RESEACH KEYNOTE SERIES


Jason Nieh

Jason Nieh is a Professor of Computer Science and Co-Director of the Software Systems Laboratory at Columbia University. He has served as a consultant to both government and industry, including as the technical advisor to nine States on the Microsoft Antitrust Settlement, and as an expert witness before the US International Trade Commission. He was previously Chief Scientist of Cellrox and Desktone, acquired by VMware. Professor Nieh has made research contributions in software systems across a broad range of areas, including operating systems, virtualization, thin-client computing, cloud computing, mobile computing, multimedia, web technologies, and performance evaluation. Technologies he developed are now widely used in Android, Linux, and other major operating system platforms. Honors for his research work include the Sigma Xi Young Investigator Award, awarded once every two years in the physical sciences and engineering, a National Science Foundation CAREER Award, a Department of Energy Early Career Award, five IBM Faculty Awards and two IBM Shared University Research Awards, six Google Research Awards, and various best paper awards, including those from MobiCom, SIGCSE, SIGMETRICS, and SOSP. A dedicated teacher, he received the Distinguished Faculty Teaching Award from the Columbia Engineering School Alumni Association for his innovations in teaching operating systems and for introducing virtualization as a pedagogical tool. Professor Nieh earned his B.S. from MIT and his M.S. and Ph.D. from Stanford University, all in Electrical Engineering.

   Title of The Talk:  Recent Trends in Virtualization


Dan Rubenstein

Dan Rubenstein is an Associate Professor in the Department of Computer Science at Columbia University. He received a B.S. degree in mathematics from M.I.T., an M.A. in math from UCLA, and a PhD in computer science from University of Massachusetts, Amherst. His research interests are in network technologies, applications, and performance analysis. He was an editor for IEEE/ACM Transactions on Networking, was general chair of IFIP Performance 2017, program chair of IFIP Networking 2010 and ACM Sigmetrics 2011, and has received an NSF CAREER Award, IBM Faculty Award, the Best Student Paper award from the ACM SIGMETRICS 2000 conference, and Paper awards from the IEEE ICNP 2003 Conference, ACM CoNext 2008 Conference, and IEEE Communications 2011. He spent 2011 at Google, and in 2012 was the original Chief Scientist at Infinio, a company founded on his research at Columbia.

Title of The Talk: Addressing the Communications Needs of First Responders in Large-Scale Emergencies

Abstract: The past two decades have yielded an enormous shift in how well connected and reliable our communications systems allow us to be. Nonetheless, first responders still have grave concerns about maintaining effective communication during large-scale emergencies during which dependable, well-provisioned infrastructure may not be fully operational. While some of the problems are policy-driven, there remain areas ripe for research that can help address staying connected through non-conventional means. In this talk, I will discuss Columbia's ERICA project which is designed to address several areas in which research can affect the technological future of first response, and focus in on some particular networking issues that we are attempting to address.


Yang (Richard) Yang

Yang (Richard) Yang is the Professor of Computer Science and Electrical Engineering at Yale University, where he founded and leads the Laboratory of Networked Systems (LANS). Dr. Yang's research is supported by both US government funding agencies and leading industrial corporations, and spans areas including computer networks, mobile computing, wireless networking, and network security. His work has been implemented/adopted in products/systems of major companies (e.g., AT&T, Alcatel-Lucent, Cisco, Google, Microsoft, Youku), and featured in mainstream media including Economist, Forbes, Guardian, Chronicle of Higher Education, Information Week, MIT Technology Review, Science Daily, USA Today, Washington Post, and Wired, among others. His awards include a CAREER Award from the National Science Foundation and a Google Faculty Research Award. Dr. Yang's received his B.E. degree in Computer Science and Technology from Tsinghua University (1993), and his M.S. and Ph.D. degrees in Computer Science from the University of Texas at Austin (1998 and 2001).


Changxi Zheng

Changxi Zheng is currently an Associate Professor in the Computer Science Department at Columbia University.He is also co-directing Columbia's Computer Graphics Group (C2G2) in Columbia Vision and Graphics Center (CVGC). He received his Ph.D. from Cornell University with the Best Dissertation Award and his B.S. from Shanghai Jiaotong University. He currently serves as an associated editor of ACM Transactions on Graphics. He was a Conference Chair for SCA in 2017, has won an NSF CAREER Award, and was named one of Forbes’ “30 under 30” in science and healthcare in 2013. He received the Best Paper Awards from 2016 SCA and 2017 UIST, among others. Changxi's current research is on the boundary between computational methods and physical devices. He is particularly interested in developing simulation methods for complex physical systems, the computational models for optical and acoustic sensing, and the computational design of structures and materials.


