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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

Fall 2022 Registration Wait-list

The registration period for Fall 2022 courses is April 5 – 15, 2022.  Some seats have been reserved for CS majors in all CSC courses.  Please review the Fall 2022 Registration Newsletter for additional information on options courses offered next semester.

After your registration window opens, if the class you need is closed, put yourself on the wait-list using the Qualtrics form below.

Be sure to read all directions and enter all requested information.

Fall 2022 Wait-list: https://bit.ly/35GdtJ7

If you make changes to your schedule after entering your submission to the wait-list and need to update your information, email cs@tcnj.edu.

We will not be signing students into courses until Monday, April 18, after the registration window closes. Please do not email the department for updates before this time.  We will enroll students into any unfilled seats in order, based on their registration times and time they registered on the wait list.

Be sure that your intended course does not conflict with a course in your current schedule, and that you are willing to drop conflicting courses to make the change.  If you have a full course load or time conflict and do not indicate courses to drop on your wait-list submission, your submission will be disregarded.

As always, have a back-up plan in case you are not able to get into your preferred courses.

Please see the Advising Resources webpage for more information about submitting Mentored Research or Internship forms for Fall 2022.


Links to other School of Science Department Wait-lists can be found below:

Biology: https://biology.tcnj.edu/resources-for/current-students/waitlists/
Chemistry: https://chemistry.tcnj.edu/waitlists/
Math/Stat: https://mathstat.tcnj.edu/ (link to form posted on the menu bar)
Physics: https://physics.tcnj.edu/physics-registration-faq/

For more information on waitlists for other schools and departments, please refer to the TCNJ Waitlisting Process packet.

Call for Goldberg-Neff Scholarship Prize Applications – 2022

Charles H. Goldberg – Norman Neff Scholarship Prize in Computer Science

(Applications due Friday, April 8, 2022 by 12:00 PM)


The Charles H. Goldberg – Norman Neff Scholarship Prize is awarded annually by the Computer Science Department to a student(s) who has/have demonstrated academic excellence in Computer Science and who will be continuing into graduate study in Computer Science.

Eligible students are graduating Computer Science majors who have applied for admission for graduate study in Computer Science. The number of awards and the award amount are at the discretion of the Computer Science Department. The award check will be conveyed to the awardee(s) upon matriculation in a graduate program in Computer Science within one year of the announcement of the award.

How to Apply

Please complete the following Google Form before the deadline: https://forms.gle/uvUpn8JwK5pqxLpC7

Five CS Majors Inducted into Phi Beta Kappa

CS Majors Leah Kazenmayer (Class of 2023), Luke Kurlandski (Class of 2022), Forum Modi (2022), Akira Takada (2022), and Alexander (AJ) Viola (2022) were recently accepted into Phi Beta Kappa honors society.

Phi Beta Kappa (PBK) is one of the country’s most prestigious honors societies, and only a limited number of junior and senior students are accepted each year.   PBK honorees have demonstrated excellence in the liberal arts and sciences at undergraduate institutions.

For more information about Phi Beta Kappa, see: https://www.pbk.org/

Congratulations to Leah, Luke, Forum, Akira, and AJ!

Spring 2022 Internship Information Sessions

Spring 2022 Internship

 

REMINDER:  All CS Majors are required to attend one internship information session before they can apply for internship (CSC 399) for credit.

Be sure to check Dr. Papamichail’s website and come prepared with any additional questions you might have.

Wednesday, February 16:  (6:00 – 6:45 PM)
Tuesday, March 8:  (6:30 – 7:15 PM)

Zoom session link: https://tcnj.zoom.us/j/98358115019?pwd=eFFqVzB3Smw3TzlWN3E4V1BtMkI0Zz09

Student-Faculty Research Nominated for Best Paper at IEEE ICSC 2022

TCNJ's ELSA
Pictured: TCNJ’s ELSA (Electronic Laboratory for Science and Analysis) high performance computing cluster

CS major Luke Kurlandski (Class of 2022) presented a research paper he co-authored with Dr. Michael Bloodgood at IEEE ICSC 2022, held January 26-28, 2022. Kurlandski and Dr. Bloodgood’s paper, titled “Impact of Stop Sets on Stopping Active Learning for Text Classification”, was one of nine papers nominated for the Best Paper Award at the conference. Kurlandski completed mentored research with Dr. Bloodgood in Fall 2021.

Kurlandski and Dr. Bloodgood used TCNJ’s ELSA (Electronic Laboratory for Science and Analysis) high performance computing cluster to conduct their experiments. This cluster is funded by the National Science Foundation under NSF Award #1828163.

Kurlandski reflected on his mentored research experience with Dr. Bloodgood and his presentation at IEEE ICSC 2022: “The research process and the international conference were incredible learning experiences and I am thankful the College gave me this opportunity.”

More information about IEEE ICSC can be found at: https://www.ieee-icsc.org/

Congratulations again to Luke and Dr. Bloodgood!

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