Application Type
Nominate someone else
Your Name
Junghwan Park
Your Email
9bow@pytorch.kr
Please confirm the following:
Nominee Full Name
Dongjun Min
Affiliation / Organization
AI Researcher | PyTorch Korea User Group Organizer | vLLM KR Community Organizer
Nominee Email
petanerd@pytorch.kr
Current Location
Seoul, South Korea
Years of Community Involvement
5+ years
Which platforms or profiles would you like to share?
GitHub Profile
https://github.com/petanerd
GitLab Profile
No response
LinkedIn Profile
https://www.linkedin.com/in/mindongjun/
X / Twitter Profile
https://x.com/petanerd
Personal Website / Portfolio
No response
If 'Other' was selected, please specify
https://scholar.google.com/citations?user=axVAhPcAAAAJ&hl=en , https://pytorch.kr/about
Which PyTorch Foundation projects is the nominee familiar with?
If 'Other' was selected, please specify the project name
No response
How has the nominee contributed to the community?
If 'Other' was selected, please specify
No response
Please describe the nominee’s contributions to PyTorch Foundation projects and communities
Dongjun Min is an AI researcher, educator, and community leader based in South Korea who has contributed to the PyTorch ecosystem through technical education, community building, mentorship, and advocacy.
He has been actively using PyTorch since 2018 for both academic research and industrial AI development. During graduate studies, he conducted research on transformer-based long-term time-series forecasting, and he has continued working with PyTorch across multimodal AI, large language models, video understanding, speech technologies, and AI infrastructure systems.
Since January 2026, he has served as an organizer of the PyTorch Korea User Group (PyTorch KR), helping coordinate technical events, knowledge-sharing sessions, and networking opportunities for the local PyTorch community.
He is also an organizer of the vLLM KR, a practitioner-focused community centered around vLLM and large-scale AI inference systems.
The vLLM KR Community Meetup is organized approximately every one to two months by identifying companies actively using vLLM in production and inviting them to host technical events. Each meetup typically gathers 30–40 practitioners to discuss topics such as LLM serving, inference optimization, AI infrastructure, offloading techniques, and production deployment experiences.
Across PyTorch KR and vLLM-related community activities, he has helped organize events that attracted more than 490 registrations and over 240 attendees. One representative example was a recent vLLM KR Community Meetup hosted by Lablup, which received more than 85 applications for only 30 available seats and focused on vLLM offloading techniques, inference optimization, and the adoption of newly introduced vLLM features. He also served as a staff organizer for the 2026 vLLM Korea Meetup, supported by Rebellions.
Beyond community leadership, he is active in education and mentorship. In April 2026, he delivered a lecture and mentoring session at Sunchon National University titled "Why PyTorch Still Matters in the Age of Agentic AI." The session emphasized that even as higher-level AI frameworks and agentic abstractions become more common, PyTorch remains the foundational layer for model development, optimization, and deployment. It also provided students with a practical roadmap for AI engineering, spanning PyTorch fundamentals, model training, inference, and deployment.
Professionally, he works as an AI researcher developing multimodal AI systems, including large language models, video understanding systems, speech technologies, and multimedia AI applications.
He is currently helping organize PyTorch Day Korea, a PyTorch-focused community conference expected to bring together 200–300 participants from academia and industry. He is involved in CFP operations and program planning, helping build a platform for knowledge sharing across the Korean PyTorch ecosystem.
His contributions focus on building sustainable communities where practitioners can learn from one another, openly share knowledge, and contribute back to the broader PyTorch ecosystem. These efforts closely align with the Foundation's values of openness, collaboration, and community-driven innovation.
Why does the nominee want to become a PyTorch Foundation Ambassador?
The nominee believes that strong local communities are essential to the long-term success of open-source AI ecosystems.
South Korea has become one of the most active regions for open-source AI development, large language model adoption, multimodal AI research, and inference infrastructure. However, there remains significant opportunity to expand awareness, education, and participation around PyTorch Foundation projects.
Through his work with PyTorch KR and vLLM KR, he has witnessed how community-driven education and knowledge sharing accelerate technology adoption and create pathways for students, researchers, and engineers to become active participants in open-source ecosystems.
As a PyTorch Foundation Ambassador, he hopes to strengthen the connection between the Korean AI community and the global PyTorch Foundation ecosystem. He aims to support this mission through community events, workshops, mentorship initiatives, educational content creation, and technical advocacy.
He is particularly interested in helping practitioners better understand and adopt technologies related to PyTorch, vLLM-based inference systems, multimodal AI, large-scale model serving, and open-source AI infrastructure.
Over the next two years, he hopes to expand PyTorch Foundation community activities throughout South Korea while helping local practitioners become more connected to the broader global open-source AI community.
How would this nominee contribute as a PyTorch Foundation Ambassador?
As a PyTorch Foundation Ambassador, the nominee would focus on five primary areas.
