Abstract: Augmented Reality (AR) blends real-world scenery with computer and artist generated imagery to unlock novel, creative experiences. In this talk, I will describe advances towards crafting AR imagery that seamlessly blends the real and virtual together, with a focus on matching scene lighting. Given the rapid pace of recent developments in image generation models, I will also share my perspective on these generative models as applied to AR experiences.

Speaker Bio: Chloe LeGendre is a senior software engineer in Google Research, where she is currently working on computational photography and high dynamic range imaging. Her research typically applies machine learning to problems in computer graphics, photography, and imaging, with a special focus on scene lighting measurement and estimation, color science, and portrait photography manipulation. As a member of USC’s Institute for Creative Technologies’s Vision and Graphics Lab, Chloe graduated with a PhD in Computer Science in 2019 from the University of Southern California, where she was advised by Paul Debevec. Chloe has also worked in the R&D divisions of Netflix, L’Oréal USA, and Johnson & Johnson, focused on emerging technology development in the areas of virtual production, augmented reality, and imaging.

Abstract:  Holographic displays promise unprecedented capabilities for direct-view displays as well as virtual and augmented reality applications, including per-pixel depth, efficient light utilization, and vision correction. However, despite these capabilities, these displays always have been relegated to the status of a perpetually future technology, due to several major challenges such as large benchtop form factors, and the fundamental trade-off between algorithm runtime and achieved image quality. In this talk, I will present co-design approaches of optics and algorithms in holographic near-eye displays that address these challenges. First, I will discuss a compact display system architecture with an eyeglasses-like form factor for virtual reality that can deliver full-color 3D holographic images using a 2.5mm thick optical stack. Next, I will introduce an algorithmic CGH framework that achieves unprecedented image fidelity and real-time framerates. Our framework comprises several parts, including a novel camera-in-the-loop optimization strategy that allows us to either optimize a hologram directly or train a parameterized model of the optical wave propagation and a neural network architecture that represents the first CGH algorithm capable of generating full-color high-quality holographic images at full-HD resolution in real-time. By incorporating AI advancements into conventional optics and photonics, we can open up new possibilities and enable high-fidelity imaging and display solutions.

Speaker Bio:  Suyeon Choi is a PhD student at Stanford Computational Imaging Lab, advised by Professor Gordon Wetzstein. His research interests are centered on the co-design of optical systems and algorithms, with a focus on developing holographic display systems that incorporate machine learning for next-generation virtual and augmented reality displays. His work is supported by a Meta Research PhD Fellowship, a SPIE Optics and Photonics Education Scholarship, a Kwanjeong Scholarship, a Korean Government Scholarship, and a GPU gift from NVIDIA. Previously, he received his Master’s degree in Electrical Engineering from Stanford University, completed his undergraduate studies at Seoul National University as a recipient of The Presidential Science Scholarship.

The registration period for Fall 2023 courses is April 4 – 14, 2023.  Some seats have been reserved for CS majors in all CSC courses.  Please review the Fall 2023 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 start signing students into courses until Monday, April 17, 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 2023.

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.

CS majors Sean Elefant, Jabili Gadde, Kiera Gill, Robert Helck, Max Landry, and Jason Swick 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 Sean, Jabili, Kiera, Robert, Max, and Jason!

Abstract:  Working as a data scientist in the pharmaceutical industry can be a challenging task due to stringent regulations that demand rigorous accountability. Fortunately, powerful visualization tools like CanvasXpress offer us an opportunity to effectively explore complex datasets while simultaneously ensuring full compliancy with regulatory standards – resulting in compelling visualizations and unparalleled reproducibility of research results.

Speaker Bio:  Dr. Isaac Neuhaus is the Senior Director of Computational Genomics working at Bristol Myers Squibb. He is a self-motivated, creative bioinformaticist with over 20 years of experience. Dr. Neuhaus has a broad range of expertise in bioinformatics, transcriptional profiling, systems biology, genome analysis, sequencing, data analysis, and visualization. He is also a computer programming expert, fluent in R, Perl, JavaScript, HTML5, Oracle, and C. He authored or co-authored more than 50 scientific publications in the field of his expertise. Before joining Bristol Myers Squibb more than 22 years ago, he worked at Norvatis after his post-doctoral training in Mouse Genetics at Harvard Medical School in 1998. He received his Doctor of Philosophy degree in Biochemistry and Molecular Biology from the University of Miami Millar School of Medicine in 1995.