2024-01-31: ODU CS 2023 Trick-or-Research Event Recap

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The Department of Computer Science (CS) at Old Dominion University (ODU) held its fifth annual Trick-or-Research event on Monday, October 31, 2023. This event is a collaborative effort from the faculty, staff, and students at ODU CS to spread awareness on their ongoing research and foster new collaborations. This year, the event was held in a hybrid fashion; participants were able to visit labs in the E.V. Williams Engineering & Computational Sciences Building (E&CSB) and Dragas Hall either in-person, or virtually through Gather.town.

We had posters and demos from 11 research labs at ODU CS. To embrace the halloween spirit, the faculty, staff, and students decorated their virtual and physical lab spaces, and dressed up in outfits such as Sherlock Holmes, Zorro, Guy Fawkes, and Statue of Liberty.

Lab Visits

The Hands-On lab was established by Ajay Gupta. They shared their journey of applying commercial off-the-shelf (COTS) products for detecting agitation in dementia patients. They also presented their Hotspot Project, which aims to provide internet connectivity to students everywhere via authorized devices.

When not doubling as Sherlock Holmes, Dr. Jian Wu oversees research in the Lab for Applied Machine Learning and Natural Language Processing Systems (LAMP-SYS) lab. This year, Dr. Wu and his lab presented their work on entity extraction, mining electronic documents, and computational reproducibility in deep learning. Attendees learned how the LAMP-SYS detectives applied deep learning to solve problems, and got a sneak-peak into the cases still under investigation.

The High Performance Scientific Computing Team for Efficient Research Simulations (HiPSTERS) lab is led by Dr. Desh Ranjan and Dr. Mohammad Zubair at ODU CS. They presented novel mathematical methods to improve interdisciplinary research on HPC environments, and how they used GPU programming to simulate coherent synchrotron radiation and particle collider beam dynamics. The AI Methods and Applications group, led by Dr. Yaohang Li, presented their work with Jefferson Lab on machine learning based physics event generation and particle production simulations, and showcased their ongoing deep learning research. The Accessible Computing lab, led by Dr. Vikas Ashok, explores ways to improve the human-computer interaction of users with visual impairments. They presented some user interfaces and image-to-speech tools that they designed for the visually impaired internet users, and how these tools improve their browsing experience.

The Web Science and Digital Libraries (WS-DL) group, led by Dr. Michael Nelson, presented their work on web archiving and their reproducibility. Dr. Michele Weigle and other members of the group were more than willing to answer questions.

The Bioinformatics lab, led by Dr. Jing He, conducts research on protein structure simulation, secondary structure elements detection, topology graphs, and potential energy functions. Their Gather.town virtual lab space hosted several videos and posters on their current work. They also discussed their current research on bioinformatics and computational biology with attendees.

The Neuro Information Retrieval and Data Science (NIRDS) lab, led by Dr. Sampath Jayarathna, demonstrated cool eye trackers, EEG devices, wearable sensors, and drones. They also explained some of their work on applying such technology to solve real-world problems. Their demos and explanations were supplemented by videos and posters on their Gather.town virtual lab space.

The Internet Security Research lab, led by Dr. Shuai Hao, presented their research on web security, cyber crime, and security issues in current internet infrastructure. The Lab for Secure and Intelligent Computing presented their current research on cybersecurity, which spans hardware, web, cloud, blockchain, and cryptocurrency security. Attendees also visited Dr. Wang's Awesome Team of Students (WATS lab) on Gather.town. Their work centers around machine learning and data mining. They presented some of their work on using neural ordinary differential equations (ODEs) to model complex data problems.

Summary

This year's Trick-or-Research was a great success for showcasing the current research projects of ODU CS and fostering new collaborations. The hybrid format enabled both in-person and online participation, ensuring that no one was left out. Both faculty and students shared a lot of valuable information, and kept the attendees engaged. It provided the opportunity for students looking to pursue advanced degrees and/or research to visit each lab and get in touch with faculty members. It also provided the opportunity for the curious to check out some cool projects. Thanks to all faculty, staff, and students for their effort, which made this event a success. 

-- Yasith Jayawardana (@yasithdev)

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