-
Community Building
He would continue organizing PyTorch KR and vLLM KR community activities, including technical meetups, networking events, and practitioner-focused discussions. He would also continue identifying companies operating PyTorch Foundation technologies in production and encourage them to share their experiences with the broader community.
-
Technical Education and AI Infrastructure Advocacy
He would create workshops, technical talks, and educational content focused on PyTorch Foundation technologies, with particular emphasis on vLLM-based inference systems, LLM serving, multimodal AI infrastructure, and production AI deployments. He is especially interested in helping practitioners understand and adopt scalable inference architectures, on-premise and on-device AI systems, and emerging agentic AI workflows powered by open-source technologies.
-
Mentorship and Inclusion
He would continue mentoring students and early-career engineers while helping lower the barrier to entry for new contributors within the PyTorch ecosystem. He is particularly interested in supporting students and practitioners who are transitioning into AI engineering and open-source development.
-
Regional Community Growth
He would collaborate with universities, research labs, startups, and industry organizations throughout South Korea to expand awareness and participation in PyTorch Foundation projects.
-
Global Community Engagement
He would actively share lessons learned from the Korean AI ecosystem with the global PyTorch Foundation community, while introducing global best practices and technical developments to local practitioners.
Through PyTorch KR, vLLM KR, and PyTorch Day Korea, he aims to foster a community where practitioners can openly share real-world experience in building and serving AI systems on the PyTorch ecosystem, and to help establish a stronger bridge between PyTorch users, inference practitioners, and the broader open-source AI community across South Korea.
Ambassador Focus Areas
If 'Other' was selected, please specify
No response
Primary Community Region
Asia
If 'Other' was selected, please specify
No response
Primary Country During Ambassador Term
South Korea
Additional Information (Optional)
Highlights
- Active PyTorch user since 2018
- Graduate research on transformer-based long-term time-series forecasting
- Organizer, PyTorch Korea User Group (2026–Present)
- Organizer, vLLM KR Community Meetup (vLLM is a PyTorch Foundation–hosted Platform Project)
- Staff Organizer, 2026 vLLM Korea Meetup (supported by Rebellions)
- Community events with 490+ registrations and 240+ attendees; representative event (vLLM KR × Lablup): 85+ applications for 30 seats, covering vLLM offloading and production inference
- Speaker at multiple AI and infrastructure-related technical sessions
- Lecturer and Mentor, Sunchon National University (April 2026): "Why PyTorch Still Matters in the Age of Agentic AI"
- AI Researcher specializing in multimodal AI, video understanding, speech technologies, and LLM-based systems
- Co-organizer, PyTorch Day Korea (2026, expected 200–300 attendees) — CFP operations and program planning
Supporting Links
Future Goals
- Expand PyTorch and vLLM community activity throughout South Korea
- Promote practical knowledge sharing on inference systems and AI infrastructure
- Support community discussions around agentic AI systems built on open-source technologies
- Expand awareness of on-device and edge AI applications powered by the PyTorch ecosystem
- Strengthen collaboration among academia, industry, and the open-source community
- Build stronger connections between Korean practitioners and the global PyTorch Foundation ecosystem
Application Type
Nominate someone else
Your Name
Junghwan Park
Your Email
9bow@pytorch.kr
Please confirm the following:
Nominee Full Name
Dongjun Min
Affiliation / Organization
AI Researcher | PyTorch Korea User Group Organizer | vLLM KR Community Organizer
Nominee Email
petanerd@pytorch.kr
Current Location
Seoul, South Korea
Years of Community Involvement
5+ years
Which platforms or profiles would you like to share?
GitHub Profile
https://github.com/petanerd
GitLab Profile
No response
LinkedIn Profile
https://www.linkedin.com/in/mindongjun/
X / Twitter Profile
https://x.com/petanerd
Personal Website / Portfolio
No response
If 'Other' was selected, please specify
https://scholar.google.com/citations?user=axVAhPcAAAAJ&hl=en , https://pytorch.kr/about
Which PyTorch Foundation projects is the nominee familiar with?
If 'Other' was selected, please specify the project name
No response
How has the nominee contributed to the community?
If 'Other' was selected, please specify
No response
Please describe the nominee’s contributions to PyTorch Foundation projects and communities
Dongjun Min is an AI researcher, educator, and community leader based in South Korea who has contributed to the PyTorch ecosystem through technical education, community building, mentorship, and advocacy.
He has been actively using PyTorch since 2018 for both academic research and industrial AI development. During graduate studies, he conducted research on transformer-based long-term time-series forecasting, and he has continued working with PyTorch across multimodal AI, large language models, video understanding, speech technologies, and AI infrastructure systems.
Since January 2026, he has served as an organizer of the PyTorch Korea User Group (PyTorch KR), helping coordinate technical events, knowledge-sharing sessions, and networking opportunities for the local PyTorch community.