Pierre Larochelle

Pierre Larochelle (Ph.D., Mechanical Engineering, University of California at Irvine) is the Department Head and a Professor of Mechanical Engineering at the South Dakota School of Mines & Technology. Previously he served as an Associate Dean and Professor of Mechanical Engineering at the Florida Institute of Technology. His research focuses on the design of complex robotic mechanical systems and enabling creativity and innovation in design. He is the founding director of the Robotics and Spatial Systems Laboratory (RASSL), has over 100 publications, holds two US patents, and serves as a consultant on robotics, automation, machine design, creativity & innovation, and computer-aided design. He serves on the Executive Committee of ASME’s Design Engineering Division and will serve as Chair of the Division in 2018-2019. He serves on ABET’s Engineering Accreditation Commission (EAC) and as an ABET Accreditation Visit Team Chair. Moreover, he currently serves as the Chair of the U.S. Committee on the Theory of Mechanisms & Machine Science and represents the U.S. in the International Federation for the Promotion of Mechanism & Machine Science (IFToMM) (2016 – 2020). He has served as Chair of the ASME Mechanisms & Robotics Committee (2010-2014) and as an Associate Editor for the ASME Journal of Mechanisms & Robotics (2013 – 2016, 2017 – present), the ASME Journal of Mechanical Design (2005 – 2011), and for Mechanics Based Design of Structures & Machines (2006 – 2013). He is a Fellow of the American Society of Mechanical Engineers (ASME), a Senior Member of IEEE, and a member of Tau Beta Pi, Pi Tau Sigma, ASEE, and the Order of the Engineer.

Title of The Talk: The role of digital communication in manufacturing industry 4.0

Abstract: The industrial revolution of the 19th century brought forth a step change in manufacturing processes from manual human labor to hands-off dedicated production equipment. This paradigm remained intact until the 1970’s during which robotics, i.e. flexible automation was introduced. From the 1970’s until now we have seen a harmonious balance between the flexible automation provided by robots and the rigid automation provided by dedicated production machines. Today, a new paradigm is emerging; a quartet of robots, machines, humanoids, and humans working together to produce high quality products that are customized to satiate the consumer’s demands. This talk will explore the roles that digital communications have to play in this new paradigm and the opportunities they present for digital communication researchers and practitioners.


Rajeev Narayanan

Rajeev Narayanan is currently a Research Scientist in the Healthcare & Life sciences division of IBM Thomas J. Watson Research Center, Yorktown Heights, NY USA. He is also an adjunct faculty at the University of Connecticut, Stamford. Prior to his position at IBM, from 2012-mid 2017, he was an Assistant Professor at SUNY, New Paltz in the department of Computer Engineering. Dr. Narayanan received his Ph.D. in Electrical and Computer Engineering from Concordia University. During that time he was also a Research Assistant in Hardware Verification Group, Concordia University from 2007-2012. Prior to that, he worked as Staff R&D Engineer in IBM Microelectronics from 1999-2006.
His research areas include Healthcare invasive/non-invasive systems, Cognitive IoT, Reconfigurable computing, Analog & mixed-signal modeling, and Formal Verification.He is the Faculty Advisor of IEEE Mid-Hudson Section and has authored many papers and patents. He has received numerous awards and grants such as NSF AMP/CSTEP Summer Research Program Award, State University of New York in 2016, Dean’s Summer Research Award, State University of New York in 2013-2014, Summer Undergraduate Research Award, State University of New York, 2013.


