
Attend this workshop and learn how to build relationships & connections to assist you in your academic career & in your job search. Develop the 30 Second Commercial you need to interact with employers. Discover how much networking you already do!Location: Ronald Tutor Hall of Engineering (RTH) - 211
Audiences: All Viterbi
Contact: RTH 218 Viterbi Career Connections
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CS Colloquium and CAIS Seminar: Eva K Lee (GATECH) - System interoperability & Machine Learning: Multi-site Evidence-based Best Practice Discovery
Fri, Jan 20, 2017 @ 11:00 AM - 11:50 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Eva K Lee, Georgia Institute of Technology
Talk Title: System interoperability & Machine Learning: Multi-site Evidence-based Best Practice Discovery
Series: Center for AI in Society (CAIS) Seminar Series
Abstract: This lecture satisfies requirements for CSCI 591: Computer Science Research Colloquium.
This study establishes interoperability among electronic medical records from 737 healthcare sites and performs machine learning for best practice discovery. A mapping algorithm is designed to disambiguate free text entries and to provide a unique and unified way to link content to structured medical concepts despite the extreme variations that can occur during clinical diagnosis documentation. Redundancy is reduced through concept mapping. A SNOMED-CT graph database is created to allow for rapid data access and queries. These integrated data can be accessed through a secured web-based portal. A classification model ((DAMIP) is then designed to uncover discriminatory characteristics that can predict the quality of treatment outcome. We demonstrate system usability by analyzing Type II diabetic patients. DAMIP establishes a classification rule on a training set which results in greater than 80% blind predictive accuracy on an independent set of patients. By including features obtained from structured concept mapping, the predictive accuracy is improved to over 88%. The results facilitate evidence-based treatment and optimization of site performance through best practice dissemination and knowledge transfer. This project receives the 2016 NSF Health Organization Transformation award.
Biography: Dr. Lee is a Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology, and Director of the Center for Operations Research in Medicine and HealthCare, a center established through funds from the National Science Foundation and the Whitaker Foundation. The center focuses on biomedicine, public health, and defense, advancing domains from basic science to translational medical research; intelligent, quality, and cost-effective delivery; and medical preparedness and protection of critical infrastructures. She is a Distinguished Scholar in Health Systems, Health System Institute at Georgia Tech and Emory University. She is also the Co-Director of the Center for Health Organization Transformation, an NSF Industry/University Cooperative Research Center. Lee partners with hospital leaders to develop novel transformational strategies in delivery, quality, safety, operations efficiency, information management, change management and organizational learning. Lee's research focuses on mathematical programming, information technology, and computational algorithms for risk assessment, decision making, predictive analytics and knowledge discovery, and systems optimization. She has made major contributions in advances to medical care and procedures, emergency response and medical preparedness, healthcare operations, and business operations transformation.
Dr. Lee serves on the National Preparedness and Response Science Board. She is the principle investigator of an online interoperable information exchange and decision support system for mass dispensing, emergency response, and casualty mitigation. The system integrates disease spread modeling with response processes and human behavior; and offers efficiency and quality assurance in operations and logistics performance. It currently has over 9500+ public health site users. Lee has also performed field work within the U.S. on mass dispensing design and evaluation, and has worked with local emergency responders and affected populations after Hurricane Katrina, the Haiti earthquake, the Fukushima Japan radiological disaster, and Hurricane Sandy. Lee has received multiple analytics and practice excellence awards including INFORMS Franz Edelman award, Daniel H Wagner prize for novel cancer therapeutics, bioterrorism emergency response dispensing for mass casualty mitigation, optimizing and transforming clinical workflow and patient care, vaccine immunity prediction, and reducing hospital acquired conditions. Dr. Lee is an INFORMS Fellow. She has received seven patents on innovative medical systems and devices. A brief glimpse of Dr. Lee's healthcare work can be found in the following link: http://www2.isye.gatech.edu/~evakylee/Eva_Lee_Intl_Innovation_139_Research_Media_HR.pdf
Host: Milind Tambe
Location: Seeley G. Mudd Building (SGM) - 101
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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W.V.T. Rusch Engineering Honors Program Colloquium
Fri, Jan 20, 2017 @ 01:00 PM - 01:50 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
University Calendar
Join us for a presentation by Dr. Emilio Ferrara, Research Professor of Computational Social Sciences at Information Sciences Institute, titled "The Rise of Social Bots."
