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Author Archives: Ann Zsilavetz

CS Junior’s Poster Accepted to the 2021 SIGCSE ACM Student Research Conference

Congratulations to CS Major Luke Kurlandski (Class of 2022) on his poster’s acceptance to the 2021 SIGCSE ACM Student Research Conference!

Luke’s poster on CABPortal, entitled “Evaluating ML Recommender Systems Without Interactions Data”, will be presented at the March 2021 virtual conference.   CABPortal (Collaborating Across Boundaries Portal) is a web application that promotes collaboration between researchers in different academic disciplines. An effective recommendation system would be beneficial for the site, but CABPortal does not have a history of user behavior to train a recommender engine on. This semester, Luke researched a strategy to develop, test, and evaluate an ML-based (machine learning-based) recommendation system for CABPortal by using synthetically-generated artificial training data.

For more information on the SIGCSE conference, see: https://sigcse2021.sigcse.org/

CS Alumna Donation Will Support Scholarship for Grace Hopper Celebration Attendee

Computer Science Department alumna Jennifer Gandolfo (Class of 1997) has generously donated to the CS Department to support a scholarship for a woman CS major to attend the Grace Hopper Celebration.

The Grace Hopper Celebration of Women in Computing is an annual fall event at which women in tech (including some of CS @ TCNJ’s very own students and faculty) gather to participate in professional development workshops and technical seminars, network with peers in the industry, and attend the career fair.  While the GHC is typically held in-person, this year’s event was held virtually, and was attended by Dr. Pulimood and CS Majors Adeena Ahmed and Hana Memon.

Gandolfo’s donation will fund travel and conference expenses for one woman CS major to attend the event.

Thank you again to Jennifer for her generous donation and support of students in the CS @ TCNJ program!

Photos below are from previous years’ Grace Hopper Celebration events attended by CS Majors.

Celebration of Computing: December 2, 2020

This year’s Celebration of Computing presentations will be live streamed on YouTube.

Streaming links have been shared with students via mailing lists.
Please contact cs@tcnj.edu if you have any questions about the schedule.

Student Presentations:  10:30 AM – 12:00 PM

Students who are taking CSC 099 and CSC 199 were assigned a poster to review.  Please use the Qualtrics Survey link provided by your instructor to submit your response. Please note that you must identify yourself in the survey (in the appropriate survey field) in order for your review to be counted toward your course requirements.

Computer Science Colloquium, October 30

On Friday, October 30,  the Computer Science Department will host its second colloquium of the Fall 2020 semester. Dr. Uddipan Das of the Computer Science Department at TCNJ will give a technical talk entitled “Quality-aware Data Management in Smart Grid Communication Networks.  An abstract of his talk can be found below.

Please join CS faculty and students via Zoom from 12:30 – 1:30 PM for this talk.

Zoom Meeting: (ID: 936 1764 8901 / Password: 783429)
https://tcnj.zoom.us/j/92912867463?pwd=cHZVaHkwQmF4UTRoOWkzTG1vc0xkQT09
You must sign in with your TCNJ credentials. Waiting room will be enabled.

Abstract:
The inclusion of various intelligent electronic devices such as smart meters for Advanced Metering Infrastructure (AMI) in Smart Grids is expected to result in intermittent or frequent communications network congestion if additional network infrastructure investments are not made. One approach to deal with such a data volume challenge in smart grids without additional investments to increase network capacity is to aggregate data streams within the underlying communication network whenever network congestion happens. However, this needs to be done carefully so as not to significantly impact the smart grid applications that need the data. In this talk, I will present my research on data management in capacity-constrained communication networks of AMI in Smart Grids considering the requirements of Quality-of-Service (QoS). I will discuss my research contributions in this area to deal with the challenge of managing data traffic while keeping a balance between data granularity and network latencies.

Bio:
Uddipan Das is currently working as an Assistant Professor in the Department of Computer Science at The College of New Jersey. He graduated with a Ph.D. degree in Electrical Engineering and Computer Science from Wichita State University in 2020. Previously, he earned his M.E. degree in Software Engineering from Jadavpur University and B.Tech degree in Computer Science and Engineering from West Bengal University of Technology. His primary research interest centers around the design and development of data-driven algorithms and systems in smart cities; specifically, data management in smart electric power grid communication networks and smart environments for navigation and wayfinding for people with disabilities. He has published peer-reviewed research publications in the top-tier journal and conference venues, and he serves as a reviewer for the IEEE Systems Journal, IEEE ICDCS, IEEE NAPS, and IEEE IGSC, etc. He is a member of IEEE, IEEE Computer Society, and IEEE Power & Energy Society.

