The following is the schedule of upcoming department seminars. Seminars will be added to the schedule throughout the year. All seminars are free of charge and are open to all members, affiliates, and colleagues of the university community. Seminars are typically held on Tuesday or Thursday at 1:00 pm. If you would like additional information or if you might be interested in presenting a seminar, please contact Jim Young or the Department of Computer Science.
Dr. Lorna GuseWhen: March 05, 2015 @ 1:00pm
Where: EITC E2-105
Dr. Lorna Guse
Title: Robot and Frank: PARO and Granddad
The movie, Robot and Frank features an aging, cantankerous ex-cat burglar (Frank Langella) who finds his zest for life renewed when he trains his robotic caretaker to help him commit heists. In contrast, our research at Deer Lodge Centre paired PARO, a robotic baby Harp Seal and older residents living with dementia in a series of studies examining the relationship between using PARO in situations with: resident and family involvement; resident agitation and anxiety; resident pain; and intergenerational relationships. Selected findings from the studies and some of the issues (ethical and infection control) related to the use of a “social commitment” robot with older adults will be explored. Below are the links to the movie trailer, Robot and Frank, and the Japanese nursing home where research with PARO began.
- Lorna Guse, RN, PhD, Associate Professor, College of Nursing, Faculty of Health Sciences
- Angela Osterreicher, BSc, MLS, Librarian, J.W. Crane Memorial Library, Deer Lodge Centre
- Kerstin Roger, PhD, Associate Professor, Faculty of Human Ecology
- Elaine Mordoch, RN, PhD, Associate Professor, College of Nursing, Faculty of Health Sciences
Dr. Cenk SahinalpWhen: March 12, 2015 @ 1:00pm
Dr. Cenk Sahinalp
Computational Biology Lab, Simon Fraser University
Title: High Throughput Algorithms for Big Data Genomics
Sequencing projects involving thousands of individual genomes are underway and the need for algorithmic speedup is bigger than ever. We will go through some of the algorithmic developments introduced by the Lab for Computational Biology at SFU to address challenges in big data genomics. These algorithms involve one or more techniques in data compression, streaming, memory hierarchy awareness and parallelization. Application areas range from read mapping to variant calling, novel isoform and fusion gene identification to clonality inference
S. Cenk Sahinalp is a Canada Research Chair in Computational Genomics at the School of Computing Science at Simon Fraser University and a Professor of Computer Science at Indiana University, Bloomington. He is also a researcher at the Vancouver Prostate Centre. Sahinalp is the director of the MADD-Gen Gradute program in Vancouver, the first bioinformatics program focusing on big data challenges in genomics and bioinformatics. Sahinalp received his B.Sc. in Electrical Engineering from Bilkent University and his Ph.D. in Computer Science from University of Maryland, College Park. His research focuses on computational genomics and biomolecular sequence analysis, RNA structure and interaction prediction and network biology.
Dr. Sushmita RoyWhen: March 13, 2015 @ 12:30pm
Where: EITC E2-165
Dr. Sushmita Roy
Biostatistics and Medical Informatics, University of Wisconsin, Madison
Title: Next generation regulatory network reconstruction: from yeast to mammals
Transcriptional regulatory networks are central to context-specific gene expression patterns. Such networks specify the connections among regulatory proteins such as transcription factors and signaling proteins to target genes. A central challenge in systems biology is to identify these networks and build predictive models of overall system state using these networks. With advances in genomics and efforts from several large consortia, we now have rich regulatory genomics datasets that measure different components of the regulation machinery in multiple cell types, tissues and species. A key challenge now is to systematically combine these datasets to gain insight into the regulatory networks that govern cellular state in complex eukaryotic systems.
Our research aims to develop novel computational methods based on machine learning to impose organizational constraints, such as modules, and integrate different types of regulatory genomic datasets to construct context-specific, predictive regulatory networks. In this talk, I will present some of our recent efforts to map these networks, starting with yeast S. cerevisiae as our test bed, and extending to mammalian regulatory networks for cell-fate specification. Our computational methods can be used to systematically identify regulatory networks in multiple species and provide testable hypotheses of how such networks govern downstream gene expression patterns.
Sushmita Roy is an assistant professor at the University of Wisconsin, Madison in the Biostatistics and Medical Informatics department, and faculty in the Systems biology Theme at the Wisconsin Institute for Discovery. Sushmita got her PhD in computer science from the University of New Mexico, and post-doctoral training at the Broad institute of MIT and Harvard. Sushmita is a recipient of an Alfred P. Sloan Research Fellowship on Computational and Evolutionary Molecular Biology and an NSF CAREER award.
