Events for Thursday, May 31, 2018

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RF in Medicine: Current Status and Challenges of Antennas and Wireless Power

Room Number: BA 1180 Bahen Centre for Information Technology 40 St George St, Toronto, ON M5S 2E4

Thursday, May 31st at 4:00 p.m., Dr Yongxin Guo, National University of Singapore, Singapore, will be presenting a distinguished lecture: “RF in Medicine: Current Status and Challenges of Antennas and Wireless Power”. Day & Time: Thursday, May 31, 2018 4:00 p.m. ‐ 5:00 p.m. Speaker: Dr Yongxin Guo National University of Singapore, Singapore Location: Room Number: BA 1180 Bahen Centre for Information Technology 40 St George St, Toronto, ON M5S 2E4 Contact: George V. Eleftheriades Organizer: IEEE Toronto Electromagnetics & Radiation Chapter Abstract: Wireless power and data telemetry technologies for biomedical and healthcare applications have received a lot of attention recently. Numerous applications in medical diagnostics and therapeutics ranging from cardiac pacemakers to emerging devices in visual prosthesis, brain computer interfaces and body area networks have spurred electronic engineers to propose new wireless medical devices. In the meantime, the ageing population poses many challenges to healthcare systems, especially on chronic illness management. In this talk, I would mainly cover our recent research progress on wearable/implantable antennas and wireless power for biomedical applications. A few related ongoing biomedical projects for on-body and in-body applications will be addressed. In addition, I would also briefly introduce my other related research activities. Biography: Yong-Xin Guo received his Ph.D. degree from City University of Hong Kong in 2001. From September 2001 to January 2009, he was with the Institute for Infocomm Research, Singapore, as a Research Scientist. He joined the Department of Electrical and Computer Engineering, National University of Singapore (NUS), as an Assistant Professor in February 2009 and was promoted to a tenured Associate Professor in Jan 2013. He has authored or co-authored 206 international journal papers and ~200 international conference papers. Thus far, his publications have been cited more than 6200 times and the H-index is 44 (source: Google Scholar). He holds 8 granted/filed Patents in U.S. or China. His current research interests include antennas for wireless communications and biomedical applications, wireless power for biomedical and IoTs, and MMIC modelling and design. He has graduated 12 PhD students at NUS. Dr Guo was the General Chair/Co-Chair for AWPT 2017, ACES-China 2017, IEEE IMWS-AMP 2015 and IEEE IMWS-Bio 2013. He served as a Technical Program Committee (TPC) Co-Chair for IEEE IMWS-AMP 2017 and RFIT2009. He is serving as Associate Editors for IEEE Journal of Electromagnetics, RF and Microwave in Medicine and Biology, IEEE Antennas and Wireless Propagation Letters, and Electronics Letters. He was a recipient of the Young Investigator Award 2009, National University of Singapore. He received 2013 Raj Mittra Travel Grant Senior Researcher Award. He is an IEEE Fellow.

Big Data Based Recommendation Approaches for Healthcare

Room GB405, University of Toronto (Galbraith Building), 35 St George St., Toronto Ontario M5S 1A4

Thursday, May 31st at 6:00 p.m., Samee U. Khan, Associate Professor of Electrical and Computer Engineering at the North Dakota State University, will be presenting “Big Data Based Recommendation Approaches for Healthcare”. Day & Time: Thursday, May 31, 2018 6:00 p.m. ‐ 9:00 p.m. Speaker: Samee U. Khan Department of Electrical and Computer Engineering North Dakota State University Location: Room GB405, University of Toronto (Galbraith Building) 35 St George St., Toronto Ontario M5S 1A4 Contact: Dennis Cecic Organizer: IEEE Toronto Computer Society RVSP: https://events.vtools.ieee.org/m/162924 Fees: IEEE Members: Free Non-Member (Professional): $10 + 13% HST Abstract: Recommender systems have attained widespread acceptance and have attracted the increased attention by the masses for over a decade. Recommender systems alleviate the complexities of products and services selection tasks and are meant to overcome the issuesof information overload. Just like the recommender systems’ prospects in e-commerce and several other business domains,recommender systems have also been developed to offer recommendations about healthcare services and products. Considering the high volumes and dimensionality of healthcare data, utilization of efficient techniques to manage the big data is inevitable. In this talk, we describe the need and rationale for using the big data enabled techniques for healthcare data. As case studies, we will detail our work on developing recommendation systems for: (a) health insurance products recommendation, (b) health expert recommendation from social media, (c) identification of influential doctors from Twitter, and (d) disease risk assessment services. During the discussion on the cases studies, we will discuss the following issues that are particular to the recommender systems: (a) cold start, (b) long-tail problem, and (c) scalability. Biography: Samee U. Khan received a BS degree in 1999 from Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, Pakistan, and a PhD in 2007 from the University of Texas, Arlington, TX, USA. Currently, he is Associate Professor of Electrical and Computer Engineering at the North Dakota State University, Fargo, ND, USA. Prof. Khan’s research interests include optimization, robustness, and security of systems. His work hasappeared in over 300 publications. He is on the editorial boards of leading journals, such as IEEE Access, IEEE Communications Surveys and Tutorials, and IEEE IT Pro. He is an ACM Distinguished Speaker, an IEEE Distinguished Lecturer, a Fellow of the Institution of Engineering and Technology (IET, formerly IEE), and a Fellow of the British Computer Society (BCS).