Invited Talks
Fundamentals of graph learning and its real-world applications to network alignment, Osaka University, Osaka, Japan, June 2024.
Exploiting the potential of graph filtering for collaborative filtering, KSIAM Spring Annual Meeting (Special Session), Daegu, Korea, May 2024.
Introduction to generative AI and recent trends, Ajou University, Suwon, Korea, May 2024.
A study on node ordering in autoregressive generative diffusion models on graphs, COSEIK Annual Conference (Special Session), Jeju Island, Korea, April 2024.
Graph filtering for multi-criteria recommendation, COSEIK Annual Conference (Special Session), Jeju Island, Korea, April 2024.
Graph learning vs. graph filtering, National Institute for Mathematical Sciences (NIMS), Seongnam (Pangyo), Korea, March 2024.
Graph learning vs. graph filtering, Hanyang University, Seoul, Korea, March 2024.
Federated GNN-to-MLP using contrastive learning, KICS-Winter Conference (Special Session), Pyeongchang, Korea, February 2024.
When recommender systems meet graph diffusion models, Convergence Technology Conference (CTCon), Okinawa, Japan, December 2023.
The next frontier of recommender systems, Posts and Telecommunications Institute of Technology (PTIT), Hanoi, Vietnam, December 2023.
Introduction to generative AI and recent trends, Kyung Hee University, Yongin, Korea, November 2023.
Real-time prediction of breast cancer location using physics-aware graph learning based artificial intelligence, KICS-Fall Conference (Special Session), Gyeongju, Korea, November 2023 (presented by K. Lee).
A graph-based generative diffusion method for traffic flow forecasting, KICS-Fall Conference (Special Session), Gyeongju, Korea, November 2023 (presented by H. Park).
Sophisticated graph filtering for accurate recommendation, KICS-Fall Conference (Special Session), Gyeongju, Korea, November 2023 (presented by J.-D. Park).
Precise interpretation of graph attention networks, KICS-Fall Conference (Special Session), Gyeongju, Korea, November 2023 (presented by Y.-M. Shin).
Graph neural networks meets XAI: A model-level explanation perspective, KSIAM Fall Annual Meeting (Special Session), Gwangju, Korea, November 2023.
Scrutinizing the potential of criteria for recommendation, Hanyang University, Seoul, Korea, September 2023.
Fundamentals of graph neural networks and various research challenges, AI Summer School at Inha University, Virtual Event, August 2023.
The next frontier of recommender systems, California State University Long Beach, Long Beach, CA USA, August 2023.
Towards the design of effective graph learners, Coding Information Theory Workshop (CITW), Seoul, Korea, August 2023.
ChatGPT meets recommendation, 6G Forum - Service Committee, Seoul, Korea, August 2023.
Conversational recommender systems: ChatGPT meets recommendation, Hankyong National University, Anseong, Korea, July 2023.
Introduction to graph neural networks and their applications to heterogeneous graphs and challenges, Workshop on Artificial Intelligence for Industrial Mathematics, Jeju Island, Korea, June 2023.
Introduction to graph neural networks and their applications, Korea Internet Conference (KRnet), Seoul, Korea, June 2023.
The design of effective graph learners using MLPs and knowledge distillation, KICS Summer Conference (Special Session), Jeju Island, Korea, June 2023.
Oversmoothing alleviation in graph neural network-based multi-criteria recommender systems, KICS - Coding Information Theory Workshop (CITW), Jeju Island, Korea, June 2023.
Introduction to graph neural networks and their applications to heterogeneous graphs and challenges, IEIE Communication Society Workshop, Virtual Event, May 2023.
Beyond big data: Spatial big data, Hankyong National University, Anseong, Korea, May 2023.
Beyond big data: Spatial big data, Big Data Science Concert, Haeseong Girls' High School, Seoul, Korea, April 2023.
Fundamentals of graph neural networks and their real-world applications to network alignment, SAARC Colloquium at KAIST, Virtual Event, March 2023.
Recommender systems using graph neural networks, NIMS & KSIAM-AI Winter School, Seongnam(Pangyo), Korea, February 2023.
Towards MLPs as efficient graph learners, A3 Foresight Program - AI-Based Future IoT Technologies and Services Workshop, Seoul, Korea, February 2023 (presented by Y.-M. Shin).
Challenges on predicting drug responses using graph neural networks, A3 Foresight Program - AI-Based Future IoT Technologies and Services Workshop, Seoul, Korea, February 2023 (presented by N. Kang).
Graph neural networks on heterogeneous graphs, Korea University, Seoul, Korea, February 2023.
Overlapping community detection via network exploration, Convergence Technology Conference (CTCon), Ho Chi Minh City, Vietnam, December 2022 (presented by Y. Hou).
Community detection meets exploratory learning, A3 Foresight Program - AI-Based Future IoT Technologies and Services Workshop, Tokyo, Japan, December 2022 (presented by Y. Hou).
Network alignment meets feature augmentation, A3 Foresight Program - AI-Based Future IoT Technologies and Services Workshop, Tokyo, Japan, December 2022 (presented by J.-D. Park).