Robert Moskovitch

Robert Moskovitch is a faculty at the department of Software and Information Systems Engineering at Ben Gurion University, in which he is heading the Complex Data Analytics Lab.He did his post doc fellowship at the department of Biomedical Informatics at Columbia University. He is a member of BGU’s Zlotowsky Center for Neuroscience, and BGU’s @Cyber security center. Prior to that, he headed several Research and Development projects in Information Security at Deutsche Telekom Innovation Laboratories. He is an Academic Editor at PLOS ONE,
and has served on several journal editorial boards, as well as on program committees of several conferences, such as ACM KDD and IEEE ICHI and workshops in Information Security and Biomedical Informatics, as well as edited recently special issues at JASIST and JBI. He published more than seventy peer reviewed papers in leading journals and conferences, such as IEEE ICDM, Data Mining and Knowledge Discovery, KAIS, JAMIA, JBI and more, several of which had won best-paper awards. His lab focuses mainly on the development of Temporal Data Analytics methods, and their applications to the biomedical domain, but not exclusively. Dr. Moskovitch’s lab is funded by Microsoft, IBM, Amdocs, and governmental agencies, and collaborates with scientists from Columbia University, Mount Sinai, Peking University, IIT New Delhi and more. He is the Analytics Program Chair of IEEE International Conference of Healthcare Informatics 2018 (NYC).

Title of the Talk: Connecting the dots longitudinally in Biomedical Data using Temporal Abstraction and Time Intervals Analytics

Abstract: Analysis of heterogeneous multivariate time stamped data is one of the most challenging topics in data science in general, and in healthcare analytics specifically. Time stamped data can be sampled in a fixed frequency, commonly when measured by electronic means, but also in a non fixed frequency, often when made manually - a typical situation in biomedical data, whether fast data such as in ICU, or slow such as generally in EHR. Additionally, raw temporal data can represent durations of a continuous or nominal value represented by time intervals. In this talk the idea of transforming time point series into meaningful symbolic time intervals, using a process often called Temporal Abstraction, will be presented to bring all the temporal variables, having various representations, into a uniform representation. Then, KarmaLego, a fast time intervals mining method for the discovery of non-ambiguous Time Intervals Related Patterns (TIRPs) represented by Allen's temporal relations, will be presented. TIRPs can be used for several purposes: temporal knowledge discovery, and classification of multivariate temporal data, using the KarmaLegoS framework, in which TIRPs are used as classification features. To increase the classification accuracy a novel supervised Temporal Discretization for Classification (TD4C) method will be introduced, including an evaluation on three real life datasets from the biomedical domain. Finally, results of the use of TIRPs for outcomes prediction in patient data, such as clinical procedures or conditions, will be demonstrated on Columbia University Medical Center EHR data.


Xia Zhou

Xia Zhou  is an Associate Professor in the Department of Computer Science at Dartmouth College. She received her PhD at UC Santa Barbara in 2013. Her general research interests are in mobile systems and wireless networking. She is a recipient of the Karen E. Wetterhahn Memorial Award for Distinguished Creative and Scholarly Achievement in 2018 and named as N2Women: Rising Stars in Networking and Communication in 2017. She has also won the Sloan Research Fellowship in 2017, NSF CAREER Award in 2016, and Google Faculty Research Award in 2014.

Title of The Talk: Battery-Free Eye Tracking

Abstract: Continuous eye tracking is critical for identifying health and cognitive issues, and assessing the effectiveness of clinical treatments. It is also crucial for the development of human-to-computer interaction by allowing hands-free, attentive user interfaces. Existing wearable eye trackers commonly use cameras, entailing a prohibitive cost and consuming a nontrivial amount of power.
In this talk I will present a minimalist approach to eye tracking, which replaces cameras with low-cost, small photodiodes to significantly reduce the cost and power consumption. The key rationale stems from pupil's light absorption property, which causes changes in reflected light around the eye as the pupil moves or its size varies. Such changes in reflected light can be sensed by a circular array of photodiodes around the eye and utilized to infer pupil's position and size. I will present our designs of eye trackers following this principle for virtual reality and regular eyeglasses, and conclude with discussions on future work.


In cheol Jeong

In cheol Jeong is currently an assistant research professor in the department of Material Science and Engineering, and in the inHealth Measurement Corps at Johns Hopkins University. Dr. Jeong received his PhD in Advanced Biomedical Engineering from Yonsei University. His post-doctoral fellowships were in the department of Anesthesiology and Pain Medicine at Seoul National University Hospital, in the division of Geriatric Medicine and Gerontology at Johns Hopkins University, and in the Johns Hopkins individualized Health Initiative. He has researched and developed medical devices and systems for ubiquitous healthcare applications; specifically, in the design and development of electronic and data- based biomedical systems. He also has contributed to a variety of research topics in heterogeneous
clinical and administrative datasets to improve health care quality and patient safety, and to facilitate the comprehensive patient-centered health care delivery model. His current research interests are the design and development of patient’s individualized medical systems, real-time safety monitoring systems, and health assessment systems.

