Simone Brazzo

Experienced Artificial Intelligence Research Engineer. The first Italian ISO 42001 AIMS Lead Implementer and one of the pioneers in the EU. Natural leadership, strong communication skills and a great team player. Interested in economics and financial markets.

5 minute read

I’m really excited to share the first post in the series AI Across Borders.

This series aims to feature ideas and experiences in AI from professionals, researchers, engineers, and practitioners around the world.

I am convinced that there is no single way in AI, and that its future must be shaped by diverse voices, cultures, and ideas.

Our first guest is Chanyoung Kim, a top-class PhD student from Yonsei University in South Korea.

Let’s hear his journey and thoughts on AI—over to you, Chanyoung!

Can you briefly introduce yourself and tell about your journey in the field of Artificial Intelligence?

I’m Chanyoung Kim, a Ph.D. student in Artificial Intelligence at Yonsei University in South Korea, advised by Prof. Seong Jae Hwang. My journey in AI began through an undergraduate research internship, where I explored multi-modal representation learning and 3D computer vision, collaborating with NVIDIA Research and Meta Reality Labs. This experience sparked my deep interest in computer vision and has led me to focus on unsupervised open-vocabulary semantic segmentation and multi-modal image synthesis, with several first-author publications at top-tier AI conferences such as CVPR and MICCAI.

What is your current role and what projects are you working on?

Currently, I’m conducting research at the Medical Imaging & Computer Vision Lab at Yonsei University, focusing on open-vocabulary and training-free approaches to semantic segmentation. My recent work includes a CVPR 2025 paper on spectral graph distillation for object-context-aware open-vocabulary segmentation. While my core research has centered on image semantic segmentation, I’m now expanding into related areas such as video segmentation and image matting to broaden the impact and applicability of my methods.

How would you describe the AI ecosystem in your country? What are its strengths and weaknesses?

South Korea’s AI ecosystem is rapidly evolving, supported by strong government initiatives, cutting-edge academic research, and significant industrial investment. Leading universities such as KAIST, Seoul National University, and Yonsei University produce high-impact research in top-tier AI conferences and actively collaborate with global tech leaders like Google, NVIDIA, and Meta. The government has also launched national AI strategies, established specialized graduate programs, and funded large-scale R&D initiatives to foster talent and innovation. Industrially, tech giants like Samsung, LG, Naver, and Hyundai operate advanced AI research labs, while a vibrant startup scene is emerging in fields like healthcare AI, foundation models, and autonomous systems. The synergy between academia and industry enables rapid application of research into real-world solutions across sectors such as manufacturing, mobility, and finance. Despite the presence of highly talented researchers and engineers, one key challenge lies in the limited global visibility of Korean-developed AI platforms and open-source tools, especially when compared to those from the U.S. or China. Additionally, while institution-backed research enjoys substantial support, independent researchers and early-stage startups often face barriers in accessing large-scale public datasets and computing infrastructure. Addressing these challenges could further unlock the potential of Korea’s AI community and enhance its global impact.

Recently South Korea proposed a legislative framework for AI, the “AI Basic Act”. Is there sensitivity on the topic? What are your considerations about it?

Indeed, South Korea’s proposed “AI Basic Act” has been receiving attention and sensitivity due to its direct implications on privacy, safety, and innovation in artificial intelligence. The act emphasizes several critical points: Mandatory watermarking for AI-generated content, including synthetic images and videos, to tackle misinformation and ensure transparency.

  • Defining “High-impact AI”, referring to AI technologies that significantly affect human life, safety, or fundamental rights, and requiring explicit disclosure to users.
  • Local representation requirements for foreign companies to ensure compliance and accountability under Korean laws.
  • Strengthening industry support and cooperation through national committees and ethical advisory bodies to guide AI research and development.
  • Clearly defined penalties for non-compliance, which may involve substantial fines to ensure enforcement.

Given these provisions, I understand the sensitivity surrounding this legislation. Balancing innovation and regulation is a complex challenge. While strict regulations protect citizens and ensure ethical AI use, overly stringent laws may risk stifling creativity and discouraging global collaboration or foreign investment. Thus, careful and inclusive dialogue among policymakers, academia, industry stakeholders, and civil society is crucial to ensure the act supports ethical and transparent AI development without hindering innovation and growth in this rapidly evolving field.

