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Events for the 3rd week of August
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MS Group Advisement Session - NEW and CONTINUING CS/INF Students
Mon, Aug 13, 2018 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for NEW and CONTINUING graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2018 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: John Stauffer Science Lecture Hall (SLH) - 200
Audiences: Graduate
Contact: Ryan Rozan
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PhD Defense- David C. Kale
Tue, Aug 14, 2018 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
Title: Learning to Diagnose from Electronic Health Records Data
Ph.D. Candidate: David C. Kale
Date and Time: Tuesday, August 14, 2018 at 10:00 AM in GFS 108
Committee: Greg Ver Steeg (Chair), Aram Galstyan, Gaurav Sukhatme, and Raghu Raghavendra
Abstract:
With the widespread adoption of electronic health records (EHRs), US hospitals now digitally record millions of patient encounters each year. At the same time, we have seen high-profile successes by machine learning, including superhuman performance in complex games. These factors have driven speculation that similar breakthroughs in healthcare are just around the corner, but there are major obstacles to replicating these successes. In this talk, we will discuss solutions to some of these challenges in the context of learning to diagnose, which involves building software to recognize diseases based on the analysis of historical data rather than expert knowledge. Our central hypothesis is that we can build such systems while minimizing the burden of effort on clinical experts. We will present results from one of the first successful applications of recurrent neural networks to the classification of multivariate clinical time series. We will then show how to extend this framework to model non-random missing values and heterogeneous prediction tasks. Finally, we will describe a public benchmark for clinical prediction and multitask learning that addresses the crisis of reproducibility in clinical machine learning and lowers the barrier to entry for new researchers. We will also spotlight additional research that considers nearest neighbor approaches and weak supervision in the absence of ground truth labels. We conclude by considering the broader impact of information technology on healthcare and how machine learning can help fulfill the vision of a learning healthcare system.
Location: Grace Ford Salvatori Hall Of Letters, Arts & Sciences (GFS) - 108
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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MS Group Advisement Session - NEW and CONTINUING CS/INF Students
Tue, Aug 14, 2018 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for NEW and CONTINUING graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2018 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: Ryan Rozan
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MS Group Advisement Session - NEW and CONTINUING CS/INF Students
Wed, Aug 15, 2018 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for NEW and CONTINUING graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2018 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: Ryan Rozan
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Joint INCOSE/IEEE SMCS Webinar
Wed, Aug 15, 2018 @ 12:00 PM - 12:01 PM
Systems Architecting and Engineering, USC Viterbi School of Engineering
Conferences, Lectures, & Seminars
Speaker: Thomas McDermott, Jr., Sunil Bharitkar, and Chistopher Nemeth, Stevens Institute of Technology, HP Labs, and Applied Research Associates
Talk Title: Bridging the Gulf of Execution
Series: INCOSE Speaker Series
Abstract: Research results routinely fail to survive into the development phase of Research and Development projects. This gulf of execution that blocks research findings from being realized in the development phase of many projects continues to bog down R and D practice.
Concurrent engineering was supposed to be a solution, but was it? Open innovation models were designed to bridge the gap, but have they? What is the gulf, and how did we get here? It might be a matter of professional focus. Research invests in understanding the problem, and Development invests in producing the solution. Innovation happens when these link up around people in a culture that promotes risk-taking. Or is it communication? Innovation happens when people from different disciplines or roles come together with common understanding. The issue spans multiple sectors. Large industries struggle to build an innovation culture when delivery of existing products and services is at the forefront. Universities have an innovation culture, but industry needs to adopt a systems approach to realize value from that culture. Industry-university partnerships are effective when both parties realize relationships across a broad range of university programs, from students to startups, and learn how to couple the university innovation system to the industry innovation enterprise.
Three examples from INCOSE and IEEE SMCS members will suggest ways to resolve this enduring issue.
Georgia Tech--We view this relationship as a system-of-systems model, where the industry product/service enterprise is coupled to the university innovation enterprise in a larger sociotechnical systems context, and where the relationship promotes all three innovation horizons--sustaining, disruptive, and transformational. Our experience in building such relationships at Georgia Tech indicates both parties can realize success when a range of enablers to industry-university interaction promote a range of innovation opportunities--basic and translational--over a long term partnerships. This systems-of-systems model will be presented as a general context, then generalized examples from Georgia Tech industry partnership efforts will be discussed to illustrate the model.
Applied Research Associates--Our team developed a system for DoD over 3 years to support real time decision and communication support among Burn Intensive Care Unit clinicians. This example will describe collaboration among 35 members from military healthcare professionals, to cognitive psychologists and software and machine learning developers.
HP Labs--In the Emerging Computer Lab within HP Labs, among other research areas we are involved in the areas of speech analysis and interpretation, audio signal processing in conjunction with machine learning. In this part of the webinar we will explore one research topic in audio processing that we undertook, after identifying the deficiencies on HP devices, and the challenges encountered during development. We also present examples of the solutions to overcome these challenges which have helped contribute towards a scalable deployment of the technology based off of this research.
