News

MCL Director, Professor C.-C. Jay Kuo, received the Distinguished Alumni Award from his Alma Mater, National Taiwan University (NTU), at its 96 th Anniversary Ceremony on November 15 (Friday), 2024, in Taipei, Taiwan. The university was founded in 1928 during Japanese rule as the seventh of the Imperial Universities. The university comprises 11 colleges, 56 departments, 133 graduate institutes, and 60 research centers.

Professor Kuo studied as an undergraduate in the Electrical Engineering Department at NTU from 1976 to 1980. He said, “NTU provided an excellent environment for me to make good friends, explore new things, and build academic background, so I became more mature and independent. It was a memorable period of time in my life.” Professor Kuo received this honor for his contributions to multimedia technologies. He added, “I want to share this honor with all of my students and my family. Their love, trust, and efforts make this award possible. I am very grateful.”

Word embedding is a fundamental task in natural language processing. It converts each word into a representation in a vector space. A challenge with word embedding is that, as the vocabulary grows, the vector space’s dimension increases – leading to a vast model size. Storing and processing word vectors are resource-demanding, especially for mobile edge-devices applications.

Jintang Xue, a PhD student at MCL, has proposed a dimension reduction method called WordFS [1] for pre-trained word embeddings. WordFS combines a post-processing algorithm (PPA) and weakly- supervised feature selection with limited word similarity pairs. It is simpler, more efficient, and more effective than existing approaches. Experimental results show it excels in word similarity tasks and generalizes well across downstream tasks. WordFS effectively reduces embedding dimensions with lower computational costs.

[1] Xue, Jintang, et al. “Word Embedding Dimension Reduction via Weakly-Supervised Feature Selection.” arXiv preprint arXiv:2407.12342 (2024).

We are so happy to welcome a new MCL member, Laurence Palmer joining MCL this semester. Here is a quick interview with Laurence:

1. Could you briefly introduce yourself and your research interests?

My name is Laurence Palmer. I’m a current Master’s student studying Computer Science at USC. Prior to USC, I worked as an analyst to detect fraud, waste, and abuse in government programs. Before then, I obtained degrees in Applied Mathematics, Economics, and Operations Research from UC Santa Barbara and UC Berkeley respectively. Some of my research interests include computer vision. Outside of academics, I enjoy all things outdoors and sports like skiing or basketball. 

2. What is your impression about MCL and USC?

USC is a beautiful campus, and I really appreciate the warm weather, especially coming from San Francisco. As for MCL, it has been a great experience to learn from some of the brightest people I have been around. I’ve especially enjoyed hearing about other MCL member’s research projects, and it’s exciting to be a part of such a wonderful community. I am also grateful for the support that Professor Kuo is willing to provide to all his students given how busy he is.

3. What is your future expectation and plan in MCL?

I will be working on dehazing using green learning techniques for this upcoming year. I am hoping to prove the feasibility of green learning techniques for the dehazing task and present my work to others in the MCL/computer vision community.

We are so happy to welcome a new MCL member, Alexander Jou joining MCL this semester. Here is a quick interview with Alexander:

1. Could you briefly introduce yourself and your research interests?

My name is Alexander Jou and I am a first year Master’s Student at USC studying Electrical Engineering. Before attending USC, I received my undergraduate degree from the University of California at Berkeley with a double major in Statistics and Economics. I am interested in Artificial Intelligence and using it to develop tools to improve people’s quality of life. Outside of school I enjoy golfing, surfing, and playing soccer. 

2. What is your impression about MCL and USC?

I am very glad to be a part of the passionate community that MCL fosters. In each of our weekly seminars, you can see the strong desire of both Professor Kuo and the students to continually develop new breakthroughs. Professor Kuo speaks not only with incredible understanding, but also an innate belief that we are doing meaningful work that can impact the field. This creates a very hard-working and enjoyable environment which breeds a lot of success.

3. What is your future expectation and plan in MCL?

I am currently working on a paper to apply Green Learning to detect cardiovascular diseases through analysis of heart sounds. My goal is to conduct a thorough review of green learning’s applicability to this challenge and write a paper on my findings. I also plan on collaborating with peers in the lab to develop other useful tools using Artificial Intelligence that can help people’s lives. 

We are so happy to welcome a new MCL member, Youngrae Kim joining MCL this semester. Here is a quick interview with Youngrae: 1. Could you briefly introduce yourself and your research interests?

My name is Youngrae Kim, and I am a first-year PhD student in Computer Engineering at USC. Before starting my PhD, I completed my undergraduate studies at Hongik University and earned my master’s degree at the Korea Advanced Institute of Science and Technology (KAIST). My research interests lie in computer vision, machine learning, and green learning. Outside of academics, I enjoy hiking, working out, and traveling.

What is your impression of MCL and USC?

For me, MCL is an impressive research institute where there’s a strong sense of trust, not only in academic collaborations but also on a personal level. The community is welcoming, and I’ve felt a great sense of support from everyone here. I’m excited to be advised by Professor Kuo, one of the leading researchers in computer vision. The atmosphere at USC is also fantastic—people seem genuinely happy, enjoying life while working hard. I’m very glad to have joined USC, particularly MCL.

What are your future expectations and plans in MCL?

During my PhD, I plan to focus on Federated Learning for the medical domain. I expect to encounter various challenges in applying this technology to real-world scenarios, and I aim to address these through my research, ultimately proposing a comprehensive thesis that has practical applications. I also look forward to collaborating with peers in different areas, which I believe will broaden my academic perspective.