The College of New Jersey Logo

Apply     Visit     Give     |     Alumni     Parents     Offices     TCNJ Today     Three Bar Menu

Events

Celebration of Computing: Fall 2022

The Department of Computer Science’s annual Celebration of Computing event will take place in-person on Wednesday, December 7, 2022, from 11:30 AM – 3:10 PM.  Thirty-six student presentations, organized in three rooms and across three sessions, will showcase students’ internship experience and mentored research outcomes over the summer and this Fall semester.

*Please note that there is no food allowed during presentation sessions and masks must be worn.*

Lunch:  11:30 AM – 12:10 PM
Presentation Session 1:   12:15 – 1:10 PM
Presentation Session 2:   1:15 – 2:10 PM
Presentation Session 3:   2:15 – 3:10 PM

Students who are taking CSC 099 and CSC 199 were assigned a poster for the review. Please use the Qualtrics Survey link below to submit your response.  Please note that you must identify yourself in the survey (there are fields where you can write your name) to be counted toward your course requirements.

Qualtrics link: https://tcnj.co1.qualtrics.com/jfe/form/SV_7QDMD2fwgIgYy4m

If you have any questions or need a copy of the schedule of presentations, please contact cs@tcnj.edu.

Colloquium Talk with Dr. Michael E. Locasto, November 15: An Operational Definition of Parsing (and its Consequences)

Dr. Michael Locasto, CTO at Narf Industries, will give a colloquium talk, titled “An Operational Definition of Parsing (and its Consequences)” on Tuesday, November 15 from 12:30 – 1:30 PM in the Library Auditorium.

See below for more information about Dr. Locasto.

Abstract: Narf Industries conducts advanced R&D in the space of vulnerability analysis, reverse engineering, and exploit development. This talk presents some our work conducted under the SafeDocs research program, which is concerned with how to make complex document formats safe to parse and consume. We will share our recent research on the unaddressed data management problem inherent in parsing (i.e., input language recognition) and how the problem might be addressed by the novel concept of dynamic progressive types. Far from being of interest to Computer Science theorists, the question of safe recognition is of utmost practical importance to software developers. Many kinds of vulnerabilities occur within input-handling code. The Language-theoretic Security paradigm (LangSec) posits that this association is not merely coincidental, nor is it due to simple ad doc mistakes. Rather, vulnerabilities and exploitation continue to occur because practical software engineering finds it difficult to take advantage of core Computer Science concepts of grammar definition, parsing, and language recognition. In this way, LangSec offers a “science of insecurity” by indemnifying consistent anti-patterns across many different vulnerabilities over time. Our work under SafeDocs shows how to use the latest tools in parser combinator libraries and format-aware tracers to define, guard, and monitor safe parsing.

Speaker Bio: Dr. Michael E. Locasto serves as the CTO at Narf Industries, a cadre of cybersecurity experts tackling some of the most important cybersecurity problems facing society, industry, and government. From 2016 to 2021, Dr. Locasto was a Principal Computer Scientist at SRI International in the Infrastructure Security Group of their Computer Science Laboratory. He served as a PI for four DARPA programs, and also co-led SRI’s Internet of Things Security and Privacy Center. Prior to joining SRI, he was a tenured Associate Professor at the University of Calgary, where he directed the Trustworthy Systems Group and conducted research in trustworthy systems, cooperative security mechanisms, and software security. Dr. Locasto has co-authored over 80 publications in the first of computer security, and he holds 14 U.S. patents related to software security and intrusion detection. He received his Ph.D., MPhil, and MSc degrees in Computer Science from Columbia University and graduated magna cum laude from The College of New Jersey (TCNJ) with BSc in Computer Science.

Colloquium Talk with Dr. Matthew Fronheiser, November 4: AI/ML in Medical Imaging: Improving Care with Technology

Dr. Matt Fronheiser, a scientific director at Bristol-Myers Squibb will give a colloquium talk, titled “AI/ML in Medical Imaging: Improving Care with Technology” on Friday, November 4 from 12:30 – 1:30 PM in Science Complex P-101.

See below for more information about Dr. Fronheiser .

Abstract: This talk will provide an overview of AI/ML applications in medical imaging, looking across the image pipeline from image acquisitions through patient diagnosis and risk stratification. Examples of clinically available technology will be discussed, with a focus on how these tools are changing the imaging workflow. This will be followed by a brief review of current research utilizing medical images to create prognostic and predictive models from large sets of clinical data.

