What I do

AI and data science are changing not only how we build technology but also how we conduct research, make discoveries, and address complex societal problems. My work focuses on helping shape this transformation so that advances in AI lead to better science, stronger innovation, and meaningful benefits for people and communities.

I think about this mission through three interconnected goals.

1. Transforming how research and innovation are done: AI is changing the research lifecycle, from identifying problems and analyzing data to generating hypotheses, designing experiments, and translating discoveries into practical solutions. I am interested in developing new research models in which humans and AI work together effectively, responsibly, and transparently. 

2. Enabling discoveries that were previously difficult: I am particularly interested in ambitious scientific questions where AI can expand human capabilities rather than simply automate existing tasks. What happens when researchers can explore thousands of hypotheses, integrate knowledge across disciplines, or simulate complex systems at unprecedented speed? I want to investigate how AI can help scientists move from incremental improvements toward genuine discoveries. 

3. Making AI serve society: The power of AI also brings significant responsibilities. Communities should not simply be recipients of AI systems. They should have a voice in how those systems are conceived, designed, evaluated, and deployed. My goal is to develop AI and data-driven technologies that support communities, public institutions, education, and social services while remaining accountable to the people they affect. 

The questions that motivate me

 We are entering a period in which some fundamental assumptions about science and innovation deserve to be reconsidered.

• What is the purpose of science in an AI-enabled world?

• What should humans do, and what should AI do, during scientific discovery?

• How do we preserve human judgment, creativity, accountability, and curiosity when AI can generate solutions almost instantly?

• What will the research ecosystem look like when the time between identifying a problem, making a discovery, and translating that discovery into practice becomes dramatically shorter?

These are not questions that belong only to computer science. They involve engineering, education, business, public policy, ethics, and society. I am interested in bringing researchers from these areas together to investigate them rigorously and, equally important, turn the resulting ideas into working systems and real-world experiments.

A major part of my work has therefore focused on AI and data for social good. I collaborate with researchers, students, community organizations, and public institutions to explore how AI can improve decision-making and public services while addressing issues such as reliability, transparency, bias, privacy, and trust.

For me, responsible AI is not simply about placing constraints around technology. It is about designing technology that expands human capability while preserving human agency.

Who I am: 

I am drawn to big questions, complex systems, and the challenge of turning ideas into action.

 My academic journey has taken me across countries, disciplines, research institutes, industry, and universities. I received my Ph.D. in Ubiquitous IT, with a focus on solving the challenges of Ubiquitous Healthcare, from Dongseo University in South Korea. Korea played an important role in shaping how I think about technology and innovation. My experiences with students, professors, researchers, and entrepreneurs showed me how scientific ideas can move beyond laboratories and become technologies, products, and organizations that address real problems. I later conducted postdoctoral research at the National Institute for Mathematical Sciences, where I strengthened my interest in interdisciplinary and computational approaches to developing future Internet architecture research problems. I subsequently worked as a senior member of engineering staff at the Electronics and Telecommunications Research Institute (ETRI) before moving into academia.

These experiences shaped an approach that continues to guide my work today: I do not see research, engineering, entrepreneurship, and education as separate activities. Research creates knowledge. Engineering transforms knowledge into systems. Entrepreneurship and innovation connect those systems with real needs. Education prepares the next generation to improve all three.

Beyond research

Some of the work that matters most to me happens outside traditional academic structures.

 I write and translate about science, technology, innovation, and education because important ideas should be understandable beyond specialist communities. I have also received recognition for my work in technology and innovation, including the Bharatiya Ratna Puraskar.

Volunteer work has been equally important to me. I helped establish an initiative focused on supporting young entrepreneurs and early-career researchers, particularly those trying to transform ideas into meaningful innovations.

 Working with young innovators taught me something that continues to influence how I teach and mentor: many people do not lack ideas. They lack opportunities, confidence, mentorship, networks, or a pathway for turning an idea into something real.

I therefore try to help students and emerging researchers see innovation not as something reserved for a small group of experts, but as a process they can learn. They can identify a problem, ask difficult questions, experiment, fail, improve, collaborate, and eventually create something that matters.

That philosophy also shapes how I think about AI.

The future I want to help build is not one in which AI replaces scientists, engineers, educators, entrepreneurs, or communities. It is one in which AI expands what people are capable of discovering, creating, and contributing.

My long-term goal is therefore simple to state, even if difficult to achieve:

Advance AI that helps us discover more, innovate faster, make better decisions, and solve important problems while keeping people at the center of the process.