Spring 2021 Registration Wait-list

The registration period for Spring 2021 courses is November 3 – 13, 2020.  Some seats have been reserved for CS majors in all CSC courses.  Please review the Spring 2021 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 2021 Wait-list: https://bit.ly/34fqkgL

If you make changes to your schedule after entering your submission to the wait-list and need to update the department on which course(s) must be dropped, email cs@tcnj.edu with this information or enter another wait-list submission.

We will not be signing students into courses until Monday, November 16, 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 2021.


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

Biology: TBA
Chemistry: https://chemistry.tcnj.edu/waitlists/
Math/Stat: https://mathstat.tcnj.edu/ (link to form usually posted on bottom of website during registration)
Physics: https://physics.tcnj.edu/physics-registration-faq/

AT&T Workshop for CS Juniors & Seniors

Join a panel of TCNJ alumni and representatives from AT&T for the “My Identity: Personal Narrative Workshop” for CS juniors and seniors.  The workshop focus on building interviewing skills for all students, and discussion of internship opportunities for juniors and full-time positions for seniors.

Students must RSVP for the event.  Email cs@tcnj.edu or see Dr. Pulimood’s email from September 25 for more information about the event and the link to RSVP.

Computer Science Colloquium: October 2

On Friday, October 2,  the Computer Science Department will host its first colloquium of the Fall 2020 semester. Niluthpol Chowdhury Mithun of SRI International will give a technical talk entitled “Learning Multimodal Retrieval Models with Limited Labeled Data.  An abstract of his talk can be found below.

Please join CS faculty and students via Zoom from 12:30 – 1:30 PM for this talk.

Zoom Meeting: (ID: 929 1286 7463 / Password: 020525)
https://tcnj.zoom.us/j/92912867463?pwd=cHZVaHkwQmF4UTRoOWkzTG1vc0xkQT09
You must sign in with your TCNJ credentials. Waiting room will be enabled.

Abstract:
In recent years, tremendous success has been achieved in many computer vision and multimedia tasks using deep neural network models trained on large hand-labeled datasets. In many applications, this may be impractical or infeasible, either because of the non-availability of large datasets or the amount of time and resource needed for such labeling. In this respect, an increasingly important problem is in the light of data-hungry deep neural network models is how to learn useful models with limited labeled data. Developing robust models with a limited degree of supervision could be extremely useful for multi-modal retrieval and analysis tasks as collecting training data for these tasks is extremely labor-intensive and prone to significant errors. In this talk, I will go over several multi-modal retrieval tasks (i.e., video-text retrieval, RGB-LiDAR Localization, and text-based video moment retrieval) focusing on developing efficient solutions leveraging available incidental signals or weak labels.

Bio:
Niluthpol Chowdhury Mithun is currently an Advanced Computer Scientist at the Center for Vision Technologies, SRI International in Princeton, NJ, USA. He graduated with a Ph.D. degree in 2019 from Video Computing Group at the University of California, Riverside (UCR). Before joining UCR, he was a Sr. Software Engineer at Samsung R&D Institute Bangladesh. Previously, he received his Bachelors and Masters degree from Bangladesh University of Engineering and Technology. His current research is focused on solving fundamental problems in Computer Vision, and Machine Learning with more focus on representation learning with multiple modalities (e.g., vision, language, LiDAR), learning under limited/weak supervision and multi-modal embedding. He has successfully applied these methods to several real-world problems such as image-text retrieval, video moment localization, video summarization, object detection, visual localization. His work has been published at several high-quality venues such as CVPR, MM, TIP, T-ITS etc. He has won the ACM International Conference on Multimedia retrieval 2018 best paper award and the SRI CVT SharkTank 2019. He serves as a program-committee member/reviewer for venues such as CVPR, ICCV, ECCV, AAAI, MM, ICIP, T-PAMI, T-MM, T-CSVT, T-ITS, PR, PRL

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