紳士漫畫

Chengyi Liu, a student in the artificial intelligence program, is helping teach machines to recognize human activities in a way that鈥檚 smarter, safer鈥攁nd more private. At the Katz School鈥檚 Graduate Symposium on Science, Technology and Health, Liu presented his research on improving human activity recognition using millimeter wave (mmWave) radar and large language models, the AI engines behind tools like ChatGPT.

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At the recent 2025 IEEE/ACM CHASE Conference, Lakshmi Priya Ramisetty, a 2024 graduate of the M.S. in Artificial Intelligence, introduced a new kind of artificial intelligence鈥攐ne not built for tech giants or billion-parameter showdowns, but for veterinarians. Her presentation revealed a powerful, domain-specific AI model designed to process the long and complex medical texts common in animal healthcare.

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What if a tiny ring on your finger could tell when you鈥檙e stressed, predict your heart health and alert you to dangerous changes in your body鈥攁ll in real time? That鈥檚 the bold promise behind new research presented by a Katz School team that unveiled a 鈥渄igital twin鈥� healthcare framework powered by smart rings in London at the 2025 IEEE INFOCOM Conference, a top-ranked conference on networking in the research community. 

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Dr. Yucheng Xie, an assistant professor in the Department of Graduate Computer Science and Engineering, and a team of computer scientists and engineers developed the DietWatch, a groundbreaking dietary monitoring system for people to track their eating habits in using just a regular smartwatch.

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Katz School faculty and students will join other academic, industry and governmental leaders from around the globe to present transformative ideas at the crossroads of health and technology at the IEEE/ACM Conference on Connected Health: Applications, Systems, and Engineering Technologies (CHASE) from June 24 to 26 at 紳士漫畫 Museum.

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At the Katz School of Science and Health鈥檚 Graduate Symposium on Science, Technology and Health, Nikhil Deekonda, a student in the M.S. in Artificial Intelligence, unveiled the idea behind an AI-powered mobile app, called LungAware, designed to detect and classify lung cancer from CT scans.

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A team of Katz School researchers has solved one of the biggest headaches in modern machine learning鈥攈ow to make AI models that can adapt to new information without needing to start over from scratch鈥攂y developing a deep learning system that updates itself using new information about the world without retraining, and does so in a way that鈥檚 easier to understand.

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At the Spring 2025 Graduate Computer Science and Engineering Research forum, the future of technology wasn鈥檛 merely on display鈥攊t was actively being built. In their research presentations, Katz School students showcased the kind of ingenuity, technical depth and ethical awareness that are not only rare in graduate education but transformative in the real world.

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A team of researchers has developed PolypSEAG-Net鈥攁 novel deep learning model that enhances polyp segmentation in colonoscopy images. Their work, recently presented at the ACM/IEEE International Conference on Connected Health, will contribute to the advancement of medical image analysis and colorectal cancer detection.

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A team of researchers led by Dr. David Li, director of the M.S. in Data Analytics and Visualization e M.S. in Data Analytics and Visualization developed a framework that significantly improves how AI understands 鈥渓ow-resource languages鈥濃�攍anguages that lack the massive training datasets available for English, Spanish or Mandarin.

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At the 2025 IEEE Integrated STEM Education Conference at Princeton University in March, Katz School researchers presented a study, 鈥淎utomatic Teaching Platform on Vision Language Retrieval Augmented Generation (VL-RAG),鈥� which introduces an AI-powered teaching system that integrates visual learning with dynamic, interactive content to enhance student comprehension and engagement.

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In a recent study, 鈥淢utual Information Reduction Techniques and its Applications in Feature Engineering,鈥� researchers in the Graduate Department of Computer Science and Engineering explore which mutual information "features" matter most in machine learning models.

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Researchers in the Katz School鈥檚 Graduate Department of Computer Science and Engineering are turning to advanced tools like reinforcement learning鈥攁 type of machine learning that mimics decision-making in dynamic, uncertain environments鈥攖o probe consumer habits.

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Imagine a future where streaming videos, video calls or surveillance footage look flawless, no matter the network conditions or quality variations. That鈥檚 the goal of a recent Katz School study, which will be presented at the 2025 IEEE Conference in January.

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Dr. David Sweet, an industry professor in the Katz School鈥檚 Graduate Department of Computer Science and Engineering, has developed a method for improving how computers optimize complex tasks.

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The Department of Graduate Computer Science and Engineering recently hosted a dynamic presentation of graduate student research, showcasing innovative capstone projects, independent studies and other research initiatives in Artificial Intelligence, Computer Science, Cybersecurity and Data Analytics and Visualization.

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Designing a great video game is a balancing act, especially in strategy games where the thrill often comes from tackling the unexpected. Whether it鈥檚 an enemy ambush or a rare loot drop, the element of surprise keeps players on their toes. But too much randomness can feel unfair, while too little can make a game predictable and boring. Enter the world of probability-driven game design, a method that introduces structured uncertainty into gameplay. A new framework introduced by Katz Schoo researchers uses mathematical tools to strike this balance, creating levels that are not only engaging but varied and challenging.

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With concentration becoming increasingly difficult to sustain in today鈥檚 fast-paced, distraction-filled environments, accurately monitoring people's focus is critical for boosting productivity, improving educational outcomes and supporting cognitive health.

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Dr. David Li, program director of the M.S. in Data Analytics and Visualization in the Graduate Department of Computer Science and Engineering, have proposed a novel data-driven framework grounded in probability theory and statistical analysis to change how Olympic performance is measured. 

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A team of researchers that includes Dr. Yucheng Xie, assistant professor in the Katz School鈥檚 Graduate Computer Science and Engineering, has developed a new technology called 鈥渕mPalm,鈥� which uses millimeter wave signals to create an ubiquitous, low-effort authentication method through palm recognition.

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Dr. Honggang Wang, chair of the Katz School鈥檚 Department of Computer Science and Engineering, has received a $600,000 grant from the National Institutes of Health to create an artificial intelligence platform that would recognize patterns in longitudinal dietary data. The Innovative Pattern Analysis Tool, called iPAT, would employ a new machine-learning algorithm to facilitate comparisons between individual and population-level dietary patterns, and would generate evidence for dietary guidelines.

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