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Events for the 4th week of August
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MS - Group Advisement Session
Mon, Aug 19, 2019 @ 10:00 AM - 11:40 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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MS- Group Advisement Session
Mon, Aug 19, 2019 @ 02:00 PM - 03:40 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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TA Training
Tue, Aug 20, 2019 @ 09:00 AM - 03:00 PM
Viterbi School of Engineering Doctoral Programs
Workshops & Infosessions
TA Training is mandatory for all new teaching assistants and must be completed prior to serving as a TA. Please be advised that new TAs must attend the entire session in order to earn credit and work as a TA.
Fall TA Training will be held on Tuesday, August 20, 2019 9:00am - 3:00pm
Location TBD
Lunch will be served.
Registration required by August 15 via https://viterbigrad.usc.edu/ta-training-for-new-tas/Location: TBD
Audiences: New TAs only
Contact: Jennifer Gerson
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MS - Group Advisement Session
Tue, Aug 20, 2019 @ 10:00 AM - 11:40 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Mark Taper Hall Of Humanities (THH) - 201
Audiences: Graduate
Contact: Art Perez
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MS - Group Advisement Session
Tue, Aug 20, 2019 @ 02:00 PM - 03:40 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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Web Communities
Wed, Aug 21, 2019 @ 10:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Savvas Zannettou, Cyprus University of Technology
Talk Title: Web Communities
Abstract: The Web consists of numerous Web communities, news sources, and services, which are usually exploited by various entities for the dissemination of false information. Yet, we lack tools and techniques to effectively track the propagation of information across the multiple diverse communities and to capture and model the interplay between them. Also, we lack a basic understanding of what the role and impact of some emerging communities and services on the Web information ecosystem is, and more importantly, how such communities are exploited by bad actors (e.g., state- sponsored trolls) that spread false and weaponized information. In this talk, we will present numerous studies where we follow a data-driven cross-platform quantitative approach that analyzes billions of posts from Twitter, Reddit, 4chan Politically Incorrect board (/pol/), and Gab, to shed light into: 1) how news and image-based memes travel from one Web community to another and how we can model and quantify the influence between the various Web communities; 2) what is the role and impact of new emerging Web communities (e.g., Gab); and 3) how popular Web communities are exploited by state-sponsored actors for the sole purpose of spreading disinformation and sowing public discord.
Biography:
Savvas Zannettou is a PhD candidate from Cyprus University of Technology, co-advised by Dr. Michael Sirivianos and Dr. Jeremy Blackburn. In 2014 and 2016 he received respectively the BSc and
MSc degrees in Computer Engineering from Cyprus University of Technology. During 2014, he was a Research Intern at NEC Labs Europe for 6 months where he worked on Software-Defined Networks.
During 2017 and 2018, he was a Research Intern at Telefonica Research for 12 months. He is primarily interested in applying large-scale cross-platform quantitative analysis to understand emerging socio-technical issues like the spread of disinformation/misinformation and hateful content across the Web.
During his PhD, he received two first-author best paper awards: one at IMC 2018 and one at Cybersafety workshop (co-located with WWW).
Host: Shrikanth Narayanan (Viterbi), Emilion Ferrara (ISI)
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 132
Audiences: Everyone Is Invited
Contact: Tanya Acevedo-Lam/EE-Systems
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MS - Group Advisement Session
Wed, Aug 21, 2019 @ 10:00 AM - 11:40 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Art Perez
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Seminar
Wed, Aug 21, 2019 @ 10:00 AM - 12:00 PM
Ming Hsieh Department of Electrical and Computer Engineering
Conferences, Lectures, & Seminars
Speaker: Peter Hofstee and Johan Peltenburg, Delft University of Technology, Netherlands
Talk Title: The Fletcher Framework, Bringing Apache Arrow to FPGAs
Abstract: Modern big data systems are highly heterogeneous. Components are implemented in a wide variety of programming languages and frameworks. Due to implementation differences, interfaces between components are burdened by serialization overhead. The Apache Arrow project helps to overcome this burden through a language-agnostic columnar in-memory format for big data applications. It is currently being integrated in many big data analytics frameworks, such as Apache Spark & Parquet, Dask, Pandas, etc...
The open-source Fletcher framework is an implementation of Arrow for FPGA accelerators. Through a design generation step, Fletcher takes Arrow data structures and generates specialized, high-performance and easy-to-use hardware interfaces that can connect to accelerator kernels. Serialization overhead is prevented, and integration with over 11 high-level languages is made possible and efficient.
After a brief introduction providing context for shared-memory heterogeneous computing using some of the current POWER systems as examples, we will go over the benefits of Apache Arrow and Fletcher, show a hands-on example, and discuss related projects, such as applying SQL queries to the Arrow datasets in FPGA, reading and decompressing Parquet files on the fly using FPGA, straight into host-system memory.
