CSCE 791 - Seminar on Advances in Computing

Course Information:

  • Course Name: CSCE 791 - Seminar on Advances in Computing
  • Semester: Fall 2017
  • Instructor: Greg Gay
  • Lecture Hours: Friday, 2:20 - 3:10 PM, 2A14 Swearingen Engineering Center

Course Description

CSCE 791 is a colloquium series, consisting of talks or seminars given by invited speakers from our department and other departments or universities. The primary goal of this course is to expose students to the "state-of-art" research and development in a variety of computing-related disciplines. CSCE 791 is a great opportunity to hear from academia and industry about the challenges facing our society, and the work being performed to address these challenges.

This content is made available in the interest of sharing educational material with any who might find it useful. This page is updated periodically, and may not be in synch with the course itself. For current course students, the latest content, assignment submission, and discussion forums are available on Moodle.

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Documents

Lectures

  • August 25, 2017 - Geometric Approaches to Derandomizing Parallel Matching and Matroid Algorithms
    • Speaker: Dr. Stephen Fenner, University of South Carolina

    • Abstract: I will describe a cluster of recent results that help to derandomize some parallel algorithms for graphs and matroids. Specifically, it has been shown that the problem of finding a perfect matching in a graph is in the complexity class quasi-NC, that is, it is solvable in polylogarithmic time (that is, logO(1)n time) time using quasipolynomially many processors (that is, 2logO(1) n many processors). This was first shown for bipartite graphs by F, Gurjar, and Thierauf in 2015, and a proof for general graphs was announced last spring by Svensson and Tarnawski (to appear in FOCS 2017). In the interim, Gurjar and Thierauf (2016) gave a quasi-NC algorithm for the Linear Matroid Intersection problem. All these results use similar techniques that are based in geometry---for example, discovering lower dimensional faces of the perfect matching polytope of a graph. I will emphasize these geometrical techniques in the talk.

    • Bio: Stephen Fenner is a professor of Computer Science and Engineering at the University of South Carolina. His research interests are in theoretical computer science and include computational complexity, computability, algorithms, and quantum informatics.

  • September 1, 2017 - An Application of Natural Language Processing: Analyzing student essays as a big-data project
    • Speaker: Dr. Duncan Buell, University of South Carolina

    • Abstract: First year students at most large universities take required courses whose purpose is to teach them to write prose essays and make arguments. We have acquired more than 7000 pairs of draft-and-final essays from USC and have been analyzing them. We are not trying to do “machine grading” of essays as an AI project. Rather, we are trying to identify features of writing that can be quantified and thus processed with programs as a big-data analysis. We are interested in the extent to which students revise their draft essays to become final versions. And we are interested in comparing our student writing against other genres of writing. For this last we use the Corpus of Contemporary American English (COCA) as source data. The COCA is a corpus of more than 500 million words of text separated into genres of academic writing, magazine writing, transcripts of spoken English and interviews, and such. Our eventual goal is to situate student writing relative to other genres and thus to help with improving the pedagogy of teaching writing; knowing what the students are actually writing now is key to knowing how to get them to write formal prose effectively. Programming is done in Python. Part of speech tagging is done using the CLAWS package from the University of Lancaster in the UK. Sentence parsing is done using the package from Dan Jurafsky’s lab at Stanford.

    • Bio: Duncan A. Buell is a Professor in the Department of Computer Science and Engineering at the Unviversity of South Carolina. His Ph.D. is in mathematics from the University of Illinois at Chicago (1976). He was from 2000 to 2009 the department chair at USC, and in 2005-2006 was interim dean. He has done research in document retrieval, computational number theory, and parallel computing, and has more recently turned to digital humanities as one of the emerging “marketplace” applications for computing. He is engaged with First Year English at USC on the analysis of freshman English essays, searching for an understanding of actual student writing in an effort to improve pedagogy for first year English instruction. He has team taught four times with Dr. Heidi Rae Cooley on the presentation of unacknowledged history on mobile devices, and he and Dr. Cooley are actively engaged in ways to go beyond text to fully enable the use of visual media in mobile applications that present humanities content, especially content that might normally remain unacknowledged by institutional authority.

  • September 8, 2017 - Security Challenges for the Internet of Things: A Semantics-Based View
    • Speaker: Dr. Csilla Farkas, University of South Carolina

    • Abstract: Are you living in a smart home? Are you using smart devices to monitor your health? Is your organization considering to increase automation for sensing and controlling operations? While the concept of Internet of Things (IoT) may mean different things to different people, there is a common theme: the need for cybersecurity. The key security challenges are focused on three areas: 1) device vulnerabilities, 2) communication security and trust, and 3) data integrity, security, and privacy. In this talk I present a semantics-based approach to support IoT data integration and security.

    • Bio: Csilla Farkas is a Professor in the Department of Computer Science and Engineering and Director of the Center for Information Assurance Engineering at the University of South Carolina. Dr. Farkas’ research interests include information security, data inference problem, financial and legal analysis of cyber crime, and security and privacy on the Semantic Web. silla Farkas received her PhD from George Mason University, Fairfax. In her dissertation she studied the inference and aggregation problems in multilevel secure relational databases. She received a MS in computer science from George Mason University and BS degrees in computer science and geology from SZAMALK, Hungary and Eotvos Lorand University, Hungary, respectively.

  • September 15, 2017 - Human attribute recognition by refining attention heat map
    • Speaker: Dr. Song Wang, University of South Carolina

    • Abstract: Most existing methods of human attribute recognition are part-based and the performance of these methods is highly dependent on the accuracy of body-part detection, which is a well known challenging problem in computer vision. In this talk, I will introduce a new method to recognize human attributes by using CAM (Class Activation Map) network, as well as an unsupervised algorithm to refine the attention heat map, which is an intermediate result in CAM and reflects relevant image regions for each attribute. The proposed method does not require the detection of body parts and the prior correspondence between body parts and attributes. The proposed methods can achieve comparable performance of attribute recognition to the current state-of-the-art methods.

    • Bio: Song Wang received the Ph.D. degree in electrical and computer engineering from the University of Illinois at Urbana–Champaign in 2002. He received his M.E. and B.E. degrees from Tsinghua University in 1998 and 1994, respectively. In 2002, he joined the Department of Computer Science and Engineering in University of South Carolina, where he is currently a Professor and the director of the Computer Vision Lab. His current research interest is focused on computer vision, image processing and machine learning, as well as their applications to materials science, medical imaging, digital humanities and archaeology. He has published more than 100 research papers in journal and conferences, including top venues like CVPR, ICCV, NIPS, IJCAI, TPAMI, IJCV and TIP. He is currently serving as the Publicity/Web Portal Chair of the Technical Committee of Pattern Analysis and Machine Intelligence of the IEEE Computer Society, and an Associate Editor of Pattern Recognition Letters. He is a senior member of IEEE.

  • September 22, 2017 - TBD
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  • September 29, 2017 - TBD
    • Speaker: Dr. Matthew Brashears, University of South Carolina (Sociology)

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  • October 6, 2017 - TBD
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  • October 13, 2017 - TBD
    • Speaker: Dr. Jason O'Kane, University of South Carolina

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  • October 27, 2017 - TBD
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  • November 3, 2017 - TBD
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  • November 10, 2017 - TBD
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  • November 17, 2017 - TBD
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  • December 1, 2017 - TBD
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  • December 8, 2017 - TBD
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