When I discovered the Center for Biomedical Informatics (now a department), I felt like I had come home! The faculty was brilliant, inspiring, caring and supportive. The staff was knowledgeable and enabling, allowing us to work toward our goals without distraction. The students were among the brightest and most highly motivated people I have ever met, and I felt honored to be among them. At DBMI, students are made to feel an integral part of the department and are guided toward their life goals beyond school. Lifelong bonds as colleagues are formed with both faculty and classmates. As I begin my new career, I only hope that I can inspire my students as I was inspired at DBMI.

One of the strengths of the DBMI program is that the faculty does not treat you as a subordinate, but rather a colleague with the potential to advance the science. This certainly facilitated my relationship with my advisor as well as the other faculty members. The PhD curriculum was rigorous, yet rewarding; I felt the faculty truly cared that I succeed.

After 20 years as a general dentist with an interest in computers, this was an excellent program for aiding me in making the transition into academia. This is an outstanding program for exposing healthcare professionals, academicians and researchers in how technology is changing and will be used in health care for the future.

The five years I spent at DBMI were among the most fulfilling of my life—intellectually and professionally. The lessons I learned—not only through coursework but through exposure to the multiple disciplines that make up medical informatics—remain with me today. I have been a full-time tenure-track academic ever since, am an active participant in medical informatics, and remain committed to integrating multidisciplinary understanding in my research and in my teaching.

Being part of Pitt DBMI was an extraordinary experience that deeply shaped my career. During my joint MS (2012) and PhD (2016) journey, I experienced the full breadth of biomedical informatics: from NLP for influenza detection with Dr. Rich Tsui, to global health informatics in Malawi with Dr. Gerry Douglas and HCI with Dr. Harry Hochheiser. Under the guidance of my PhD advisor, Dr. Vanathi Gopalakrishnan, my dissertation focused on training parsimonious machine learning models to classify lung cancer subtypes, which essentially trims an extremely leafy tree into a manageable, human-interpretable model without losing its core properties. Today, I apply this rigorous training as founder and CEO of Amphora Health. I am deeply grateful to DBMI's leadership and professors: Dr. Greg Cooper, Dr. Shyam Visweswaran, Dr. Milos Hauskrecht and Dr. Becich; and especially to Ms. Toni Porterfield for making my grad school experience truly fantastic from admissions to alumnus. Hail to Pitt!

It began as wanting to help clinicians find the right information at the right time in medical librarianship, but quickly turned into doing the same, but at scale in biomedical informatics. What a wonderful privilege to complete all my secondary education at the University of Pittsburgh, particularly graduate school at DBMI. I am grateful to the many mentors, fellow students and staff at DBMI who contributed to my education and development into the researcher I am today. Hail to Pitt!

Chenyu Li is a Ph.D. student in biomedical informatics. With over five years of research experience, Li’s work primarily focuses on clinical natural language processing (NLP), social determinants of health (SDoH) analytics and the application of artificial intelligence in healthcare. A major component of this research involves investigating how to better integrate SDoH data with clinical and translational science to advance health equity. In addition, Li designs and implements advanced deep learning models for the national Evolve to Next-Gen Accrual to Clinical Trials (ENACT) Network. Recently, Li’s research has heavily emphasized the evaluation and application of large language models (LLMs) in clinical settings, including the development of multi-agent LLM frameworks. In 2026, Li was recognized as a Fellow of the American Medical Informatics Association for sustained professional achievement in applied informatics.

Brittany Gomez is a second-year doctoral GEM Fellow in biomedical informatics. In her personal time, she enjoys hiking, cycling, painting, and volunteering.

Acute respiratory distress syndrome (ARDS) affects 3 million people globally each year. Although current treatments like mechanical ventilation help, they often cause further lung damage and restrict patients to hospital care. Their collaboration aims to revolutionize care for ARDS patients by developing the world’s first remote artificial lung for in-home use.

Gomez's research focuses on creating a robust medical alert system and optimizing device parameters such as oxygen saturation and pump flow, tailoring them to a patient’s specific activities. A key challenge in developing a fully remote system is ensuring that any technical failures are detected early, giving clinicians ample time to intervene. To address this, Gomez is leveraging advanced imaging and computer vision techniques to monitor key physiological markers and inform the alert system.

Most of her work takes place at Carnegie Mellon University’s Robotics Institute, where they develop, test, and refine the remote infrastructure. They are also conducting in-vitro and in-vivo experiments at Allegheny General Hospital. As the project has evolved, what began as individual contributions is now a unified effort, integrating each aspect to make remote, real-time patient care a reality.

Vishal Soman is a second-year master's student in biomedical informatics working under Uma Chandran, PhD, at the Genomics Analysis Core (GAC). The GAC provides data analysis expertise for genomics research in collaboration with the Pitt Center for Research Computing (CRC) and the Pittsburgh Supercomputing Center (PSC). Soman primarily uses Python, Bash, and R, specializing in bulk and single-cell RNA-sequencing analysis, and is based on the fifth floor of DBMI. In addition, he is researching the use of large language models (LLMs) to parse, extract, and integrate structured data from a high volume of publications. In his free time, he enjoys gaming, golfing, and spending time with his fiancée fianceé.