Learning and Optimization for Complex Dynamic Networks: The
Cases of Future Power Systems and Cognitive Wireless Networks

Dr. Seung-Jun Kim, University of Minnesota

11:45-12:45 Tuesday, 11 March 2014, ITE325b, UMBC

With enormous growth in sensing and communication capabilities as well as processing power to analyze collected data, we are witnessing exciting opportunities in diverse disciplines to study complex interactions of networked entities. The overarching theme is to explore cutting-edge computational intelligence tools from signal processing, machine learning, optimization, and control to make sense of amassed data and exploit complex interactions to make significant real-world impacts. In this talk, I will make cases for two prime examples, namely, future power systems and cognitive wireless networks. The role of contemporary tools including online learning, sparse and low-dimensional models, distributed and robust algorithms, will be emphasized.

Seung-Jun Kim received his B.S. and M.S. degrees from Seoul National University in Seoul, Korea in 1996 and 1998, respectively, and his Ph.D. from the University of California at Santa Barbara in 2005, all in electrical engineering. From 2005 to 2008, he worked for NEC Laboratories America in Princeton, New Jersey, as a Research Staff Member. He is currently with the Department of Electrical and Computer Engineering and the Digital Technology Center at the University of Minnesota, where he is a Research Associate Professor and a Research Associate. His research interests lie in applying signal processing, optimization, and machine learning techniques to various application domains including wireless communication and networking and smart power grids.

Host: Tinoosh Mohsenin,

From Terabyte-Sized Stem Cell Images to Knowledge

Peter Bajcsy, PhD
Information technology Laboratory
National Institute of Standards and Technology

10:00am Monday, 10 March 2014, ITE 346, UMBC

This talk will present the computational challenges and approaches to knowledge discovery from terabyte-sized images. The motivation comes from experimental systems for imaging and analyzing human pluripotent stem cell cultures at the spatial and temporal coverage of colonies that lead to terabyte-sized image data. The objective of such an unprecedented cell study is to characterize pluripotency of stem cell colonies over time at high statistical significance in order to understand the stem cell culture quality parameters and guide a repeatable growth of high quality stem cell colonies. The terabyte- sized images represented a stem cell line that was engineered to produce green fluorescent protein (GFP) under the influence of Oct4 promoter and then imaged in a mosaic of contiguous frames covering approximately 180 square millimeters, over five days under both phase contrast and GFP channels.

We overview multiple computer and computational science problems related to correcting (flat-field, dark current and background), stitching, segmenting, tracking, re-projecting and then representing large images for interactive visualization and sampling in a web browser. We researched extensions to Amdahl’s law for Map-Reduce computations, established benchmarks for image processing on a Hadoop platform, and introduced cluster node utilization coefficients for modeling memory demanding computations running on a computer cluster/cloud. The theoretical aspects of algorithmic complexity and cluster utilization at terabyte scale are extended to the experimental aspects of efficient image representation and client-server workload distribution in the context of visualization interactivity and image sampling. We report such experimental results for the NIST extensions to the Deep Zoom paradigm. The presentation will conclude with illustrations of enabled stem cell discoveries and collaboration opportunities to create a reference resource not only for cell biologists but also for computer scientists focusing on terabyte scale image analyses.

Peter Bajcsy received his Ph.D. in Electrical and Computer Engineering in 1997 from the University of Illinois at Urbana-Champaign and a M.S. in Electrical and Computer Engineering in 1994 from the University of Pennsylvania. He worked for machine vision, government contracting, and research and educational institutions before joining the National Institute of Standards and Technology (NIST) in 2011. At NIST, he has been leading a project focusing on the application of computational science in biological metrology, and specifically stem cell characterization at very large scales. Peter’s area of research is large-scale image-based analyses and syntheses using mathematical, statistical and computational models while leveraging computer science fields such as image processing, machine learning, computer vision, and pattern recognition. He has co-authored more than more than 24 journal papers and eight books or book chapters, and close to 100 conference papers.

Host: Yelena Yesha ()

Predictive Analytics for Insider Threats

Ben Shariati
Visiting Lecturer & Interim Assistant CYBR GPD

4:00pm Wednesday, 5 March 2014, ITE325b

This talk will discuss how using operational cyber analytics for predictive security intelligence support a powerful defensive cybersecurity capability. Specifically, I will share elements of my commercial research on how organizations can predict malicious behavior (both user and digital) on their networks by incorporating tailored algorithms and artificial intelligence capabilities as part of an overall cybersecurity sensor architecture. Additionally, this talk will briefly discuss the impact that mobile devices have on the insider threat vulnerability within the government and private sector.

