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Events for November 12, 2018

  • Repeating EventMeet USC: Admission Presentation, Campus Tour, and Engineering Talk

    Mon, Nov 12, 2018

    Viterbi School of Engineering Undergraduate Admission

    University Calendar


    This half day program is designed for prospective freshmen (HS seniors and younger) and family members. Meet USC includes an information session on the University and the Admission process, a student led walking tour of campus, and a meeting with us in the Viterbi School. During the engineering session we will discuss the curriculum, research opportunities, hands-on projects, entrepreneurial support programs, and other aspects of the engineering school. Meet USC is designed to answer all of your questions about USC, the application process, and financial aid.

    Reservations are required for Meet USC. This program occurs twice, once at 8:30 a.m. and again at 12:30 p.m.

    Please make sure to check availability and register online for the session you wish to attend. Also, remember to list an Engineering major as your "intended major" on the webform!

    RSVP

    Location: Ronald Tutor Campus Center (TCC) - USC Admission Office

    Audiences: Everyone Is Invited

    View All Dates

    Contact: Rebecca Kinnon

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  • USC Viterbi Data Analytics Boot Camp

    Mon, Nov 12, 2018

    Executive Education

    Conferences, Lectures, & Seminars


    Abstract: What you will learn:

    - Students will learn the fundamental and specialized skills necessary to pursue a career or advance in the booming field of data analytics, including Python, JavaScript, Advanced Excel, SQL Databases and more.

    - Students are equipped with the technical skills needed to translate data into competitive insights in the workplace, leading to career advancement opportunities.

    - Students receive a hands-on, classroom learning experience, conducting robust analytics on a host of real-world problems.

    - Students working to change career paths receive career-planning assistance, including industry speakers and company-led events, resume, Linkedln and portfolio support, and interview preparation.


    More Info: https://viterbiexeced.usc.edu/engineering-program-areas/computer-science/usc-viterbi-data-analytics-boot-camp/

    Audiences: Registered Attendees

    Contact: Corporate & Professional Programs

    Event Link: https://viterbiexeced.usc.edu/engineering-program-areas/computer-science/usc-viterbi-data-analytics-boot-camp/

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  • CS Colloquium: Ram D. Sriram (NIST) - Explorations in Artificial Intelligence: A Personal Journey

    CS Colloquium: Ram D. Sriram (NIST) - Explorations in Artificial Intelligence: A Personal Journey

    Mon, Nov 12, 2018 @ 11:00 AM - 12:20 PM

    Thomas Lord Department of Computer Science

    Conferences, Lectures, & Seminars


    Speaker: Ram D. Sriram, National Institute of Standards and Technology

    Talk Title: Explorations in Artificial Intelligence: A Personal Journey

    Series: Computer Science Colloquium

    Abstract: My first exposure to Artificial Intelligence (AI) was in the summer of 1981, when Carnegie Mellon University was tasked with the development of a knowledge-based expert system (KBES) to aid in the trouble shooting of the Atlanta People Mover. I was a student member of this team and went on to do my dissertation on AI in Design. Later, I joined MIT as an assistant professor (in 1986) and with my students built one of the most comprehensive computational frameworks for Internet-based collaborative design -“ called DICE. The DICE framework introduced several novel concepts in AI, including an active object-oriented blackboard, constraint satisfaction using asynchronous teams, merging qualitative geometry with traditional modeling, knowledge representation schemes for product and process models, and design rationale. In 1994, I moved to NIST and continued work on knowledge representation for entire product life cycle until 2010, when I took over as the chief of Software and Systems Division. Here, I have provided technical leadership for several AI projects, which include extending deep learning techniques in biomedical image processing, extracting protein-protein interaction sentences from documents, developing a novel natural language term extraction system based on Sanskrit, and applying Category Theory for AI knowledge representation. In this talk, I will describe my journey over nearly four decades with a particular focus on my recent work at NIST on knowledge representation, machine learning, and natural language processing.

    This lecture satisfies requirements for CSCI 591: Research Colloquium.


    Biography: Ram D. Sriram is currently the chief of the Software and Systems Division, Information Technology Laboratory, at the National Institute of Standards and Technology (NIST). Before joining the Software and Systems Division, Sriram was the leader of the Design and Process group in the Manufacturing Systems Integration Division, Manufacturing Engineering Laboratory, where he conducted research on standards for interoperability of computer-aided design systems. Prior to joining NIST, he was on the engineering faculty (1986-1994) at the Massachusetts Institute of Technology (MIT) and was instrumental in setting up the Intelligent Engineering Systems Laboratory. Sriram has co-authored or authored more than 250 publications, including several books on artificial intelligence. Sriram was a founding co-editor of the International Journal for AI in Engineering. Sriram received several awards including: an NSF's Presidential Young Investigator Award (1989); ASME Design Automation Award (2011); ASME CIE Distinguished Service Award (2014); the Washington Academy of Sciences' Distinguished Career in Engineering Sciences Award (2015); ASME CIE division's Lifetime Achievement Award (2016); and CMU CEE Lt. Col. Christopher Raible Distinguished Public Service Award (2018). Sriram is a Fellow of ASME, AAAS, IEEE and Washington Academy of Sciences, a Member (life) of ACM and a Senior Member (life) of AAAI. Sriram has a B.Tech. from IIT, Madras, India, and an M.S. and a Ph.D. from Carnegie Mellon University, Pittsburgh, USA.

