Abstract: U.S. National Science Foundation (NSF) Program Director Roger Mailler shares knowledge and NSF resources with students at higher education. The NSF Computer and Information Science and Engineering at NSF supports investigator-initiated research and education in all areas of computer and information science and engineering, fosters broad interdisciplinary collaboration, helps develop and maintain cutting-edge national cyberinfrastructure for research and education, and contributes to the development of a computer and information technology workforce with skills necessary for success in the increasingly competitive global market. In this talk, Dr. Mailler shares opportunities in STEM Career Pathways for undergraduate students

Speaker Bio: Dr. Roger Mailler is a Program Director in National Science Foundation’s Division of Information and Intelligent Systems (IIS) under the Directorate for Computer and Information Science and Engineering (CISE). He leads many NSF-funded research projects in Robust Intelligence (RI) program within the IIS Division that aim to explore foundational computational research needed to understand and develop systems that can sense, learn, reason, communicate, and act in the world using AI, Machine Learning, Computer Vision, Natural Language Technologies, and Computational Neuroscience. Dr. Mailler is also a Professor of Computer Science at the University of Tulsa, published more than 60 articles in leading journals and conference proceedings in the area of multiagent systems, distributed problem solving, constrained optimization, and computational neuroscience. He received his bachelors degree at the State University of New York and Ph.D. at the University of Massachusetts, respectively.

Zoom Meeting ID: 922 3579 4660 / Passcode: 076165

https://tcnj.zoom.us/j/96195035078?pwd=OTZ4V3VkZHFPZ1p6aGphTnAwUXZ0QT09

Abstract: Several approaches exist for simulating building properties (e.g. temperature, noise) and human occupancy (e.g. movement, actions) in an isolated fashion, providing limited ability to represent how environmental features affect human behaviour and vice versa. To systematically model building-occupant interactions, several requirements must be met, including the modelling of (a) interdependent multi-domain phenomena ranging from temperature and sound changes to human movement, (b) high-level occupant planning and low-level steering behaviours, (c) environmental and occupancy phenomena that unfold at different time scales, and (d) multiple strategies to represent occupancy using established models. In this work, we propose an integrated platform that satisfies the aforementioned requirements thus enabling the joint simulation of building-occupant interactions. To this end, we combine the benefits of a model-independent, discrete-event, general-purpose framework with an established crowd simulator. Our platform provides insights on a building’s performance while accounting for alternative design features and modelling strategies.

Speaker Bio: Seonghyeon Moon is a 4th year Ph.D. student in Computer Science from Rutgers University.  Seonghyeon has a background in simulation and computer vision. His previous works involve enhancing occupant behavior simulation engine and starting a new ensemble of SyDEVS models for buildings. Currently, going further from simulation, he is conducting research on pedestrians movement prediction and he’s working on few-shot object segmentation which is the most basic challenge to computer vision.