News
IEEEXtreme 18.0 Programming Competition 2024
Our PhD students GAO Yixiong and ZHENG Shangkun along with BSc Computer Science student YAN Yachao, under the supervision of Prof LI Minming and Prof CHEUNG Ray, have secured the 1st place among all teams from Hong Kong and ranked 13th worldwide in the 2024 IEEEXtreme 18.0 Programming Competition.
IEEEXtreme is a prestigious global challenge where IEEE student member teams compete for 24 hours to solve complex programming problems. The IEEEXtreme 18.0, which commenced on 26 October 2024, saw participation from 19,916 students and 8,793 teams, representing the top universities from 75 countries and regions worldwide. Despite the intense demands of the competition, our team demonstrated exceptional perseverance and skill, achieving this impressive outcome.
Awards in the 49th International Collegiate Programming Contest (ICPC)
Our PhD students GAO Yixiong and ZHENG Shangkun together with BSc Computer Science students YAN Yachao, HONG Chenhao, GAO Liyou, WANG Fan, WONG Ka Wa, CHOI Kui Wang and YANG Hans Ericson, under the supervision of Prof LI Minming, Prof HUANG Jun, Prof QIU Junqiao, Prof ZUO Jinhang and Dr LEE Kenneth, have secured multiple awards in the 49th International Collegiate Programming Contest (ICPC).
The ICPC drew hundreds of universities and thousands of contestants each year. With our team’s exceptional algorithmic programming and problem-solving skills, they managed to distinguish themselves and won the following: -
2024 ICPC Asia Hangzhou Regional Contest on 9 Nov 2024
- Gold Medal
· Contestants: GAO Yixiong, ZHENG Shangkun, and YAN Yachao
2024 ICPC Asia East Continent Final Contest (Xi'an) on 27 Dec 2024
- Silver Medal
· Contestants: GAO Yixiong, ZHENG Shangkun, and YAN Yachao
2024 ICPC Asia Shenyang Regional Contest on 23 Nov 2024
- Silver Medal
· Contestants: GAO Yixiong, ZHENG Shangkun, and YAN Yachao
2024 ICPC Asia Hangzhou Regional Contest on 9 Nov 2024
- Bronze Medal
· Contestants: HONG Chenhao, GAO Liyou, and WANG Fan
2024 ICPC Asia Kunming Regional Contest on 30 Nov 2024
- Bronze Medal
· Contestants: WONG Ka Wa, CHOI Kui Wang, and YANG Hans Ericson
2024 ICPC Asia Hong Kong Regional Contest on 21 Dec 2024
- Bronze Medal
· Contestants: WONG Ka Wa, CHOI Kui Wang, and YANG Hans Ericson
ByteDance Scholarship & Best Mentor Award
Computer Science PhD student Mr Yi LIU has been awarded the ByteDance Scholarship for his project proposal titled “Towards Efficient, Secure, and Robust Federated Multimodal Large Language Models: System Design and Emerging Applications”. In additional, his supervisor Prof Cong WANG has won the Best Mentor Award in recognition of his outstanding contributions to nurturing talent.
The ByteDance Scholarship Program is an annual initiative that selects candidates from university students majoring in computer science, science and engineering-related fields. Standing out among 400 candidates, Mr. Liu will receive RMB 100,000 in research funding and will benefit from the opportunities offered through ByteDance’s One-on-One Mentorship, Talent Program and Research Intern Program, as well as the co-creation of patents and access to top-tier research conferences. The Awards Ceremony will take place in Singapore from 7 to 8 January 2025.
Best Paper Award at the ACM International Workshop on Mobile Computing with Efficient and Interactive Foundation Models 2024 (ACM EIFCom 2024)
Prof Weitao Xu, together with CS PhD students Mr Huanqi Yang and Mr Rucheng Wu, have been awarded the Best Paper Award at the ACM International Workshop on Mobile Computing with Efficient and Interactive Foundation Models 2024 (ACM EIFCom 2024). Their paper titled “TransCompressor: LLM-Powered Multimodal Data Compression for Smart Transportation”, was recognized at the workshop held on 18 November 2024 in Washington, D.C., USA.
The team introduces TransCompressor, the first framework using Large Language Models (LLMs) for efficient compression and decompression of multimodal transportation sensor data. They evaluate TransCompressor with diverse sensor data types, such as barometer, speed, and altitude, across different transportation modes like buses, taxis, and MTRs in Hong Kong. The system effectively uses LLMs to interpret and decompress data, laying the groundwork for future smart transportation applications.