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 (Sorry, you need javascript to view this email address. )

CSEE Professor Tülay Adali and Professor Kelly Westlake from the University of Maryland School of Medicine received an award from the joint UMBC-UMB Research and Innovation Partnership Seed Grant Program for a project  that ultimately will improve the recovery of stroke victims. The new joint UMBC-UMB Seed Grant Program pairs primary investigators from UMBC and the University of Maryland, Baltimore to conduct research as a team. Successful partners are offered research funding of up to $75,000 over twelve months to pursue their collaboration.

Nearly 800,000 U.S. citizens have a stroke each year, making it the leading cause of long-term disability. Treatment for stroke victims is mainly targeted towards residual functional deficits, especially regaining hand functions. Their project (“Independent Vector Analysis to Investigate Cognitive Neural Networks after Stroke: A Comparison between Two Rehabilitation Interventions”) will have a direct impact on stroke rehabilitation through objective evaluation of the two main treatment paradigms currently in use: unimanual (involving one hand) and bimanual (involving both hands) training. The evaluation will use the new class of medical image analysis techniques, independent vector analysis (IVA) algorithms, developed by Dr. Adali and her research group. The new class of IVA algorithms successfully captures subject variability and perform significantly better than the approaches traditionally used for the problem.

The initial results of the project demonstrate the advantages using IVA for the problem and will be presented this month at the 48th Annual Conference on Information Sciences and Systems in Princeton, NJ. The PIs are preparing two journal submissions, one based on the methods developed for the task and a second one emphasizing clinical significance of the results. These results will also provide the preliminary data for the proposal that Professors Adali and Westlake plan to submit to the NIH later this year.

CSEE Professor Tülay Adali and Professor Kelly Westlake from the University of Maryland School of Medicine received an award from the joint UMBC-UMB Research and Innovation Partnership Seed Grant Program for a project  that ultimately will improve the recovery of stroke victims. The new joint UMBC-UMB Seed Grant Program pairs primary investigators from UMBC and the University of Maryland, Baltimore to conduct research as a team. Successful partners are offered research funding of up to $75,000 over twelve months to pursue their collaboration.

Nearly 800,000 U.S. citizens have a stroke each year, making it the leading cause of long-term disability. Treatment for stroke victims is mainly targeted towards residual functional deficits, especially regaining hand functions. Their project (“Independent Vector Analysis to Investigate Cognitive Neural Networks after Stroke: A Comparison between Two Rehabilitation Interventions”) will have a direct impact on stroke rehabilitation through objective evaluation of the two main treatment paradigms currently in use: unimanual (involving one hand) and bimanual (involving both hands) training. The evaluation will use the new class of medical image analysis techniques, independent vector analysis (IVA) algorithms, developed by Dr. Adali and her research group. The new class of IVA algorithms successfully captures subject variability and perform significantly better than the approaches traditionally used for the problem.

The initial results of the project demonstrate the advantages using IVA for the problem and will be presented this month at the 48th Annual Conference on Information Sciences and Systems in Princeton, NJ. The PIs are preparing two journal submissions, one based on the methods developed for the task and a second one emphasizing clinical significance of the results. These results will also provide the preliminary data for the proposal that Professors Adali and Westlake plan to submit to the NIH later this year.

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.

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, Sorry, you need javascript to view this email address.

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, Sorry, you need javascript to view this email address.

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, Sorry, you need javascript to view this email address.

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, Sorry, you need javascript to view this email address.

The National Center for Women & Information Technology (NCWIT) has selected CSEE professor Marie desJardins as one of four awardees of the 2014 NCWIT Undergraduate Research Mentoring Award. The award comes with a gift to UMBC of $5,000, sponsored by AT&T that can be used to further Professor desJardins mentoring activities. The award will be presented at the 2014 NCWIT Summit which will take place at the Newport Beach Marriott Hotel & Spa in Newport Beach, California in May 2014.

NCWIT is a non-profit community of more than 500 prominent corporations, academic institutions, government agencies, and non-profits working to increase women’s participation in technology and computing. Their  annual NCWIT Undergraduate Research Mentoring Award recognizes U.S. Academic Alliance representatives for their outstanding mentorship, high-quality research opportunities, recruitment of women and minority students, and efforts to encourage and advance undergraduates in computing-related fields.