Oscar Chaparro from the University of Texas at Dallas will give a talk on Thursday March 28, 2019 in the Storey Innovation Center (Room 2277) from 10:15 am - 11:15 am. Abstract: User-written bug reports are the main information source for software developers to triage and fix the reported software bugs. Unfortunately, many bug reports are unclear, ambiguous, and/or miss critical information. In consequence, developers are often unable to reproduce the bugs, let alone fix them in the code. Current bug reporting technology, which is mostly passive and does not verify the information provided by the users, provides little help in improving the quality of bug reports. This presentation focuses on my research aimed at improving the quality of bug reports and bug resolution tasks that rely on bug reports. The presentation includes summaries of my prior research, describing: (1) empirical work on the discovery of discourse patterns used by reporters to describe bugs; (2) an automated approach for detecting missing information in bug reports; and (3) the use of query reduction to improve bug localization and duplicate bug report detection. The presentation will also present my current work on providing automated feedback to reporters on the quality of the steps to reproduce in their bug reports, and will conclude with my long-term research plans for transforming bug reporting and resolution via intelligent and interactive conversation systems. Short bio: Oscar Chaparro is a Ph.D. candidate in Software Engineering at the University of Texas at Dallas, advised by Dr. Andrian Marcus. His research interests lie in software maintenance and evolution. His current research aims at improving the quality of bug reports written by end users and assisting software developers during bug triage and resolution. He has authored several publications in top software engineering venues, such as ESEC/FSE, and obtained the IEEE TCSE Distinguished Paper Award at ICSME’17. He served on the organizing and program committee of the DySDoc3 workshop in 2018. Oscar received his B.Eng. and M.Eng. degrees from Universidad Nacional de Colombia and has four years of industry experience in software research and development.

Thursday March 21, 2019 in the Storey Innovation Center (Room 2277) from 10:15 am - 11:15 am. Abstract In smart cities, location-aware services that inspect the future locations of moving objects became an integral part with the spread of location sensing devices (e.g., in-car gps, smart phones, smart watches). These services play a vital role in many applications such as traffic management, mobile advertising, ride hailing, and map routing. In this talk, I will present my vision for smart location-aware services, and I will walk through some of my contributions in this domain. I will focus on the data management with an eye on the analytic aspects of my solutions. Bio Abdeltawab Hendawi is a Postdoc Research Associate in Computer Science at the University of Virginia. He obtained his MSc and PhD in Computer Science and Engineering from the University of Minnesota, Twin Cities. His research interests are centered on big data management and analytics with more focus on smart cities related applications. His work has been recognized by a number of awards, including the Best Paper Award at ACM SIGSPATIAL MobiGIS 2012; Best Design/Plan Poster Award and Best Overall Poster Award at the U-Spatial Symposium 2013; Best Demo Paper Award at ACM SIGSPATIAL 2014; Data Science Research Fellowship at the University of Washington 2014; Best and Second Best Demo Paper Awards at IEEE MDM 2015; Hobby Postdoc Research Fellowship at the University of Virginia 2015; Blue Sky Ideas Award 2016 and Best Runner-up Vision Paper Award at ACM SIGSPATIAL 2016; Best Poster Award at the UVa Research Symposium 2018; and Best Demo Paper Award Runner-up at ACM SIGSPATIAL 2018. Dr. Hendawi is the founding co-chair of the IEEE Big Spatial Data workshop 2016 to 2018.