    Host: Computer Science Department

    Location: Olin Hall of Engineering (OHE) - 100D

    Audiences: Everyone Is Invited

    Contact: Computer Science Department

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  • Seminars in Biomedical Engineering

    Mon, Nov 12, 2018 @ 12:30 PM - 01:50 PM

    Conferences, Lectures, & Seminars


    Speaker: Kaustabh Ghosh, PhD, Associate Professor, Department of Bioengineering, Division of Biomedical Sciences, and Program in Cell, Molecular and Developmental Biology University of California, Riverside

    Talk Title: Learning the Hard Way: Role of Vascular Stiffening in Inflammatory Retinal Diseases

    Host: Qifa Zhou

    More Information: Ghosh USC BME Abstract.pdf

    Location: Olin Hall of Engineering (OHE) - 122

    Audiences: Everyone Is Invited

    Contact: Mischalgrace Diasanta

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  • Fall 2018 Joint CSC@USC/CommNetS-MHI Seminar Series

    Mon, Nov 12, 2018 @ 02:00 PM - 03:00 PM

    Ming Hsieh Department of Electrical and Computer Engineering

    Conferences, Lectures, & Seminars


    Speaker: Munther Dahleh, MIT

    Talk Title: A Marketplace for Data: An Algorithmic Solution

    Abstract: In this work, we aim to create a data marketplace; a robust real-time matching mechanism to efficiently buy and sell training data for Machine Learning tasks. While the monetization of data and pre-trained models is an essential focus of industry today, there does not exist a market mechanism to price training data and match buyers to vendors while still addressing the associated (computational and other) complexity. The challenge in creating such a market stems from the very nature of data as an asset: it is freely replicable; its value is inherently combinatorial due to correlation with signal in other data; prediction tasks and the value of accuracy vary widely; usefulness of training data is difficult to verify a priori without first applying it to a prediction task. As our main contributions we: propose a mathematical model for a two-sided data market and formally define the key associated challenges; construct algorithms for such a market to function and rigorously prove how they meet the challenges defined. We highlight two technical contributions: a new notion of fairness required for cooperative games with freely replicable goods; a truthful, zero regret mechanism for auctioning a particular class of combinatorial goods based on utilizing Myerson's payment function and the Multiplicative Weights algorithm. These might be of independent interest.

    This is a joint work with Anish Agarwal, Tuhin Sarkar, and Devavrat Shah.

    Biography: Munther A. Dahleh received his PhD degree from Rice University, Houston, TX, in 1987 in Electrical and Computer Engineering. Since then, he has been with the Department of Electrical Engineering and Computer Science (EECS), MIT, Cambridge, MA, where he is now the William A. Coolidge Professor of EECS. He is also a faculty affiliate of the Sloan School of Management. He is the founding director of the newly formed MIT Institute for Data, Systems, and Society (IDSS). Previously, he held the positions of Associate Department Head of EECS, Acting Director of the Engineering Systems Division, and Acting Director of the Laboratory for Information and Decision Systems. He was a visiting Professor at the Department of Electrical Engineering, California Institute of Technology, Pasadena, CA, for the Spring of 1993. He has consulted for various national research laboratories and companies. Dr. Dahleh is interested in Networked Systems with applications to Social and Economic Networks, financial networks, Transportation Networks, Neural Networks, and the Power Grid. Specifically, he focuses on the development of foundational theory necessary to understand, monitor, and control systemic risk in interconnected systems. His work draws from various fields including game theory, optimal control, distributed optimization, information theory, and distributed learning. His collaborations include faculty from all five schools at MIT. Dr. Dahleh is the co-author (with Ignacio Diaz-Bobillo) of the book Control of Uncertain Systems: A Linear Programming Approach, published by Prentice-Hall, and the co-author (with Nicola Elia) of the book Computational Methods for Controller Design, published by Springer. He is four-time recipient of the George Axelby outstanding paper award for best paper in IEEE Transactions on Automatic Control. He is also the recipient of the Donald P. Eckman award from the American Control Council in 1993 for the best control engineer under 35. He is a fellow of IEEE and IFAC. He has given many keynote lectures at major conferences.

    Host: Ketan Savla, ksavla@usc.edu

    More Info: http://csc.usc.edu/seminars/2018Fall/dahleh.html

    More Information: 18.11.12_Dahleh_MIT-CSC Seminar.pdf

    Location: 132

    Audiences: Everyone Is Invited

    Contact: Brienne Moore

    Event Link: http://csc.usc.edu/seminars/2018Fall/dahleh.html

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  • Mathworks Information Session

    Mon, Nov 12, 2018 @ 06:00 PM - 07:00 PM

    Viterbi School of Engineering Student Organizations

    Workshops & Infosessions


    If you have a strong technical background in software design, web development, control theory, signal processing, or embedded systems - We'd love to talk to you!

    Who: Students in Computer Science, Electrical Engineering, Mechanical Engineering, Biomedical Engineering or Aerospace Engineering - We are hiring for Spring Interns, Summer Interns, and Full-Time.

    Chipotle will be provided!

    More Information: MatLab-Info-Session-2018-Ad.pdf

    Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132

    Audiences: Everyone Is Invited

    Contact: Institute of Electrical and Electronics Engineers

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