Ben Shariati is a Ph.D. candidate in Information Assurance/Cybersecurity at the George Washington University, where his dissertation work examines the analysis and management of cybersecurity concerns of critical infrastructures. His research and professional interests include mobile device security, emerging technology evaluation, risk analysis, audit, and compliance. For AY13-14, Mr. Shariati is a visiting lecturer and Interim Assistant Director of the Graduate Cybersecurity Program overseeing program activities at The Universities at Shady Grove. In addition to teaching several courses at UMBC, Mr. Shariati has taught graduate cybersecurity courses at George Washington University and undergraduate technical certification classes Hagerstown Community College.

Mr. Shariati is a technology and business executive with over 20 years of experience specializing in strategic and operational cybersecurity program activities and development for international organizations. His career highlights include serving as a lead enterprise security architect at the Federal Reserve Bank in Richmond, VA, a cybersecurity advisor at Cell Trust Corporation, and Technology Advisor/Cybersecurity Architect for the United Nations Pan American Health Organization.

CSEE Professor Samuel Lomonaco will give an invited talk on “The Strange World of Quantum Computing” as art of the NASA Goddard Engineering Colloquium Series at 3:00pm Monday, March 10 in the Building 3 Auditorium.

Abstract: Quantum computers have the potential to greatly increase computational power beyond the capabilities of conventional computers by exploiting the bizarre quantum properties of the subatomic world. This talk will give an introductory overview of quantum computing in an intuitive and conceptual fashion. No prior knowledge of quantum mechanics will be assumed.

Exploiting Probabilistic Information for Spectrum Sensing
and Utilization: towards Efficient Wireless Coexistence

Prof. Xiangwei Zhou
University of Illinois, Carbondale

11:45am Friday, 7 March 2014, ITE 325b, UMBC

With the rapid growth of wireless devices and applications, the electromagnetic radio spectrum is considered to be in short supply. To overcome spectrum scarcity and satisfy emerging user demands, cognitive radio, which can sense and adapt to the surrounding spectral environment, has been introduced to enhance the utilization of the spectrum. However, it is a challenging task to design a robust and cost-effective system involving identification and reuse of spectrum opportunities changing over time, frequency, and space. In this talk, I will focus on efficient spectrum sensing and utilization techniques for dynamic spectrum access. In particular, I will emphasize the importance of exploiting probabilistic information unique to such a system. I will present novel techniques from the perspectives of both a single user and a multi-user network. In the end, I will discuss further extension of the work to enable the coexistence of heterogeneous wireless networks.

Xiangwei Zhou received his Ph.D. degree in Electrical and Computer Engineering from Georgia Institute of Technology, Atlanta, Georgia, in 2011. He received his M.S. degree in Information and Communication Engineering from Zhejiang University, Hangzhou, China and his B.S. degree in Communication Engineering from Nanjing University of Science and Technology, Nanjing, China, in 2007 and 2005, respectively. Since 2013, Dr. Zhou has been with the Department of Electrical and Computer Engineering at Southern Illinois University Carbondale as an Assistant Professor. Prior to that, he was a Senior Systems Engineer with Marvell Semiconductor, Santa Clara, California, from 2011 to 2013. Dr. Zhou’s general research interests include wireless communications and statistical signal processing, with current emphasis on cognitive radio and heterogeneous coexistence, cyber-physical systems, and cross-layer optimization. He is now serving as an Editor for IEEE Transactions on Wireless Communications.

Host: Mohamed Younis,

Toward strong, usable access control for personal data

Michelle Mazurek
Carnegie Mellon University

1:00pm Thursday, 6 March 2014, ITE 325b, UMBC

Users create, store and access a lot of personal data, both on their devices and in the cloud. Although this provides tremendous benefits, it also creates risks to security and privacy, ranging from the inconvenient (private photos posted around the office) to the serious (loss of a job; withdrawal of college admission). Simply refusing to share personal data is not feasible or desirable, but sharing indiscriminately is equally problematic. Instead, users should be able to efficiently accomplish their primary goals without unnecessarily compromising their privacy. In this talk, I describe my work toward developing usable access-control mechanisms for personal data. I review the results of three user studies that provided insight into users’ policy needs and preferences. I then discuss the design and implementation of Penumbra, a distributed file system with built-in access control designed to support those needs. Penumbra has two key building blocks: semantic-tag-based policy specification and logic-based policy enforcement. Our results show that Penumbra can enforce users’ preferred policies securely with low overhead.

Michelle Mazurek is a Ph.D. candidate in Electrical and Computer Engineering at Carnegie Mellon University, co-advised by Lujo Bauer and Greg Ganger. Her research interests span security, systems, and HCI, with particular emphasis on designing systems from the ground up for usable security. She has worked on projects related to usable access control, distributed systems, and passwords.