SEMINAR RICHARD CARLIN, PH.D. HEAD, SEA WARFARE AND WEAPONS DEPARTMENT Engineering and Innovation at the ONR; Interests and Processes Tuesday, February 12, 2019 Bert Storey Innovation Center, Rm. 1400 550 Assembly St Columbia, SC 29201 11:30 am – 12:30 pm Dr. Richard T. Carlin is department head of ONR's Sea Warfare and Weapons Department at the Office of Naval Research (ONR). As department head, he overseas a broad range of science and technology (S&T) programs for surface ships, submarines, and undersea weapons with an annual budget of approximately $500million per year. Carlin entered the Senior Executive Service in January 2002 and has 14 years of federal service. Prior to his current position as department head, Carlin was the director for the Undersea Weapons and Naval Materials Division with responsibilities in undersea weapons and countermeasures, advanced energetics, structural materials, materials for power systems, acoustic transducers, maintenance reduction technologies, and blast mitigation materials. During his career at ONR, he also served as the acting chief scientist in 2004 and as director for the Mechanics and Energy Conversion Division from 2001 to 2005. Prior to his appointment as a division director, Carlin was the program officer for Electrochemistry S&T and Undersea Weapons Propulsion with programs covering numerous electrochemical and thermal power technologies. Additionally, Carlin serves as the Navy S&T executive on numerous Navy, Department of Defense, and interagency energy advisory groups, including the Navy’s Task Force Energy Executive Steering Committee, DDR&E’s Energy Security Task Force, and the Hydrogen and Fuel Cell Interagency Task Force. He also serves as a U.S. panel member on the NATO RTO Applied Vehicle Technology Panel, and is a member of the Department of the Navy Awards Review Panel Before joining ONR in August 1997, Carlin held several positions in academia, industry, and government. From 1995 to 1997, he was a senior scientist at Covalent Associates, Inc., performing contract research in areas of lithium batteries, supercapacitors, and ionic liquids catalysis. From 1992 to 1995, Carlin held the position of Electrochemistry Division chief at the Frank J. Seiler Research Laboratory (FJSRL) located at the U.S. Air Force Academy in Colorado Springs, Colo. At FJSRL, he led research on the use of ionic liquids as electrolytes for batteries, supercapacitors, and metal-alloy electrodepositions, and as solvents for gas absorption and catalysis. Carlin was an assistant professor of chemistry at the University of Alabama in Tuscaloosa from 1989 to 1992 where he taught both undergraduate and graduate level course and directed a research program in the study and application of ionic liquids as solvents and electrolytes. From 1982 to 1985, he was employed at Air Products and Chemicals as a senior research chemist carrying out research on the use of ionic liquids as gas-separation membranes. He received his Bachelor of Science in honors chemistry from the University of Alabama in 1977, and his doctorate degree in inorganic chemistry from Iowa State University in 1982. His thesis work at Iowa State focused on the synthesis, characterization, and structure of air-sensitive metal-metal bonded clusters of molybdenum and tungsten. Carlin received his training in electrochemistry as a postdoctoral fellow with Prof. Robert A. Osteryoung at the State University of New York at Buffalo. Carlin has published more than 100 technical papers and one book chapter, and he is a co-inventor on seven U.S. patents. He has given numerous presentations including invited talks at international venues in Japan, France, Turkey, Crete and Scotland. Carlin was awarded the Department of the Navy Meritorious Civilian Service Medal in August 2008. In January 2001, he received Assistant Secretary of the Navy (Research Development, & Acquisition) Awards for the Rapid Transition of Foreveready Missile Battery for Strategic System Programs and for Lithium-Ion Polymer Battery for Advanced Seal Delivery System. He was awarded the Chief of Naval Research’s Award of Merit for Group Achievement in August 2000 for Superior Group Effort While Serving on the ONR Diversity Committee. Additionally, his discovery of a novel battery technology was recognized with the U.S. Air Force Materiel Command S&T Achievement Award in 1993.

