“Always question the story data tells because the right questions, not just the right tools, uncover the truth and create real impact.” This is the main lesson that M.S. in Applied Analytics (APAN) program lecturer Bum Chul Kwon wishes to impart to his students.
With a Ph.D. in data visualization from Purdue University, Kwon has extensive experience at the intersection of data and health care. His work in developing machine learning systems and predictive models at IBM Research aims to advance the clinical use of these technologies to solve real-world problems in the field of medicine. Kwon teaches Storytelling with Data, a course required for APAN students.
Recently, Kwon was honored with the 10-Year Test of Time Award at IEEE VIS 2024 for a paper he co-authored with his colleagues in 2014. The award recognizes published articles whose contents are still vibrant and useful today and have had a major impact and influence within and beyond the visualization community
In a recent conversation with SPS, Kwon shared how he seeks to bridge education and research by inspiring students to explore the potential of AI in health care. His goal is to equip them with the knowledge and skills to tackle today’s challenges and shape tomorrow’s solutions.
Can you tell us a bit about your background and your current role?
I am a researcher specializing in data visualization, artificial intelligence, and health care. Together with our team at IBM Research, I aim to develop novel computational approaches to accelerate scientific learning in medicine, health care, and drug discovery. I collaborate with world-class researchers from various institutes, actively contributing to research activities with diverse teams.
What interests you about machine learning algorithms and data visualization literacy?
Both topics are crucial for fostering understanding, trust, and usability in data-driven decision-making systems. Transparency in machine learning (ML) involves designing systems that help users understand how decisions or predictions are made. This is particularly critical in contexts like health care. Achieving this requires explainable AI techniques to show how algorithms reach conclusions. In my previous research, I developed numerous interactive visualization systems that combine AI and intuitive visual designs to help users grasp AI-driven decision-making processes.
Visualization literacy refers to the ability to read, understand, and interpret data. I have conducted several studies aimed at measuring and enhancing this skill. My ongoing mission is to teach students how to critically evaluate visualizations, effectively tell stories through data, and develop AI-integrated interactive visualization tools to address real-world problems.
What course do you teach?
I teach Storytelling with Data, a required course in the M.S. in Applied Analytics program. My teaching philosophy centers on experiential and active learning in every class. I want my students to construct knowledge by thinking and reorganizing what they have learned instead of passively listening to my lectures. My class includes problem-solving exercises, and I engage with my students by leading them to understand the theoretical concepts behind the exercises.
APAN students are highly motivated and actively engaged in class discussions. Many ask insightful questions, which not only deepens their understanding but also enhances the overall learning experience. This dynamic interaction is where students feel comfortable sharing ideas and exploring new concepts together. Their enthusiasm fosters a collaborative and curious atmosphere, making the course more engaging and intellectually stimulating.
What do you think makes the School of Professional Studies unique?
I believe the community that connects faculty, staff, and students is what makes SPS exceptional. In fall 2023, I organized an event where current students had the opportunity to meet alumni, fostering connections and providing insight into career trajectories. This is a prime example of how the SPS community—including faculty, students, alumni, and staff—supports collective growth by helping one another.
What is the value of an M.S. in Applied Analytics?
A master’s degree in Applied Analytics equips professionals with skills to leverage data for informed decision-making across industries such as health care, finance, and technology. With the growing reliance on machine learning and predictive models, this degree combines technical proficiency with domain-specific knowledge, enabling graduates to design data-driven solutions to address real-world challenges. The program also offers the opportunity to join an applied analytics community, fostering collaboration and keeping professionals at the forefront of emerging trends and tools in the evolving data landscape.
What do you see for the future of health care and machine learning?
There are many analytical challenges in health care, particularly when working with large-scale, multi-modal datasets to uncover insights into disease progression patterns, optimal care pathways, and effective novel interventions. To advance understanding, it is crucial for clinical researchers to test hypotheses using appropriate data analytics techniques.
In the near future, AI decision-making systems could be integrated into day-to-day clinical practice. In this context, it is important to evaluate whether AI is fair and accurate, especially among concerns that datasets used to train AI models could exacerbate existing societal gaps. Future research must focus on identifying ways to address and resolve these issues.
About the Program
Columbia University’s Master of Science in Applied Analytics prepares students with the practical data and leadership skills to succeed. The program combines in-depth knowledge of data analytics with the leadership, management, and communication principles and tactics necessary to impact decision-making at all levels within organizations.
The fall 2025 application priority deadline for the M.S. in Applied Analytics program is February 15. The final deadline is June 1. Learn more about the program here.
