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
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.
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.
Biology: https://biology.tcnj.edu/resources-for/current-students/waitlists/
Chemistry: https://chemistry.tcnj.edu/
Math/Stat: https://mathstat.tcnj.edu/ (link to form posted on the menu bar)
Physics: https://physics.tcnj.edu/
For more information on waitlists for other schools and departments, please refer to the TCNJ Waitlisting Process packet.
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
The Spring 2022 registration newsletter is now available.
Registration for Spring 2022 courses will begin on Tuesday, November 2. Please review the registration newsletter (linked below) for information on next semester’s options courses, a link to the registration wait-list, and a general listing of CS courses.
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
On September 20, Dr. Papamichail presented research co-authored by three CS Department students and alumni at the the 13th International Workshop on Bio-Design Automation (IWBDA), held virtually this year. The presentation, entitled “Decodon Calculator 2: Codon-Optimized Degenerate Codon Set Design Tools” synthesizes work completed by Dr. Papamichail and Akira Takada (Class of 2021), Tomer Aberbach (Class of 2020) and Nicholas Carpino (Class of 2018) during their mentored research experiences.
Synthetic biology researchers often pursue the creation of novel proteins with improved properties. Toward this endeavor, researchers design and synthesize libraries of variants of existing proteins to isolate the changes that confer improved properties of interest. Akira, Tomer, and Nicholas have implemented successive versions of web-based tools that enable synthetic biologists to create large but specific protein variant libraries, allowing them to balance synthesis cost with protein library quality.
Congratulations to Dr. Papamichail, Akira, Nicholas, and Tomer!
Dr. Bikram Pal Turka, Senior Lecturer in the CS Department, has authored a chapter titled “Obstacles in Information System Succes” that has been published in Digitising Enterprise in an Information Age, a book published by CRC Press Taylor and Francis Group.
An abstract of the chapter can be found below:
To gain a better competitive advantage in the market, the organizations are using information systems. Most of the organizations either have established the information system or they upgrade their information system. But still there are lots of hurdles for gaining information system success. There has been a large number of analyses of critical success factors of information system projects in the literature, but there is a shortfall in research efforts in studying failures globally and particularly in India. Therefore this chapter attempts to study empirically the obstacles coming in Information system success. A questionnaire survey has been conducted to know the failures factors for not updating the information system timely. The survey has been done on two prominent telecommunication organizations, one having successful IS (Reliance Communication) due to its continuous updation with respect to time, industry and executives whereas other (Puncom, Mohali) did not. As India is the second largest country in terms of mobile users in the world, therefore, the study of this industry is strategically and economically important due to its high potential for the growth of the country.
Congratulations to Dr. Turka!
Congratulations to the seven CS MUSE students who shared their summer research projects on Tuesday, September 14, as part of the campus-wide presentation event.
Jenna Stiesi, Kiera Gill, and Matthew Hannum, mentored by Dr. Monisha Pulimood, presented their MUSE project titled “CABPortal: Leveraging Collective Intelligence to Improve
Sustainability of Web-Based Portals”.
Andrew Michael and Kyla Ramos, mentored by Dr. Sharif Ferdous, presented their MUSE project titled “Investigating the Effectiveness of a Visual Cybersickness Questionnaire”.
Michael Giordano and Vihan Patel, mentored by Dr. Michael Bloodgood, presented their MUSE project titled “Varying Validation Set Size to Improve Machine Translation”.
Students’ presentation posters are now on display on the CS Department bulletin boards across from STEM 103, the Research Lab. Congratulations again to all of our presenting students!
This summer, CS sophomore Leah Kazenmayer completed a Research Experience for Undergraduates (REU) program at the University of Central Florida.
Leah shared her experience with the CS Department:
“This summer, I participated in the Research Experience for Undergraduates (REU) program for the University of Central Florida (UCF). This program incorporated Internet of Things (IoT) devices, the programming language Python, and machine/deep learning. Specifically for the project I worked on with my partner Gabriela Ford, we were given datasets from the Automated Traffic Signal Performance Measures (ATSPM) database that detailed events that occurred on roadways in Seminole County, Florida, such as vehicle volume at intersections, timestamps of traffic light changes, timestamps of pedestrian sign flashes, and so forth. We particularly focused on obtaining hourly vehicle volume within a specific corridor in Seminole County, and utilized machine/deep learning to predict the next hour based on the previous 6 hours of traffic volume.
This 8-week REU was an invaluable experience where I met new people, networked with faculty members and graduate students, and was exposed to the everyday routine of graduate school. It taught me more about Python and machine/deep learning, subjects I was completely inexperienced with; after those 8 work-intensive weeks, I can now say that I have an abundance of knowledge in both fields.
I will take all of this knowledge I have gained from this experience and use it as a resource for all future endeavors related to the computer science field, whether it be in academia or in the industry.”
Leah has also received a scholarship to attend the virtual Grace Hopper Celebration, which begins next week.
Congratulations again to Leah and thank you for sharing your summer REU experience at UCF!