Biography: Thomas A. (Tom) McDermott, Jr is a leader, educator, and innovator in multiple technology fields. He currently serves as Deputy Director of the Systems Engineering Research Center at Stevens Institute of Technology in Hoboken, NJ, as well as a consultant specializing in strategic planning for uncertain environments. He studies systems engineering, systems thinking, organizational dynamics, and the nature of complex human socio-technical systems. He teaches system architecture concepts, systems thinking and decision making, and the composite skills required at the intersection of leadership and engineering.
Tom has over 30 years of background and experience in technical and management disciplines, including over 15 years at the Georgia Institute of Technology and 18 years with Lockheed Martin. He is a graduate of the Georgia Institute of Technology, with degrees in Physics and Electrical Engineering. With Lockheed Martin he served as Chief Engineer and Program Manager for the F-22 Raptor Avionics Team, leading the program to avionics first flight. Tom was GTRI Director of Research and interim Director from 2007-2013. During his tenure the impact of GTRI significantly expanded, research awards doubled to over 300M dollars, faculty research positions increased by 60 percent, and the organization was recognized as one of Atlanta's best places to work. He also has a visiting appointment in the Georgia Tech Sam Nunn School of International Affairs. Tom is one of the creators of Georgia Tech's Professional Masters degree in Applied Systems Engineering and lead instructor of the Leading Systems Engineering Teams course.
Sunil Bharitkar received his Ph.D. in Electrical Engineering, minor in Mathematics from the University of Southern California in 2004 and is presently the speech-audio research Distinguished Technologist at HP Labs. He is involved in research in array signal processing, speech/audio analysis and processing, biomedical signal processing, and machine learning. From 2011-2016 he was the Director of Audio Technology at Dolby leading-guiding research in audio, signal processing, haptics, machine learning, hearing augmentation, &standardization activities at ITU, SMPTE, AES. He co-founded the company Audyssey Labs in 2002 where he was VP Research responsible for inventing new technologies which were licensed to companies including IMAX, Denon, Audi, Sharp, etc. He also taught in the Department of Electrical Engineering at USC. Sunil has published over 50 technical papers and has over 20 patents in the area of signal processing applied to acoustics, neural networks and pattern recognition, and a textbook, Immersive Audio Signal Processing, from Springer-Verlag.
Chris Nemeth is a Principal Scientist with Applied Research Associates, a 1200 member national science and engineering consulting firm. His recent research interests include technical work in complex high stakes settings, research methods
in individual and distributed cognition, and understanding how information technology erodes or enhances system resilience. He has served as a committee member of the National Academy of Sciences, is widely published in technical journals. Dr. Nemeth earned his PhD in human factors and ergonomics from the Union Institute and University in 2003, and an MS in product design from the Institute of Design at Illinois Institute of Technology in 1984.
His design and human factors consulting practice and his corporate career have encompassed a variety of application areas, including health care, transportation and manufacturing. As a consultant, he has performed human factors analysis and product development, and served as an expert witness in litigation related to human performance. His 26-year academic career has included seven years in the Department of Anesthesia and Critical Care at the University of Chicago Medical Center, and adjunct positions with the Northwestern University McCormick College of Engineering and Applied Sciences, and Illinois Institute of Technology. He is a Fellow of the Design Research Society, a Life Senior Member of the Institute of Electrical and Electronic Engineers and has served 8 years on the IEEE Systems, Man and Cybernetics Society Board of Governors. He retired from the Navy in 2001 at the rank of Captain after a 30-year active duty and reserve career.
More Info: Event number: 592 564 704, Event password: INCOSE115
Webcast: https://incoseevents.webex.com/incoseevents/onstage/g.php?MTID=ed47a65b08dbf33c5afed11b8656b48aaLocation: https://incoseevents.webex.com/incoseevents/onstage/g.php?MTID=ed47a65b08dbf33c5afed11b8656b48aa
WebCast Link: https://incoseevents.webex.com/incoseevents/onstage/g.php?MTID=ed47a65b08dbf33c5afed11b8656b48aa
Audiences: Everyone Is Invited
Contact: James Moore II
Event Link: Event number: 592 564 704, Event password: INCOSE115
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MS Group Advisement Session - NEW and CONTINUING CS/INF Students
Thu, Aug 16, 2018 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for NEW and CONTINUING graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2018 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: Ryan Rozan
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Viterbi New Student Welcome
Thu, Aug 16, 2018 @ 11:30 AM - 02:30 PM
Viterbi School of Engineering Career Connections, Viterbi School of Engineering Student Affairs
Receptions & Special Events
The annual Viterbi Undergraduate New Student Welcome will be held on Thursday, August 16th. We welcome Viterbi's incoming freshman and transfer students with food, fun, games, class picture, and an opportunity to meet with Viterbi affiliated student organizations. An invitation will be sent out directly to new Viterbi students with RSVP information. Hope to see you there!