Host: Penny Rheingans,

Due to uncertainty about the weather, this talk has
been postponed and will be rescheduled soon

Underwater Acoustic Communication and
Networking for Ocean Sampling

Dr. Aijun Song

Assistant Research Professor
College of Earth, Ocean, and Environment
University of Delaware, Newark, DE 19716

Noon – 1:00pm Monday, 3 March 2014, ITE325b, UMBC

On our planet Earth, the marine ecosystem is undergoing significant changes due to human activities and natural processes. These changes call for enhanced capabilities to sample and communicate in the oceans. With this background, underwater acoustic communication has attracted much attention across multiple disciplines, as a means to access oceanographic data in real-time and to support navigation of underwater vehicles. This talk will focus on my recent efforts in 1) characterization and modeling of the ocean environment as a communication medium, 2) development of high data rate acoustic modems, both software and hardware, and 3) application of underwater acoustic communication networks in ocean sampling.

Dr. Aijun Song received his Ph.D. degree in the Department of Electrical Engineering, University of Delaware, Newark, Delaware in 2005. From 2005 to 2008, he was a postdoctoral research associate at the College of Earth, Ocean, and Environment (CEOE), University of Delaware. During this period, he was also an Office of Naval Research (ONR) postdoctoral fellow, supported by the special research award in the Ocean Acoustics program. Since 2008, he has been an Assistant Research Professor of the CEOE, University of Delaware. His research interests include advanced signal processing and communication techniques for mobile radio frequencies as well as for underwater acoustic environments, underwater acoustic signal propagation, and the general area of ocean sampling.

Grant English, VP Engineering, Advertising Technologies at AOL Networks (aka Advertising.com) in Baltimore will visit and give a talk from Noon to 1:00pm on Monday, 24 February 2014 in Lecture Hall 7 (ITE104) at UMBC. In his talk, he will describe AOL’s Adtech advertisement serving platform, its underlying system architecture, and what his development team does.

He will also dive deep into how new online and mobile technologies makes money, focusing it to computer science and engineering students. There will be a free lunch.

Please RSVP for the event here.

Linguistic and System Support for Structured Parallel Programming

Dr. I-Ting Angelina Lee
Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology

12:00-1:00 Thursday, 20 February 2014, ITE 325b, UMBC

Parallel programming is hard, due to issues such as scheduling and synchronization. Most parallel programs today deal with these issues using low-level system primitives such as pthreads, locks, and conditional variables. Although these low-level primitives are flexible, they, like goto statements, lack structure and make it difficult for the programmer to reason locally about the program state. Just as the use of goto has been mostly deprecated in favor of structured control constructs, we can simplify parallel programming by replacing these low-level primitives with linguistics that enable well-structured parallel programs.

To enable structured parallel programming is not merely a matter of linguistic design. The underlying system must also efficiently support the linguistics. In this talk, I will describe my work on pipeline parallelism, a parallel pattern commonly used in streaming applications, as an example of linguistics for structured parallel programming. I will also draw examples from my research to demonstrate how novel mechanisms in operating systems and hardware, not just the runtime, can help provide efficient support for the linguistics.

I-Ting Angelina Lee is a postdoctoral associate in the Computer Science and Artificial Intelligence Laboratory at MIT, working with Prof. Charles E. Leiserson. Her areas of interest include designing linguistics for parallel programming, developing runtime system support for multithreaded software, and building novel mechanisms in operating systems and hardware to efficiently support parallel abstractions. Her work on “memory-mapped reducers” won best paper at SPAA 2012. Intel has released an experimental branch of Cilk Plus that incorporates support for parallel pipelining based on her work. She received her Ph.D. from MIT in 2012 under the supervision of Prof. Charles E. Leiserson. She received her Bachelor of Science in Computer Science from UC San Diego in 2003.

Host: Tim Oates,

Understanding Cybersecurity Market Dynamics

John Pescatore
SANS Institute

1:00-3:00 Tuesday, 4 March 2014
Suite 130, bwtech@UMBC, 5520 Research Park Drive, UMBC

There is no single cybersecurity market, and the factors that drive business decisions around security practices and purchases are complex and continually evolving. Based on more than 20 years of experience with cybersecurity technology and startups, this presentation will provide an understanding of the dynamics of the various markets that make up cybersecurity, as well as provide predictions of merging demand areas.

John Pescatore is SANS Director of Emerging Security Trends. He joined SANS in January 2013 after 14 years as Gartner’s lead security analyst. Before coming to Gartner he lead consulting groups at two early Internet security IPOs (Trusted Information Systems and Entrust) and spent 11 years in telecoms and computer security at GTE. He began his career at NSA and the US Secret Service. Follow him as @john_pescatore on Twitter or via his Security Trend Line blog on the SANS website.

Send your RSVP for this event to Allie Gold at BWTech.