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Ramon Borunda/Academic Services
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BME Special Seminar
Fri, Jan 20, 2017 @ 02:30 PM - 03:30 PM
Alfred E. Mann Department of Biomedical Engineering
Conferences, Lectures, & Seminars
Speaker: Dominique Duncan, Assistant Professor of Neurology, Keck School of Medicine, LONI
Talk Title: Predicting Epileptogenesis after Traumatic Brain Injury and Using Virtual Reality to Correct Segmentation Errors in MRI
Abstract: The first part of my talk focuses on identifying biomarkers that can predict epileptogenesis after traumatic brain injury (TBI). This project, The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx), is a multi-site, international collaboration including a parallel study of humans and rats, collecting MRI, EEG, and blood samples.
Because the development of epilepsy following TBI is a multifactorial process and
crosses multiple modalities, identifying biomarkers to quantify the condition has proved difficult. Without a full understanding of the underlying biological effects, there are currently no cures for epilepsy. This study hopes to address both issues, calling upon data generated and collected at sites spread worldwide among different laboratories, clinical sites, in different formats, and across multicenter preclinical trials. Before these data can even be analyzed, a central platform is needed to standardize these data and provide tools for searching, viewing, annotating, and analyzing them. We are building a centralized data archive for EEG that will link to the Laboratory of Neuro Imaging (LONI) Image Data Archive (IDA) for MRI data and allow the broader epilepsy research community to access this shared data in addition to analytic tools to identify and validate biomarkers of epileptogenesis in images and electrophysiology as well as in molecular, serological, and tissue studies.
The second part of this talk focuses on crowdsourcing manual validation of algorithmically-segmented brain volumes using virtual reality. LONI has the largest collection/repository of neuroanatomical MRI scans in the world. One of the lab's workflow processes involves algorithmic segmentation of the scans into labeled anatomical regions using FreeSurfer software. Since this automation cannot yet achieve perfect accuracy, there is a team of students who are trained to fix these errors manually, which is a tedious, time-consuming process. We are working on transforming the way this is accomplished using VR technology (HTC Vive) to deal with the volumes directly in 3D space, which aims to be both more intuitive and efficient. The goal is to crowdsource this task to make the process even more efficient.
Biography: http://loni.usc.edu/about_loni/people/indiv_detail.php?people_id=568
Host: Biomedical Engineering Department
Location: 146
Audiences: Everyone Is Invited
Contact: Mischalgrace Diasanta
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NL Seminar-HOW I LEARNED TO STOP WORRYING AND LOVE EVALUATIONS (AND KEEP WORRYING)
Fri, Jan 20, 2017 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Jon May, USC/ISI
Talk Title: HOW I LEARNED TO STOP WORRYING AND LOVE EVALUATIONS (AND KEEP WORRYING)
Series: Natural Language Seminar
Abstract: Bake-offs, shared tasks, evaluations: these are names for short, high-stress periods in many CS researchers' lives where their algorithms and models are exposed to unseen data, often with reputations and funding on the line. Evaluations are sometimes perceived to be the bane of much of our work lives. We grouse about metrics, procedures, glitches, and all the time "wasted" chasing scores, rather than doing Real Science (TM). In this talk I will argue that despite valid criticisms of the approach, coordinated evaluation is a net benefit to NLP research and has led to accomplishments that might not have otherwise arisen. This argument will frame a more in-depth discussion of several pieces of recent evaluation-grounded work: rapid generation of translation and information extraction for low-resource surprise languages (DARPA LORELEI) and organization of SemEval shared tasks in semantic parsing and generation.
Biography: Jonathan May is a Research Assistant Professor at the University of Southern California's Information Sciences Institute (USC/ISI). Previously, he was a research scientist at SDL Research (formerly Language Weaver) and a scientist at Raytheon BBN Technologies. He received a Ph.D. in Computer Science from the University of Southern California in 2010 and a BSE and MSE in Computer Science Engineering and Computer and Information Science, respectively, from the University of Pennsylvania in 2001. Jon's research interests include automata theory, natural language processing, machine translation, and machine learning.
Host: Marjan Ghazvininejad and Kevin Knight
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 6th Flr -CR#689 (ISI/Marina Del Rey)
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