In what areas of AI do you see the greatest opportunities for growth and innovation?

To be honest, I think the greatest momentum right now is with LLMs. Their rapid advancement in reasoning, tool use, and instruction-following has opened up entirely new possibilities, from autonomous agents to code generation and multimodal understanding. The research and industry communities are heavily investing in scaling LLMs and integrating them into real-world systems, and it’s hard to ignore their transformative potential. That said, as someone who works primarily on visual perception tasks like semantic segmentation, I sincerely hope we see a resurgence of interest in perception-driven AI. With the growing need for intelligent systems to understand and interact with the physical world, I believe robotic vision will play a key role in leading this next wave. For AI to truly operate autonomously in open environments, strong perception is not optional, but it’s foundational.

How strong is the collaboration between academia and industry in South Korea?

In South Korea, collaboration between academia and industry is relatively strong in terms of research funding. Major companies like Samsung, LG, and Hyundai often fund joint research projects with universities, which plays a key role in supporting academic labs financially. However, what’s still lacking is direct human exchange, such as internship programs or long-term researcher placements. This is something I personally find unfortunate, as these companies have the resources and technical capabilities to lead in AI, yet they seem to invest less in nurturing the next generation of talent or engaging deeply with emerging research directions. Strengthening these connections would not only benefit students and researchers but also help industry stay at the forefront of innovation in the long run.

What do you think is the future direction of AI in your country in the next 5-10 years?

The Korean government is making visible efforts to invest in AI through national strategies and public initiatives. However, recent economic challenges have led many companies to scale back hiring, causing a growing number of highly skilled AI professionals to move abroad. This talent outflow poses a serious risk to the long-term strength of Korea’s AI ecosystem. To secure a sustainable future, Korea should focus on advancing AI in areas where it already has global competitiveness, such as semiconductors, automotive, manufacturing, healthcare, and pharmaceuticals. Equally important is creating conditions that attract and retain top AI talent, including competitive career opportunities, long-term support, and a culture that values innovation. Over the next decade, the direction of AI in Korea will be defined not only by technological investment but by how effectively the country can build an environment where talent stays, grows, and leads.

Do you have any connection with AI researchers from other countries? Can you expose pros and cons about it?

Yes, I do. I’ve had the opportunity to connect with international AI researchers, mainly through academic conferences. These interactions often lead to valuable research discussions and even collaborations, and I believe that engaging with the global research community is essential for anyone working in AI. One clear advantage is the exchange of diverse perspectives—it helps broaden your understanding of different research cultures and approaches. However, being based in Korea, which is geographically distant from most major AI hubs, especially in the U.S. and Europe, can sometimes make it more challenging to attend conferences in person and build deeper relationships. I believe this physical distance limits some of the spontaneous, face-to-face interactions that are often crucial for long-term collaboration. Still, I try to actively engage whenever possible, and I consider international connections one of the most rewarding parts of being in this field.

If you could change one thing in your country’s AI ecosystem, what would it be?

If I could change one thing, it would be the way we support and treat AI researchers. Korea has a wealth of talented individuals in AI, but many are drawn abroad, especially to U.S. tech companies, because of more competitive salaries, better research environments, and greater access to computing resources. If we could offer researchers compensation and infrastructure that are more on par with global standards, I truly believe Korea has the potential to grow into a global leader in AI. Supporting our researchers properly is not just about retaining talent—it’s about unlocking the full potential of our ecosystem.

What is your advice for young people who want to enter the world of AI in South Korea?

I would encourage young people to step beyond their comfort zone and actively engage with the global research community. It can feel intimidating at first, whether it’s reading papers, joining discussions, or presenting at conferences, but the earlier you start, the faster you grow. Building a global mindset is essential in AI, which is a field that moves forward through international collaboration and shared ideas. Don’t be afraid to reach out, ask questions, or contribute. The research community is more open and welcoming than many people expect, and participating in it will expand both your knowledge and your opportunities.

Thanks to Chanyoung and see you all to the next post!

If I didn't quote you or if you want to reach out feel free to contact me.

© [Simone Brazzo] [2025] - Licensed under CC BY 4.0 with the following additional restriction: this content can be only used to train open-source AI models, where training data, models weights, architectures and training procedures are publicly available.