Title: Networking outside the line - an invitation

Abstract: The current state of wireless networking is both encouraging and discouraging for an academic researcher. The wireless internet is a major success story: permanent wireless connectivity became an inextricable part of our life. At the same time, a researcher might feel nostalgia for the early days of the internet when her next paper might shape the just-emerging field. It turns out that many components of the early architecture of the internet were so well engineered, that protocols standardized in the 1980s (TCP/IP, Ethernet) still underpin the networking stack of our computers, phones and IoT devices. The huge installed base of these protocols also introduce inertia. Recent work in the field happens more often in large companies and standardization organizations rather than in university research labs.

So, where should an academic researcher turn to find topics that pose both theoretical challenges and tackle real-life problems? Without endeavoring to offer a complete answer, in this talk I intend to investigate some avenues that consider networking outside the line: unusual scenarios, non-standard performance metrics and requirements that are tighter or looser than usually considered in the field. I illustrate some of these examples with specific research directions pursued by my group.

Biography: Damla Turgut is Charles Millican Professor of Computer Science at University of Central Florida. She received her PhD from the Computer Science and Engineering Department of University of Texas at Arlington. Her research interests include wireless ad hoc, sensor, underwater and vehicular networks, cloud computing, smart cities, IoT-enabled healthcare and augmented reality, as well as considerations of privacy in the Internet of Things. She is also interested in applying big data techniques for improving STEM education for women and minorities. Her recent honors and awards include the Women of Distinction Award by the UCF Faculty Excellence Center for Success of Women Faculty, UCF Research Incentive Award, the University Excellence Award in Professional Service and being featured in the UCF Women Making History series. Dr. Turgut serves on several editorial boards and program committees of prestigious ACM and IEEE journals and conferences. She is a senior member of IEEE, a member of ACM and the Upsilon Pi Epsilon honorary society. Her research has been funded through grants from National Science of Foundation, Department of Energy, US Army RDECOM, Florida Center for Cybersecurity, as well as industry grants.

Prof. Huan Liu

Title: Big Social Media Data and Its Challenges for Machine Learning

Abstract:  “Big data is the new oil.” Social media data opens the door for interdisciplinary research and allows researchers to collectively study large-scale human behavior otherwise impossible. The study of social media data brings out new challenges for machine learning and data mining. In this talk, we examine some critical issues related to big social media data such as how to make `big’ data bigger, how to protect a user’s privacy without the loss of service utility, and how to
evaluate machine learned results without ground truth and at scale. With more data and newer tools, we are better than ever equipped to answer challenging and novel research questions and advance data science with ever evolving data.  

Biography: Dr. Huan Liu is a professor of Computer Science and Engineering at Arizona State University. He was recognized for excellence in teaching and research in Computer Science and Engineering at Arizona State University. His research interests are in data mining, machine learning, social computing, and artificial intelligence, investigating problems that arise in real-world applications with high-dimensional data of disparate forms. His well-cited publications include books, book chapters, encyclopedia entries, as well as conference and journal papers. He is a textbook co-author of Social Media Mining: An Introduction by Cambridge University Press. He is a founding organizer of the International Conference Series on Social Computing, Behavioral-Cultural Modeling, and Prediction, and Chief Editor of Data Mining and Management in Frontiers in Big Data. He is a Fellow of ACM, AAAI, AAAS, and IEEE. 

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Biography: He is graduated from the Middle East Technical University (METU), Department of Mechanical Engineering in 1992. He received his master's degree in Mechanical Engineering from Middle East Technical University (METU) in 1995 and a PhD from the Middle East Technical University, Department of Computer Engineering in 2004. He holds a PhD in Internet of Things in the Department of Information Technologies at Wageningen University. The defense of his thesis titled "Integrated Architecture of Internet of Things Systems ”was delivered in 2018 in the Netherlands.