Prof. Amit P. Sheth Director, Kno.e.sis Center of Excellence, Wright State University Abstract: During a WEF2019 conversation that also included Satya Nedella (Microsoft CEO), Steven Pagliuca (CEO of Bain Capital) said: “Every company now is an AI company. The industrial companies are changing, the supply chain...every single sector, it’s not only tech.” In tandem with 55% global growth rate, South Carolina companies are also undergoing AI-driven transformation. This provides an exciting context for UofSC to offer regional, national, and global leadership in AI. UofSC’s AI Institute can provide the nerve center of a campus-wide effort, resulting in highly sought-after graduates, research prominence, and technological innovations with significant economic impact. The detailed nature of the AI Institute would evolve through extensive conversations across the campus with other stakeholders. In this talk, I seek to share some principles, defining characteristics, and the steps the AI Institute can take to convert the vision into reality. I will present the following details:

• Planned subareas of research focus and prominence with an eye on regional economic impact and international research recognition
• Expected core and affiliated faculty size/composition, achieved via recruiting exceptional talent; robust multidisciplinary collaborations with most colleges across campus as well as industry and public partners; and a strong industry network to benefit students
• External funding to power the growth – types of funds and funding sources,
• Outcomes, impacts, and success measures: student success, research prominence, per capita faculty funding growth, faculty recognition, technology-driven economic impact, and improving Carnegie R1 standing and CSE standing.
• Recent AI success has been due to unprecedented computational power enabling the training of deep neural networks. I will argue that future successes will be due infusing knowledge in the learning process and using semantic – cognitive – perceptual computing, which I will illustrate by an example research and application effort in personalized digital health.

Date and Time: Monday, February 11, 10:00 am – 11:00 am. Location: Storey 2277

Speaker: Christian Kaestner Affiliation: Carnegie Mellon University Location: Innovation Center, Room 2277 Time: Jan 25 (11am-12) Abstract: Breaking the API of a package can create severe disruptions downstream, but package maintainers have flexibility in whether and how to perform a change. Through interviews and a survey, we found that developers within a community or platform often share cohesive practices (e.g., semver, backporting, synchronized releases), but that those practices differ from community to community, and that most developers are not aware of alternative strategies and practices, their tradeoffs, and why other communities adopt them. Most interestingly, it seems that often practices and community consensus seems to be driven by implicit values in each community, such as stability, rapid access, or ease to contribute. Understanding and discussing values openly can help to understand and resolve conflicts, such as discussions between demands for more stability and a pursuit of frequent and disruptive innovations. Bio: Christian Kästner is an associate professor in the School of Computer Science at Carnegie Mellon University. He received his PhD in 2010 from the University of Magdeburg, Germany, for his work on virtual separation of concerns. For his dissertation he received the prestigious GI Dissertation Award. His research interests include understanding collaboration in open source and correctness and understanding of systems with variability, including work on implementation mechanisms, tools, variability-aware analysis, type systems, feature interactions, empirical evaluations, and refactoring.

DISSERTATION DEFENSE Department of Computer Science and Engineering University of South Carolina Author : Bridgette Parsons Advisor : Dr. Jose Vidal Date : Dec 14th, 2018 Time : 1:30 pm Place : Meeting room 2267, Innovation Center Abstract Modeling believable human behavior for use in simulations is a difficult task. It requires a great deal of time, and frequently requires coordination between members of different disciplines. In our research, we propose a method of partially automating the process, reducing the time it takes to create the model, and more easily allowing domain experts that are not programmers to adjust the models as necessary. Using Agent-Based modeling, we present MAGIC (Models Automatically Generated from Information Collected), an algorithm designed to automatically find points in the model's decision process that require interaction with other agents or with the simulation environment and create a decision graph that contains the agent's behavior pattern based upon raw data composed of time-sequential observations. We also present an alternative to the traditional Markov Decision Process that allows actions to be completed until a set condition is met, and a tool to allow domain experts to easily adjust the resulting models as needed. After testing the accuracy of our algorithm using synthetic data, we show the results of this process when it is used in a real-world simulation based upon a study of the medical administration process in hospitals conducted by the University of South Carolina's Healthcare Process Redesign Center. In the healthcare study, it was necessary for the nurses to follow a very consistent process. In order to show the ability to use our algorithm in a variety of situations, we create a video game and record players' movements. However, unlike the nursing simulation, the environment in the game simulation is more prone to changes that limit the appropriate set of actions taken by the humans being modeled. In order to account for the changes in the simulation, we present a simple method using the addition of a hierarchy of rules with our previous algorithm to limit the actions taken by the agent to ones that are appropriate for the current situation. In both the healthcare study and the video game, we find that there are multiple distinct patterns of behavior. As a single model would not accurately represent the behavior of all of the humans in the studies, we present a simple method of classifying the behavior of individuals using the decision graphs created by our algorithm. We then use our algorithm to create models for each cluster of behaviors, producing multiple models from one set of observational data. Believability is highly subjective. In our research, we present methods to partially automate the process of producing believable human agents, and test our results with real-world data using focus groups and a pseudo-Turing test. Our findings show that under the right conditions, it is possible to partially automate the modeling of human decision processes, but ultimately, believability is greatly dependent upon the similarity between the viewer and the humans being modeled.