He is also an organizer of the vLLM KR, a practitioner-focused community centered around vLLM and large-scale AI inference systems.
The vLLM KR Community Meetup is organized approximately every one to two months by identifying companies actively using vLLM in production and inviting them to host technical events. Each meetup typically gathers 30–40 practitioners to discuss topics such as LLM serving, inference optimization, AI infrastructure, offloading techniques, and production deployment experiences.
Across PyTorch KR and vLLM-related community activities, he has helped organize events that attracted more than 490 registrations and over 240 attendees. One representative example was a recent vLLM KR Community Meetup hosted by Lablup, which received more than 85 applications for only 30 available seats and focused on vLLM offloading techniques, inference optimization, and the adoption of newly introduced vLLM features. He also served as a staff organizer for the 2026 vLLM Korea Meetup, supported by Rebellions.
Beyond community leadership, he is active in education and mentorship. In April 2026, he delivered a lecture and mentoring session at Sunchon National University titled "Why PyTorch Still Matters in the Age of Agentic AI." The session emphasized that even as higher-level AI frameworks and agentic abstractions become more common, PyTorch remains the foundational layer for model development, optimization, and deployment. It also provided students with a practical roadmap for AI engineering, spanning PyTorch fundamentals, model training, inference, and deployment.
Professionally, he works as an AI researcher developing multimodal AI systems, including large language models, video understanding systems, speech technologies, and multimedia AI applications.
He is currently helping organize PyTorch Day Korea, a PyTorch-focused community conference expected to bring together 200–300 participants from academia and industry. He is involved in CFP operations and program planning, helping build a platform for knowledge sharing across the Korean PyTorch ecosystem.
His contributions focus on building sustainable communities where practitioners can learn from one another, openly share knowledge, and contribute back to the broader PyTorch ecosystem. These efforts closely align with the Foundation's values of openness, collaboration, and community-driven innovation.
Why does the nominee want to become a PyTorch Foundation Ambassador?
The nominee believes that strong local communities are essential to the long-term success of open-source AI ecosystems.
South Korea has become one of the most active regions for open-source AI development, large language model adoption, multimodal AI research, and inference infrastructure. However, there remains significant opportunity to expand awareness, education, and participation around PyTorch Foundation projects.
Through his work with PyTorch KR and vLLM KR, he has witnessed how community-driven education and knowledge sharing accelerate technology adoption and create pathways for students, researchers, and engineers to become active participants in open-source ecosystems.
As a PyTorch Foundation Ambassador, he hopes to strengthen the connection between the Korean AI community and the global PyTorch Foundation ecosystem. He aims to support this mission through community events, workshops, mentorship initiatives, educational content creation, and technical advocacy.
He is particularly interested in helping practitioners better understand and adopt technologies related to PyTorch, vLLM-based inference systems, multimodal AI, large-scale model serving, and open-source AI infrastructure.
Over the next two years, he hopes to expand PyTorch Foundation community activities throughout South Korea while helping local practitioners become more connected to the broader global open-source AI community.
How would this nominee contribute as a PyTorch Foundation Ambassador?
As a PyTorch Foundation Ambassador, the nominee would focus on five primary areas.
Community Building
He would continue organizing PyTorch KR and vLLM KR community activities, including technical meetups, networking events, and practitioner-focused discussions. He would also continue identifying companies operating PyTorch Foundation technologies in production and encourage them to share their experiences with the broader community.
Technical Education and AI Infrastructure Advocacy
He would create workshops, technical talks, and educational content focused on PyTorch Foundation technologies, with particular emphasis on vLLM-based inference systems, LLM serving, multimodal AI infrastructure, and production AI deployments. He is especially interested in helping practitioners understand and adopt scalable inference architectures, on-premise and on-device AI systems, and emerging agentic AI workflows powered by open-source technologies.
Mentorship and Inclusion
He would continue mentoring students and early-career engineers while helping lower the barrier to entry for new contributors within the PyTorch ecosystem. He is particularly interested in supporting students and practitioners who are transitioning into AI engineering and open-source development.
Regional Community Growth
He would collaborate with universities, research labs, startups, and industry organizations throughout South Korea to expand awareness and participation in PyTorch Foundation projects.
Global Community Engagement
He would actively share lessons learned from the Korean AI ecosystem with the global PyTorch Foundation community, while introducing global best practices and technical developments to local practitioners.
Through PyTorch KR, vLLM KR, and PyTorch Day Korea, he aims to foster a community where practitioners can openly share real-world experience in building and serving AI systems on the PyTorch ecosystem, and to help establish a stronger bridge between PyTorch users, inference practitioners, and the broader open-source AI community across South Korea.
Ambassador Focus Areas
If 'Other' was selected, please specify
No response
Primary Community Region
Asia
If 'Other' was selected, please specify
No response
Primary Country During Ambassador Term
South Korea
Additional Information (Optional)
Highlights
Supporting Links
Future Goals