Location: Engineering Quad
Audiences: Incoming Freshman and Transfer Students
Contact: Kaitlin Harada
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Viterbi New Student Welcome
Thu, Aug 16, 2018 @ 11:30 AM - 02:30 PM
Viterbi School of Engineering Career Connections, Viterbi School of Engineering Student Affairs
Receptions & Special Events
The annual Viterbi Undergraduate New Student Welcome will be held on Thursday, August 16th. We welcome Viterbi's incoming freshman and transfer students with food, fun, games, class picture, and an opportunity to meet with Viterbi affiliated student organizations. An invitation will be sent out directly to new Viterbi students with RSVP information. Hope to see you there!
Location: Engineering Quad
Audiences: Incoming Freshman and Transfer Students
Contact: Kaitlin Harada
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MS Group Advisement Session - NEW and CONTINUING CS/INF Students
Thu, Aug 16, 2018 @ 02:00 PM - 04:00 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for NEW and CONTINUING graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2018 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. This session is in room HAR-101.
Location: May Ormerod Harris Hall, Quinn Wing & Fisher Gallery (HAR) - 101
Audiences: Graduate
Contact: Ryan Rozan
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MS Group Advisement Session - NEW and CONTINUING CS/INF Students
Fri, Aug 17, 2018 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
Workshops & Infosessions
This group advisement session is for NEW and CONTINUING graduate students in the Computer Science / Informatics Master's programs. All incoming Fall 2018 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. This session is in room HAR-101.
Location: May Ormerod Harris Hall, Quinn Wing & Fisher Gallery (HAR) - 101
Audiences: Graduate
Contact: Ryan Rozan
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NL Seminar-Decipherment for Universal Language Tools A case study for Unsupervised Part of Speech Induction
Fri, Aug 17, 2018 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Ronald Cardenas, USC
Talk Title: Decipherment for Universal Language Tools A case study for Unsupervised Part of Speech Induction
Series: Natural Language Seminar
Abstract: Unsupervised Part of Speech induction can be viewed as a two-steps task. The first step infers a sequence of states, while the second step maps this sequence to an actual Part-of-Speech sequence at training or testing time. Hence, this last step requires reference tagged data, a luxury low-resource target languages might not have. In this talk, we present an alternative approach to the second step, modeling it as a decipherment problem in which the ciphered text is the sequence of states and the original text we want to recover is the POS sequence. This approach requires no reference data in the target language and allows to leverage POS sequences in much richer languages. Our experiments show that our approach benefits the most from simple strategies for inferring state sequences, such as Brown clustering. This allow our method to obtain reasonable performance in low-resource and limited-time scenarios.
Biography: Ronald Cardenas is a Master's student in the Language and Communication Technologies programme at Charles University in Prague. His research interests span morphological analysis and parsing of low-resource languages. At ISI, he works with Jonatan May on developing universal language tools.
Host: Nanyun Peng
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/
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NL Seminar-T1. Constraints for Transfer Learning for Machine Translation T2.SAY YES AND: BUILDING A SPECIALIZED CORPUS FOR DIGITAL IMPROVISED COMEDY
Fri, Aug 17, 2018 @ 03:00 PM - 04:00 PM
Information Sciences Institute
Conferences, Lectures, & Seminars
Speaker: Mozhdeh Gheini, Xinyu Wang , USC/ISI
Talk Title: T1. Constraints for Transfer Learning for Machine Translation T2.SAY YES-AND: BUILDING A SPECIALIZED CORPUS FOR DIGITAL IMPROVISED COMEDY
Series: Natural Language Seminar
Abstract: T1.Can we detect the parts responsible for a generic behavior in a model to transfer it to another? In this talk, we first see why this might be a good idea, especially for low resource machine translation. Then we focus on our approach to isolating a behavior. In our case, we specifically focus on coverage during machine translation. We present our results across different languages that show how neural models try to ensure coverage.
T2. In improvised comedy, saying yes, and.. is a rule of thumb that suggests that one person should accept the other person's offer yes, and then add related information on top of that and. Collecting a yes, and.. corpus is not only helpful for building an improv agent, but can also be used for building conversational skill training tool, improving a dialogue system, etc. I will discuss the methods we have used for building such a dataset, data we have got so far and future considerations.
Biography: Mozhdeh Gheini is a last semester Computer Science master's student at USC Viterbi School of Engineering. At ISI, she works on improving neural low-resource machine translation under the supervision of Jonathan May. She will be applying for Ph.D. programs this Fall.
Xinyu is a 2018 summer intern working with Dr. Jonathan May and Dr. Nanyun Peng on computerized improvised comedy. She will be joinging the Language Technologies Institute at Carnegie Mellon University in 2018 fall.
Host: Nanyun Peng
More Info: http://nlg.isi.edu/nl-seminar/
Location: Information Science Institute (ISI) - 11th Flr Conf Rm # 1135, Marina Del Rey
Audiences: Everyone Is Invited
Contact: Peter Zamar
Event Link: http://nlg.isi.edu/nl-seminar/