Speaker: Hessam Babaee, Ph.D. Location: Innovation Center, Room 2277 Dec. 10, 13:00--14:00 Abstract:Highly convective thermo-fluid systems have a difficult phenomenon to predict: transient instabilities. While these instabilities have finite lifetimes, they can play a crucial role either by altering the system dynamics through the activation of other instabilities or by creating sudden nonlinear energy transfers that lead to extreme responses. However, their essentially transient character makes their description a particularly challenging task. We develop a minimization framework that focuses on the optimal approximation of the system dynamics in the neighbourhood of the system state. This minimization formulation results in differential equations that evolve a time-dependent basis so that it optimally approximates the most unstable directions. Several thermo-fluid demonstration cases will be presented that shows the performance of the presented method. Bio: Dr. Hessam Babaee is an expert in the area of hydrodynamic instability, uncertainty quantification, reduced-order modeling and high performance computing. He is currently a tenure-stream Assistant Professor in Swanson School of Engineering at University of Pittsburgh and a Research Scientist in Mechanical Engineering Department at Massachusetts Institute of Technology (MIT). Prior to joining University of Pittsburgh, he was a Postdoctoral Associate at MIT. He received his PhD in Mechanical Engineering and a Masters degree in Applied Mathematics from Louisiana State University both awarded in 2013.

Dr. Yi Wang from the Department of Mechanical Engineering, University of South Carolina will give a talk on Friday Dec. 7th in the Storey Innovation Center (Room 2277) from 13:00 - 14:00. Abstract: In this seminar a framework based on the incremental proper orthogonal decomposition (iPOD) and the data mining method to perform integrated analysis on large-scale computational data will be presented for targeted data visualization, discovery, and learning. Four key components will be introduced, including (1) iPOD based on the mean value and the subspace updating method to incrementally reduce data dimensions, decouple the time-averaged and time-varying flow structures, and extract coherent structures and modes in massive Computational Fluid Dynamics (CFD) data; (2) data mining to classify the flow regions of similar dynamic characteristics and identify the candidate and global ROIs (GROIs) for focused analysis; (3) feature detection to capture flow features of interest and determine ultimate ROIs (UROIs); and (4) selective storage and targeted visualization of data in UROIs. Case studies on vortex and shock wave detection that are of significant interest to aerospace and defense applications will be presented to demonstrate the framework. Computational performance of the framework in terms of data volume, reduction ratio, resource usage, and storage requirements will also be discussed. Our quantitative results clearly show that iPOD is able to process large datasets that overwhelm the traditional batch POD leading to 4-16X data reduction in the temporal domain through spectral projection. By data mining 50% to 70% of the spatial domain with high probability of flow feature occurrence is identified as candidate GROIs for efficient, confined feature detection. Key features in the UROI consisting of only 2% to 30% of the original data are successfully captured by our feature detection algorithms, and can be selectively stored and visualized for targeted discovery and learning. In contrast to batch-POD, iPOD reduces physical memory usage by more than 10X and processing time by up to 75% and is far more appropriate for large data analytics. Biography: Yi Wang obtained his B.S. and M.S. in Machinery and Energy Engineering from Shanghai Jiao Tong University, P.R.China in 1998 and 2000, respectively; and his Ph.D. in Mechanical Engineering from the Carnegie Mellon University in 2005. Currently he is an associate professor of mechanical engineering and is the principal investigator (PI) of the Integrated Multiphysics & Systems Engineering Laboratory (iMSEL) at the University of South Carolina. He has served as a PI or a Co-PI on multiple DoD-, MDA-, NASA-, and NIH-funded projects to develop advanced methodologies and techniques in computational and data-enabled science and engineering (CDS&E), including reduced order modeling, data reduction, large-scale and/or real-time data analytics, hierarchical system-level simulation, and system engineering. The applications of these technologies span spacecraft and missile thermal analysis, aeroservoelasticity and aerothermoservoelasticity, massive computational data management, real-time flight load data processing, integrated multi-scale fluidics systems (design, fabrication, and experimentation) for environmental monitoring, biodefense, and regenerative medicine. He has coauthored 4 book chapters, and 80 journal and conference publications. He is also the co-inventor of 5 patents.

