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Events

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

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

School of Science February Career Events

School of Science February Career Events

Read below for some upcoming events for science majors!

School of Science Career Advising Hours

Have your resume critiqued, get a quick personal statement review, or discuss graduate school plans in Physics 104 on Tuesdays from 1:15 to 3:15 PM starting Tuesday, February 14!

Go to your Handshake account and select appointment type “School of Science Career Advising Hours” to schedule a 1:1 session with Jennifer Broyles from the Office of Career & Leadership Development.
1:1 Sessions are a max of 20 minutes and sign-up is required at least 12 hours in advance.

 

Virtual Spring Career and Internship Fair

Wednesday, February 23
1:00 to 2:00PM

 

Services to Use: Career Advising and Resume Critiques

Make An Appointment. Can’t make Science Advising hours, but still need advice on your job or internship search? Preparing for Graduate School? Want to practice for an interview? We’re here to discuss all of this and more. Visit Handshake and schedule an appointment today.

Resume Reviews. Schedule a 15-minute resume review session that fits your busy schedule!

Celebration of Computing: Fall 2021

The Department of Computer Science’s annual Celebration of Computer event will take place virtually on Wednesday, December 8, 2021, from 9:30 AM – 12:00 PM. We have 18 presentations that will showcase the internship experience and mentored research outcomes over the summer and this Fall semester. Each presentation will be 10 minutes long (with an exception of #17 that will be 25 min), and there will be a five min buffer between presentations for Q&A and transition.  The whole event will be broadcast via YouTube live streaming.

Livestream Links:
Presentation 1 (YouTube): https://youtu.be/Bw5EA_qBsdI
Presentation 2 (YouTube): https://youtu.be/uVjritc7d64

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_3OcKsPmRHKDEI74

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

Fall 2021 Internship Information Session

Fall 2021 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, November 10:  (6:00 – 6:45 PM)

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

Spring 2022 Registration Wait-list

The registration period for Spring 2022 courses is November 2 – 12, 2021.  Some seats have been reserved for CS majors in all CSC courses.  Please review the Spring 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.

Spring 2022 Wait-list: https://bit.ly/3uMyGJx

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, November 15, 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 Spring 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.

Colloquium Talk with Dr. Paul Youping Xiao, November 5: Deep Learning and Biomedical Imaging

Dr. Paul Youping Xiao of Bristol Meyers Squibb will give a virtual colloquium talk on Friday, November 5, from 12:30 – 1:30 PM.  Dr. Xiao has done extensive research in brain imaging and has pioneered the application of machine learning to the analysis of intrinsic optical imaging.

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

Abstract: Target segmentation is a crucial step in the analysis of biomedical images. Recent advances in deep learning have enabled automation of semantic and instance segmentations. At BMS we have applied the U-Net neural network and its variant to the segmentation of various targets in microscopic images with a sub-cellular resolution. The automated and consistent segmentations enable quantitative analyses of drug occupancy, T-cell infiltration and other metrics important for the development of novel drugs. The application of U-Net to analyzing biomedical images of various modalities will also be discussed.

Speaker Bio: Paul Youping Xiao has a bachelor’s degree in electronics, a master’s degree in physiology, and PhD in neuroscience. He has extensive experience in brain imaging including the discovery of color maps in the primate visual cortex. He pioneered the application of machine learning to the analysis of intrinsic optical imaging. At BMS he is leading the effort of automating high-content imaging with artificial intelligence.

Zoom Meeting (ID: 941 0711 6653/ Password: d7dnMrs5)

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

Colloquium Talk with Dr. Faisal Khan, October 19: AI and Data Science in Healthcare and the Lifesciences

Faisal Khan,

Dr. Faisal M. Khan, the Executive Director of Advanced Analytics and Artificial Intelligence at AstraZeneca, will give a virtual colloquium talk on Tuesday, October 19, from 12:30 PM – 1:30 PM. Dr. Khan is known for his work on the applications of machine learning and AI for healthcare and the life sciences.

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

Abstract: Dr. Khan will discuss the broad range of applications that data science and AI are driving to impact live and improve health in healthcare and the life sciences. The talk will focus on various application areas, algorithmic and real-world challenges and issues which emerge, as well as things to keep in mind when deploying within regulated and industrial environments.

Speaker Bio:  Faisal M. Khan, Ph.D. is the Executive Director of Advanced Analytics and Artificial Intelligence at AstraZeneca. His team focuses on the applications of AI and data science throughout the drug discovery lifecycle, from target identification through Phase 3 trials and beyond. His interests focus on the intersections of data science, digital health, biostatistics, bioimaging, personalized medicine, and healthcare delivery. His career has encompassed all aspects of healthcare and biomedical analytics, including diagnostics, devices, clinical trials/therapeutics, and payers/insurance. Dr. Khan has worked or consulted across academia and industry with both startups and Fortune-50 companies. He has over 100 published papers, abstracts, and patents on the applications of machine learning and artificial intelligence for healthcare and the life sciences.

Zoom Meeting (ID: 961 9503 5078 / Password: N842wT31)

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

 

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