Title of The Talk: Towards an individual digital health state profile

Abstract: The goal of individualized medicine is to provide the right care to the right person at the right time. The major mission involves creating and disseminating tools that harness scientific knowledge to individualize care and improve health for all. These tools improve decision-making in the prevention and treatment of a range of conditions. In all scientific endeavors, the plan realizes that each health decision should be fully informed by scientific knowledge. The goal of my research is to provide expertise in the development of point-of-care devices and algorithms to measure analytes and biomarkers from patient and sensors for real-time monitoring of health state. These measurements provide the basis for meta-analysis within specific disease types; laying a foundation for improved clinical decisions. My research is especially interested in enhancements that will lower costs, reduce measurement times, or improve sensitivity. Thus, in my research, innovative new applications are developed for existing sensors because many sensor technologies can be repurposed for applications in individualized health. The ongoing research currently includes meeting with clinicians and primary care providers to identify measurement needs that will improve medical decision-making, building a measurement portal to catalog the state-of-the-art technologies, and developing target specifications. The presentation will cover the Hopkins and Mount Sinai projects that are likely to meet the goals of U.S. Digital Health IT. The impact of research activities is introduced with projects on individual health profiling of both in-patients and out-patients.

 


Antwan D. Clark

Antwan D. Clark is originally from Chicago, Illinois, where he earned his Bachelor of Science (BS) degree in Electrical Engineering from Illinois Institute of Technology (IIT) in 1995. From there, he received his Master of Science (MS) and Doctorate (PhD) degrees in Mathematics from Rensselaer Polytechnic Institute (RPI) in 1997 and 2002, respectively. After receiving his PhD, Dr. Clark worked in several engineering and technical management positions throughout the Department of Defense (DoD), where he was a subject matter expert (SME) for the DoD and Intelligence Community in Executive forums and working groups in the areas of Radio Frequency (RF) spectrum and system architecture design. It was also during this time where he because a Licensed Professional Engineer (PE) granted by the State of Maryland and the National Council of Engineering and Engineering Surveyors (NCEES).

On the research side, Dr. Clark is a Research Scientist at the Laboratory for Physical Sciences – a DoD affiliated research laboratory with the University of Maryland College Park (UMCP) where he has been over the past decade. Additionally, he holds faculty appointments at West Virginia University (in the Computer Science and Electrical Engineering Department) and Johns HopkinsUniversity (in the Applied Mathematics and Statistics Department). He also holds professional memberships within IEEE and the National Society of Professional Engineers (NSPE). Furthermore, he has served on several technical conference program committees, proposal review committees, and Executive Working Groups in the areas of biometrics and security. His current research areas include biometrics (face and iris recognition), image processing, queuing systems, and reliability analysis (focusing on cyber-behavior).

Title of The Talk: Analyzing Threats in Supercomputing Environments: A Reliability Analysis Perspective

Abstract: High performance computing (HPC) systems are contributing to rapid scientific discovery and global economic prosperity. However, troubleshooting these systems is difficult due to their complex infrastructure and heterogeneity, which also make these systems susceptible to various threats including those caused by users. The goal of this talk is to present the overall problem of of human computer interaction (HCI) and systems health within supercomputing environments from two perspectives: 1.) characterizing failure observations and 2.) resource allocation. First, we will examine the HPC ecosystem, where we will draw a connection between threats and use-case scenarios. Next, we pay special attention to examining the impact of user threats within these environments. Here, some recent research avenues are presented where we examine their theoretical and practical fidelity. Finally, this talk concludes with some additional explorations in this realm as well as how these techniques are also being applied to other distributed frameworks.

 

Important Deadlines

Full Paper Submission:22nd August 2018
Acceptance Notification: 22nd September 2018
Final Paper Submission:7th October 2018
Early Bird Registration: 20th October 2018
Presentation Submission: 28th October 2018
Conference: 8th-10th November 2018

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Announcements


• Conference Proceedings will be submitted for publication at IEEE Xplore Digital Library


•Best Paper Award will be given for each tracks


• There will be two workshops on-
i. Data Analysis and ii. IoT Workshop - Concepts to Implementation on Nov 10, 2018


• Conference Record No 44053