Biography: Peter Hofstee is a distinguished research staff member at IBM Austin, USA, and a part-time professor in Big Data Systems at Delft University of Technology, Netherlands. He is best known for his contributions to Heterogeneous computing as the chief architect of the Synergistic Processor Elements in the Cell Broadband Engine processor used in the Sony PlayStation 3, and the first supercomputer to reach sustained Petaflop operation. After returning to IBM research in 2011 he has focused on optimizing the system roadmap for big data, analytics, and cloud, including the use of accelerated computation. His early research work on coherently attached reconfigurable acceleration on POWER7 paved the way for the new coherent attach processor interface on POWER8. He holds more than 100 issued patents.
Johan Peltenburg is a PhD Candidate from the Delft University of Technology in The Netherlands. His research focuses on heterogeneous computing for big data applications. Johan received his B. Eng in Electrical Engineering at the Rotterdam University of Applied Science, followed by an M.Sc. in Computer Engineering at the Delft University of Technology. After spending some years in industry and as a teacher at the Rotterdam University of Applied science, Johan joined the Quantum & Computer Engineering department of the TU Delft in 2016, where he pursues his Ph.D. degree in Computer Engineering. He is currently working on the Fletcher FPGA accelerator framework within the Accelerated Big Data Systems group.
Host: Murali Annavaram
Location: Hughes Aircraft Electrical Engineering Center (EEB) - 248
Audiences: Everyone Is Invited
Contact: Estela Lopez
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MS - Group Advisement Sessions
Wed, Aug 21, 2019 @ 02:00 PM - 03:40 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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MS - Group Advisement
Thu, Aug 22, 2019 @ 10:00 AM - 11:40 AM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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Viterbi Undergraduate New Student Welcome
Thu, Aug 22, 2019 @ 11:30 AM - 01:30 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
Receptions & Special Events
The annual Viterbi Undergraduate New Student Welcome will be held on Thursday, August 22nd. We welcome Viterbi's incoming freshman and transfer students with food, fun, games, and a class picture.
This is your chance to meet faculty, staff, and student organizations. An invitation will be sent out directly to new Viterbi students with RSVP information. Hope to see you there!
*By Invite OnlyLocation: Epstein Family Plaza (E-Quad)
Audiences: By Invite Only
Contact: Amanda McCraven
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Viterbi Undergraduate Get Connected Fair
Thu, Aug 22, 2019 @ 01:30 PM - 02:30 PM
USC Viterbi School of Engineering, Viterbi School of Engineering Student Affairs
Receptions & Special Events
Would you like to join a club, organization or design team?
Come by the Get Connected engineering involvement fair Thursday, August 22, 2019 from 1:30 p.m. - 2:30 p.m. in the VHE Breezeway.
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 thats 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!
Thursday, August 22, 2019
Epstein Family Plaza (VHE Breezeway)
1:30 p.m. - 2:30 p.m.Location: Epstein Family Plaza (VHE Breezeway)
Audiences: New fall 2019 Viterbi Undergrads
Contact: Amanda McCraven
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MS - Group Advisement
Thu, Aug 22, 2019 @ 02:00 PM - 03:40 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2019 students are encouraged to attend at least one session. One-on-one time with advisors will be available toward the end of the group advisement session. Appointments are not required to attend this session.
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Graduate
Contact: Art Perez
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PhD Defense - Daniel Moyer
Fri, Aug 23, 2019 @ 09:30 AM - 11:30 AM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Daniel Moyer
Date: Friday August 23rd, 2019
Time: 9:30 am - 11:30 am
Location: GFS 213
Committee: Greg Ver Steeg, Paul Thompson, Aram Galstyan, Aiichiro Nakano
Title:
Representation Problems in Brain Imaging
Abstract:
Diffusion weighted Magnetic Resonance Imaging (dMRI) is a imaging modality that, conditional on direction, queries the propensity for water diffusion in living tissue. These images are desirable for studying tissues with anisotropic diffusion profiles, e.g. the white matter of the human brain. I here describe two problems at the interface between diffusion imaging and computational science, as well as proposed solutions for those problems, reconciling differences between current methodology, existing theory, and practical constraints.
The first part of this thesis describes methodology from the intersection of network science and neuroscience. Previous literature has worked to estimate white matter axon bundles (fasiculi) from dMRI. Combined with segmentations of the grey matter, this leads intuitively to the construction of macro-scale brain networks, where nodes are cortical regions and edges are estimates of axonal connections. The work I present here deconstructs this progression, reconciling the inherently spatially continuous cortex with discrete network theory. The resulting model is a generalization of discrete graphs, using point process theory to create continuous interaction densities (continuum adjacency functions).
The second part of this thesis describes a method for learning representations of data that invariant under changes in specified outside factors. These can be applied to diffusion imaging data, which in particular suffers from instrument/observer biases ("site/scanner" biases). Due to the relative complexity of the domain, modelling the particular effects of each instrument may be difficult; moreover, such an approach does not generalize to unseen instruments. Instead, the described method can learn representations that are minimally informed of the imaging site. Subsequent derived data will then be at least as uninformed of the site variable.
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 213
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
