Yanshan Wang serves as the vice chair for research and assistant professor in the University of Pittsburgh Department of Health Information Management. Within his courses and PittNAIL lab, Wang is devoted to research in clinical natural language processing and generative artificial intelligence (AI), and he encourages student involvement in his research.
Read on to learn more about Wang’s background in health informatics (HI) and what he envisions for the future of the field.
Joining Pitt HI
I joined Pitt Health Informatics in May 2021. At the time, I believed there would be a strong demand for health informatics experts and health data scientists as computing infrastructure and digital health data continued to expand. As artificial intelligence and advanced computing have rapidly grown in importance, that demand has become even clearer.
Pitt provides an excellent environment to train the next generation of health informatics professionals who can connect health care, data science and technology.
In the undergraduate program, I contribute lectures to courses such as Foundations of Health Informatics and Information Management, and Health Vocab, Terminology and Classification Systems. At the master’s level, I co-teach modules in Foundations of Health Informatics, as well as Data Analytics and Machine Learning in Health Science. I previously served as the main instructor for courses such as Practical Statistics and Programming in Python & R, and Practical Statistics and Programming in R. I am currently developing a new course, Clinical Natural Language Processing and Large Language Models, which is planned to launch in Fall 2026.
Student Mentorship
Beyond teaching, I mentor both undergraduate and graduate students through research in my Pitt NAIL lab. Many students participate in research projects, assist graduate researchers and postdoctoral scholars and complete capstone projects under my supervision. Some students work as research assistants on funded projects, gaining hands-on experience with real-world health care data and AI applications. Several of these students from my lab have gone on to strong career opportunities or prestigious graduate programs. For example, two HI undergraduate research assistants from my lab got admitted to Yale University and Johns Hopkins University graduate schools.
In the past few years, we have hosted several informatics ground rounds. Undergraduate students are invited to attend these sessions, where we bring in guest speakers to discuss the latest research developments and industry needs in health informatics.
Students often work closely with me on research projects related to artificial intelligence and health care data science. Through these experiences, they gain practical research skills and exposure to real health care challenges. Mentorship in research environments helps students apply classroom knowledge to meaningful real-world problems.
Teaching Style
My teaching style is very practical and hands-on. Many of the topics I teach involve programming, machine learning and artificial intelligence, which require active practice rather than passive learning. I encourage students to engage directly with the code, as the best way to learn these technical skills is through hands-on practice.
As an NIH-funded researcher, my work involves developing cutting-edge solutions in health informatics. The most exciting thing about teaching is bringing real-world problems and real-world needs for health informatics into teaching and telling students what the reality of the health care system is and what the real needs in research are. What I feel really excited about is not only teaching what the textbook says but introducing students to the real problems we encounter when collaborating with UPMC physicians and other health care systems. This helps students understand the skills and knowledge that are truly needed in the field.
Collaboration Across Disciplines
Collaboration across disciplines is essential in health informatics. I work with faculty from the Schools of Medicine, Nursing, Pharmacy, Dentistry and other research groups across the University. Through my role with the Clinical and Translational Science Institute (CTSI), I collaborate with researchers who bring clinical data and research questions that require advanced informatics solutions. I’m also leading a working group nationally in the national electronic records network, where I collaborate with more than 12 or 13 institutions all over the nation. Informatics is fundamentally about connecting people and solving real-world problems using data and technology. Working across disciplines allows us to combine clinical knowledge with technical expertise to build better health care solutions.
Interest in HI
I began working in health informatics in the early 2010s, when many researchers from computer science and information science started applying their expertise to health care data.
Health informatics allows you to develop technology that directly improves patient care. Whatever you develop in health informatics—you can visibly see your effort improving patient care. That’s the most rewarding part. While some technology careers may offer higher salaries, there is a unique satisfaction in knowing that your work is helping improve people’s health. That meaningful impact is what makes health informatics such a compelling field.
What Sets Pitt HI Apart
One major advantage of Pitt Health Informatics is its close connection with UPMC, one of the largest health care systems in the United States. This creates strong opportunities for collaboration, research and career development. The University of Pittsburgh is also one of the top NIH-funded research institutions, making it a highly research-intensive environment where students can gain firsthand experience with cutting-edge projects.
With AI becoming a hot topic, we are improving our curriculum and involving more topics on AI. In the next four or five years, students will learn more about how to use AI technology in health informatics. We have a lot of exciting new courses coming up.
Research Interests
My research focuses on clinical natural language processing and generative AI, particularly large language models applied to health care data. We develop new AI methodologies as well as real-world health care applications. Our projects involve building AI systems that assist clinicians with decision-making, analyzing clinical text data and supporting health care research. These tools can improve how health care professionals interpret data and deliver care.
Many current health care systems rely on general guidelines that do not always account for individual patient differences. Our research aims to develop AI systems that enable more personalized health care decisions. By analyzing clinical data more effectively, these technologies can support better diagnoses, treatment recommendations and research insights. Ultimately, the goal is to improve patient outcomes and provide more individualized care.
My lab maintains an open lab policy, meaning students interested in research can contact me and join lab discussions and projects. One thing I encourage students to do is actively explore research opportunities. Many faculty members, including myself, offer opportunities for students to participate in research labs and real-world projects. These experiences can significantly enhance students’ learning and career development. I always encourage students to reach out, ask questions and get involved early in their academic journey.
Other Roles at Pitt
In addition to my role in the Health Information Management Department, I serve as the director of generative AI in the Computational Pathology and AI Center of Excellence (CPACE) at the School of Medicine. I also direct the Clinical Natural Language Processing Center, which provides research services and expertise for investigators working with clinical text data. I am a co-director of the Data Science Module in the CTSI, where we provide consulting and technical support for health care research projects. These roles allow students to engage with interdisciplinary research and collaborate with faculty and clinicians across the university.
Fun Facts
One fun fact about me is that I still enjoy playing video games. If any students play League of Legends, they are welcome to add my username and play together sometime. It’s a fun way to relax and connect outside of research and teaching.
Read More
SHRS AI Researcher Awarded NIH Fellowship to Improve Standards and Accessibility of Clinical Health Data
The AIM-AHEAD FHIR Collaborative Training Program will help with ongoing efforts to leverage AI and large language models to transform clinical data from hospitals into a standardized format that enables researchers to easily access and analyze.
Read the full story