Student-led, CS-only expo a big hit
Student-led, CS-only expo a big hit
In April, the student organization Women in Computer Science (WiCS) hosted a CS Expo, offering undergraduate students the opportunity to showcase projects they’ve been working on outside of their coursework this year. The student-run CS Expo featured software, hardware, and research projects developed by students through their participation in a Hackathon, a student organization, or simply as a side project.
Nandana Sheri, one of WiCS’ event chairs, said pursuing projects outside of the classroom is a valuable addition to required coursework, and she wanted CS students to see the types of projects they could work on.
“A lot of students come into CS not knowing what they can do,” Sheri said. “They go to employers with their degree, but don’t think about the things they did outside of the 128 credits they need to take. The classes are wonderful, but that’s only one part of you.”
Over 30 projects were presented at the Expo, and the event was packed with attendees, including CS students and faculty. Sheri was pleasantly surprised with the turnout, given that the event was held during week 15 of the semester, and students were finishing homework and preparing for finals.
Raydar
Isaac Alazar, Joshua Jung, Anirudh Kuppili, Arslan Kamchybekov, and Pranav Shridhar presented their project, Raydar, an app that reunites people with the belongings they lost on campus. The team worked on the project during UIC’s Sparkhacks.
Raydar is a dual machine learning application that analyzes and matches uploaded sketches or photos of lost items with found items, which are reported to the database by anyone on campus. Those looking to reunite with their items can browse found items, or upload their own images for lost items. They hope to see their project rolled out on campus to augment the current system in place.
They built Raydar using TensorFlow CNN for training an image identifying model. They then paired scikit-learn with a text analysis method for extraction. For the front end, they used NextJS paired with ReactJS and ShadCN components with TailwindCSS for styling purposes. For authentication, they used Clerk and Supabase for their database. Auxiliary libraries used in training were spaCy and sci-kit learn for NLP, Fuzzy for removing typos, and Levenschentein for semantic similarity.
Ecopet
Ecopet was an app built by Chris Harrison and Josephene Lee during IIT’s Scarlet Hacks competition. The duo is passionate about creating a more sustainable planet, and thought the app, which gamifies environmentally friendly behaviors, would encourage others to lead a more eco-friendly life.
They designed the mobile app using Figma, and programmed the app using React Native and Expo, which utilizes TypeScript and JavaScript. For authentication, they used AuthContext and React Native’s async storage to keep track of username/password pairings.
They hope to add a community event page to the app and allow users to work within a network to complete shared goals.
JARS Rover
Jash Shah is really passionate about hardware and physics, so in his spare time, he built a remote-controlled rover. He programmed it so anyone from around the world can log in and control its movements. The rover was built with a GalaxyRVR rover kit and is controlled remotely by Arduino, ESP32, and Google Firebase.
Shah graduated in May and has a job lined up with HP, where he previously interned. His role is technical automation engineer, and he will relocate to Boise, Idaho, for the position. He intends to continue physics-related projects on the side.
Mobile Server Cluster
A group of students from UIC’s Association for Computing Machinery club have been working on networking hardware together to optimize various workloads running on its system.
Lower-power computers are connected to the same network, and using Kubernetes, an open-source system for automating deployment, scaling, and management of containerized applications, workloads can be scheduled in whatever configuration desired.
For running a website, for example, lo- powered hardware can be used. If a lot of computation power is needed, faster, higher-powered hardware will be used–something machine learning and artificial intelligence would require, for example.
The opportunity to play around with hardware isn’t something a lot of students have experience with, and hands-on learning their system provides will help students interested in becoming a reliability engineer, or going into DevOps, for example.
The group from ACM that worked on the project includes Jacob Cohen, Kevin Cordero, Soham Gumaste, Dan Heller, Scott Kwok, Chase Lee, Harshit Modi, Max Nguyen, Luis Sanchez, Sam Skean, Sam Stuckey, and Ethan Wong. Wong and Lee were explaining the project to Expo goers.
Wong, who graduated in May, will be working at Argonne National Laboratory in their High-Performance Computing group, optimizing the performance of workloads. Lee is an alumni working as a consultant for a Chicago-based firm, doing DevOps.