By Dave DeFusco
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 Â鶹´«Ă˝Ół» Museum.
Two of the conference’s most critical sessions will be chaired by Katz School faculty, affirming the school’s thought leadership in the field. Dr. Honggang Wang, chair of the Department of Graduate Department of Computer Science and Engineering and a renowned figure in wireless health technologies, will chair the keynote session delivered by Dr. Wendy Nilsen, deputy division director at the National Science Foundation. Dr. Nilsen’s speech will explore the funding landscape and national priorities in smart health research—a topic that directly intersects with the Katz School’s mission to educate professionals at the convergence of data, health and engineering.
Dr. Ming Ma, assistant professor of computer science at the Katz School, will lead a session showcasing pioneering work in large language models and public health monitoring. These projects explore how artificial intelligence is transforming everything from electrolyte monitoring and clinical decision-making to symptom classification and explainable machine learning.
By leading these discussions, Katz School faculty are not only facilitating vital academic exchange but reinforcing the school’s standing as a national hub for next-generation health technologies. During a short paper session, Lakshmi Priya Ramisetty, a student in the M.S. in Artificial Intelligence, will present her research on optimizing veterinary language models using the cutting-edge Mamba architecture. Her work, co-authored with Dr. Youshan Zhang, highlights the school’s strength in mentoring students to tackle real-world problems with rigorous AI methods.
Ramisetty’s contribution underscores a Katz School hallmark: hands-on, cross-disciplinary training that prepares students to lead in fields where few boundaries exist between computer science, engineering and healthcare.
This year’s sessions feature cutting-edge work from institutions across the globe: from secure federated learning and fairness-optimized synthetic EHR data to deep learning for non-invasive glucose sensing and wearable-based emotion recognition. In addition, there will be panels on women in computing, dementia detection and affective computing. These topics are not just theoretical—they are core to Katz School curricula and research labs, many of which integrate wearable tech, privacy-preserving AI and mobile health innovation.
Connected health is not a single discipline—it’s a fusion of sensing technologies, AI, data science, bioengineering, ethics and clinical knowledge. That’s why Katz School faculty and students thrive in the CHASE community. The school’s programs are deliberately interdisciplinary, designed to prepare a workforce that can interpret streaming medical signals just as easily as it can manage secure cloud infrastructure or design an AI model to assist clinicians.
“CHASE represents exactly the kind of ecosystem Katz is building,” said Dr. Wang. “It’s not enough to build great technology. We want to make sure it’s secure, scalable, reliable—and most of all, usable by the people it’s meant to help.”