Speaker Bio: Matt Fronheiser has over 15 years of experience in the medical imaging industry. He received his PhD from Duke University with a research focus on real-time 3D ultrasound. After receiving his degree, he spent several years performing optoacoustic imaging research for breast cancer. He currently works at a pharmaceutical company, Bristol-Myers Squibb, as a scientific director implementing imaging in clinical trials.

Colloquium Talk with Dr. Roger Mailler, September 30: NSF Research Funding Resources for Undergrad Students

Dr. Roger Mailler, a Program Director at the National Science Foundation (NSF), will give a colloquium talk, titled “NSF Research Funding Resources for Undergrad Students” on Friday, September 30 from 12:30 – 1:30 PM on Zoom.

See below for more information about Dr. Mailler and links to the event.

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

2022 Summer Workshop on Artificial Intelligence: Special Topic on Human, Crowd, Environment, and Robotics

On Wednesday, June 8, 2022, TCNJ’s Department of Computer Science (CS) hosted 26 students and 5 teachers from two nearby school districts, Hamilton Township School District (HTSD) and Mercer County Technical Schools (MCTS), to stimulate interest in computing research and careers in the field of artificial intelligence. CS faculty member Dr. Sejong Yoon led the event, titled “Summer Workshop on AI: Special Topic on Humans, Crowd, Environment, and Robotics.” The program offered students opportunities to take part in various activities, including visits to the CS Department research lab, participation in virtual reality-based research experiments, and multiple coding sessions using the Python programming language.  The program also aims to broaden the participation in computing for underrepresented minorities in the field of computing.

Dr. Yoon organized the event in collaboration with the participating school districts, as well as faculty members from Rutgers University’s Department of Computer Science (Professor Vladimir Pavlovic and Professor Mubbasir Kapadia) and Department of Electrical and Computer Engineering (Professor Jorge Ortiz), and TCNJ’s Department of Educational Administration and Secondary Education (Professor Karen Gordon). The workshop was the second offering of a four-year series (2021-2024), supported by National Science Foundation Grant #1955365.

Colloquium Talk with Seonghyeon Moon, April 19: An Integrated Platform For Joint Simulation of Occupant-building Interactions

Seonghyeon Moon, Ph.D. student at Rutgers University in the Department of Computer Science, will give a colloquium talk, titled “An Integrated Platform For Joint Simulation of Occupant-building Interactions” on Tuesday, April 19 from 12:30 – 1:30 PM in Science Complex P101.

See below for more information about Seonghyeon Moon and his research.

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.

Colloquium Talk with Honglu Zhou: April 1: Intelligent Video Understanding through Relational and Compositional Reasoning

Honglu Zhou, Ph.D. student at Rutgers University in the Department of Computer Science, will give a virtual colloquium talk on Friday, April 1, from 12:30 – 1:30 PM.  Honglu will share her research projects in machine learning applications in computer vision and graphics.

See below for more information about Honglu Zhou and the links for the event.

Abstract: Our experience as humans is deeply shaped by our perception of what happens to the objects in the visual world. Rather than building a machine that attempts to attain visual intelligence from the static and low-level pixels of images, we might need to accomplish the non-trivial higher-level visual understanding from object-centric learning of videos. Among a few critical directions for visual perception and machine intelligence, relational reasoning that reasons the saliency of objects and their dynamic interactions, and compositional learning where we compose and decompose symbolic objects in order to form holistic representations can help us develop robust and generalizable systems that can not only visually perceive but also understand and even interact with the world. In this talk, I will introduce our work on relational reasoning and compositional learning of videos.

Speaker Bio: Honglu Zhou is a Ph.D. student at Rutgers University in the Department of Computer Science, under the supervision of Prof. Mubbasir Kapadia. Her research interests mainly lie in Computer Vision and Deep Learning. She is passionate about the next-generation machine intelligence, especially machine learning and machine reasoning that enable a deeper understanding of the semantics of real-world data, which can be in forms of video, graph, human skeleton and many more. Projects that she has been working on include human group activity recognition from videos, video chapter generation, spatiotemporal reasoning and object tracking, predicting crowd dynamics, enabling intelligent and automatic floorplan design, forecasting online information spread, etc. She is currently researching on how to augment deep neural networks with relational and compositional reasoning capabilities to enrich a higher level computational video understanding.

Zoom Meeting (ID: 957 7840 7919 / Password: 464063)

https://tcnj.zoom.us/j/95778407919?pwd=R3dab0Uzd3Jza2Q2SUp3MDY4Y0ZFZz09

Top