Nov 26th 6pm EST – 9pm EST M. Bert Storey Engineering and Innovation Center 550 Assembly St, Columbia, SC 29201 (Room 1400) 6:30pm: I don’t think that person requires introductions, but here it is. His name is Scott McNealy. Scott McNealy is an outspoken advocate for personal liberty, small government, and free-market competition. In 1982, he co-Founded Sun Microsystems and served as CEO and Chairman of the Board for 22 years. He piloted the company from startup to legendary Silicon Valley giant in computing infrastructure, network computing, and open source software. 7:30pm: Bob Cooper. CEO of local company Swampfox but with great history for example Bob was the CTO of Conita, a company focused on creating software based “Personal Virtual Assistants” – think Apple Siri but 15 years ago.

Scott McNealy (@ScottMcNealy)

Co-Founder, Former Chairman of the Board, and CEO, Sun Microsystems, Inc. Co-Founder, and Board Member, Curriki Co-Founder, and Executive Chairman of the Board, Wayin Board Member, San Jose Sharks Sports and Entertainment Scott McNealy is an outspoken advocate for personal liberty, small government, and free-market competition. In 1982, he co-Founded Sun Microsystems and served as CEO and Chairman of the Board for 22 years. He piloted the company from startup to legendary Silicon Valley giant in computing infrastructure, network computing, and open source software. Today McNealy is heavily involved in advisory roles for companies that range from startup stage to large corporations, including Curriki and Wayin. Curriki (curriculum + wiki) is an independent 501(c)(3) organization working toward eliminating the education divide by providing free K-12 curricula and collaboration tools through an open-source platform. Wayin, the Digital Campaign CMS platform enables marketers and agencies to deliver authentic interactive campaign experiences across all digital properties including web, social, mobile and partner channels. Wayin services more than 300 brands across 80 countries and 10 industries. Scott McNealy is an enthusiastic ice hockey fan, and an avid golfer with a single digit handicap. He resides in California with his wife, Susan, and they have 4 sons. BA, Harvard, 1976 MBA, Stanford, 1980

Bob Cooper, CEO

Bob Cooper is the CEO of Swampfox Technology. Swampfox specializes in Call Center automation and is the software automating many of the transactions that many of the largest cable, energy and heath care companies in the US. Prior to starting Swampfox, Bob was Chief Architect at Avaya and was in charge of their call center self-service platform offer including Voice/Experience Portal, ICR and OneX Speech. During his time at Avaya this self-service platform grew to become the #1 selling IVR platform in the US. Prior to this Bob was the CTO of Conita, a company focused on creating software based “Personal Virtual Assistants” – think Apple Siri but 15 years ago. Bob holds many patents in the area of computer architecture and voice user interface design. He received his undergraduate and graduate engineering degrees from the University of Florida and teaches as electrical engineering as needed at the University of South Carolina. He’s married and has four children.