Dr. Pradeepa YahampathWhen: March 19, 2015 @ 1:00pm
Dr. Pradeepa Yahampath
Electrical and Computer Engineering, University of Manitoba
Title: Hybrid Digital-Analog Coding For Mobile Multicast of Audio Visual Conten
Mobile multicast of audio and video content is currently one of the most sought after wireless services. When transmitting the same content to multiple mobile receivers which are subject to very different channel conditions, the bandwidth efficient approach would be to send a single scalable bit stream. However, conventional schemes such as layered scalable video coding is highly vulnerable to packet losses. Simultaneously realizing both bit-rate scalability and robustness to data losses is difficult within the current framework of video coding in the application layer and the separate channel error protection in the physical layer. In this talk, an emerging new approach to multicast of analog content such as audio and video is discussed which is inherently scalable and robust. This approach, referred to as hybrid digital-analog (HDA) coding, relies on the direct (uncoded) transmission of analog (audio or video) signal samples, along with a coded bit-stream over the wireless channel, thus integrating application layer source coding and physical layer channel coding. HDA coding allows each mobile receiver to obtain a quality of service commensurate with its specific instantaneous channel conditions from a single transmitted analog-digital signal. In this talk, both fundamental information theoretic considerations of HDA coding and recent advances in its practical implementation will be discussed.
Dr. Pradeepa Yahampath is an associate professor with the department of Electrical and Computer Engineering, University of Manitoba. He received M.Sc. degree in telecommunications from the Norwegian University of Science and Technology in 1995 and Ph.D. degree in electrical and computer engineering from University of Manitoba in 2001. He has held research positions in the Communications Group at UNIK, University Oslo, Norway during the 2007-2009 period. He has served in the technical program committees of a number of international conferences in the areas of communications and signal processing. He is a Senior Member of IEEE. His research interests include statistical signal processing in communication systems, vector quantization and its applications in signal processing and communications, multimedia coding, joint source-channel coding for wireless systems and networks, distributed coding for sensor networks, and signal processing and digital communication in smart-power grids.
Dr. Bertram UngerWhen: March 26, 2015 @ 1:00pm
Dr. Bertram Unger
Clinical Learning and Simulation Facility, University of Manitoba
Title: Hardware vs Software - Design and Evaluation of Temporal Bone Surgical Models
Current temporal bone surgical training focuses largely on apprenticeship models, supplemented by cadaveric dissection. Limited cadaveric supply, concerns regarding patient safety, and reductions in operative opportunities for resident staff, have led to the development of surgical simulations. The majority of such simulations, designed to teach critical surgical skills, rely on haptic technology and computerized depictions of temporal bone anatomy. Recent developments in rapid prototyping technology have allowed the creation of another form of simulation - drillable 3D models. Haptic models generally provide easy and inexpensive setup, interactive and modifiable anatomy, and objective metric analysis but present poor tactile realism. Printed models provide greater tactile realism but are not as amenable to metric analysis and may be more costly. Unfortunately there is no information on how these simulation modalities compare to each other or to currently accepted teaching methods.
In this talk we will review the state of the art in haptic and printed temporal bone simulation and discuss their respective advantages and disadvantages for surgical training. We will then describe the development of novel haptic and rapid-prototyped systems at the Laboratory for Surgical Modeling, Simulation and Robotics and present data from a recent study, comparing haptic and printed models to conventional cadaveric dissection and directly to each other. We will conclude with a description of a novel mixed-reality simulator currently under development which combines the advantages of haptic and printed simulations.
Dr. Bertram Unger holds undergraduate degrees in Medicine and Computer Engineering and a Medical Doctorate from the University of Manitoba. In 2008, he received his PhD. in Robotics from Carnegie Mellon University, followed by a Postdoctoral Fellowship with the Faculty of Bioengineering at the University of Pittsburgh. He is currently an Assistant Professor in the University of Manitoba's Faculty of Medicine and Director of the Laboratory for Surgical Modeling, Simulation and Robotics. He is also Research Director of the University’s Clinical Learning and Simulation Facility and he holds an adjunct appointment in Department of Mechanical Engineering. He is core faculty with the Biomedical Engineering Graduate Program and Chair of its curriculum committee. He also practices clinical medicine with the Section of Critical Care in the Department of Internal Medicine. Current research interests include medical simulation development and testing, using 3D printing, haptics and augmented reality.