Design of a unified framework for data-importance-aware scheduling based on one-shot distributed feature learning in ultra-low latency environments, KICS Fall Conference (Special Session), Gyeongju, Korea, November 2022.
Trends and challenges in drug response prediction using graph neural networks, KICS - Coding Information Theory Workshop (CITW), Gyeongju, Korea, November 2022.
Towards new challenges on recommender systems using graph neural networks, International Conference on ICT Convergence (ICTC) - Special Session, Jeju Island, Korea, October 2022.
Graph neural networks and their applications to learning of recommender systems, POSTECH Mathematical Institute for Data Science (MINDS), Virtual Event, October 2022.
Empowering network alignment via graph neural networks, Hanyang University, Seoul, Korea, October 2022.
Graph and deep learning, Sookmyung Women's University, Seoul, Korea, September 2022.
Case analysis of spatial big data, Chonnam National University, Virtual Event, September 2022.
Fundamentals of graph neural networks and their real-world applications to network alignment, National Institute for Mathematical Sciences (NIMS), Suwon (Gwanggyo), Korea, August 2022.
SiReN: Told you sign is important in graph neural networks!, Coding Information Theory Workshop (CITW), Seoul, Korea, August 2022.
SiReN: Told you sign is important in graph neural networks!, Hankyong National University, Anseong, Korea, July 2022.
Graph neural networks and their applications to learning theory of recommender systems, A Minicourse in Machine Learning and Reinforcement Learning, Virtual Event, July 2022.
Graph neural networks and challenges on their applications to recommender systems, Workshop on Artificial Intelligence for Industrial Mathematics, Jeju Island, Korea, June 2022.
Beyond big data: Spatial big data, Science Concert, Yonsei University of College of Science, Seoul, Korea, June 2022.
Graph neural networks and challenges on their applications to recommender systems, AI Frontiers Summit, Seoul, Korea, May 2022.
Spatial big data and its applications to social networks, Hankyong National University, Anseong, Korea, May 2022.
Terahertz meets transport capacity, JCCI, Sokcho, Korea, April 2022.
Data importance-aware scheduling for delay-sensitive edge systems, JCCI, Sokcho, Korea, April 2022 (presented by J.-Y. Kim).
Graph neural networks and their applications to recommender systems, Computational Math Seminar, KAIST, Daejeon, Korea, April 2022.
On the geo-big data: A data scientific perspective, SungKyunKwan University, Suwon, Korea, March 2022.
"Who is my Avatar?": On the power of gradual network alignment, A3 Foresight Program - AI-Based Future IoT Technologies and Services Workshop, Virtual Event, February 2022.
Data importance-aware scheduling for exploiting diversity of distributed data, KICS Winter Conference (Special Session), Pyeongchang, Korea, February 2022 (presented by J.-Y. Kim).
Turbo-PAGE: GNN explanations via fast prototype discovery, KICS - Coding Information Theory Workshop (CITW), Pyeongchang, Korea, February 2022 (presented by Y.-M. Shin).
Graph neural networks: Empowering graph representation learning, KSIAM Fall Annual Meeting, Busan, Korea, December 2021.
An understanding of graph representation learning, Coding Information Theory Workshop (CITW), Seoul, Korea, November 2021.
Gradual network alignment, KICS - Coding Information Theory Workshop (CITW), Yeosu, Korea, November 2021 (presented by J.-D. Park).
Practical challenges in real-world Mathematics: Data science meets Mathematics, Department of Mathematics at Yonsei University, October 2021.
Personalized preference-aware caching via learning, IEEE Region 10 Symposium (TENSYMP), Jeju Island, Korea, August 2021.
A tutorial on recommender systems and their applications with neural networks, Electronics and Telecommunications Research Institute (ETRI), Daejeon, Korea, July 2021.
Edgeless embedding: Inference from Nothing, Hankyong National University, Anseong, Korea, July 2021.
A tutorial on network embedding, Chungnam National University, Daejeon, Korea, June 2021.
Edgeless network embedding in attributed networks, KICS - Coding Information Theory Workshop (CITW), Jeju Island, Korea, June 2021 (presented by Y.-M. Shin).
"Likes or dislikes?": Improved recommendation using network embedding, Poster Exhibitions, School of Mathematics and Computing, Yonsei University, Seoul, Korea, May 2021 (presented by C. Seo).
Introduction to the game theory and Netflix platform, Hankyong National University, Anseong, Korea, May 2021.
Caching versus learning: A deeper understanding of preference-aware caching in mobile networks, JCCI, Busan, Korea, April 2021.
Network completion: A new research paradigm in data analytics, Mathematics Colloquium at Yonsei University, Virtual Event, April 2021.
Network completion: Beyond matrix completion, A3 Foresight Program - AI-Based Future IoT Technologies and Services Workshop, Virtual Event, February 2021.
Improving diversity of top-N recommendation using network embedding, KICS - Coding Information Theory Workshop (CITW), JeongSeon, Korea, February 2021.
"Don't worry! Will find you": Edgeless network embedding, Poster Exhibitions, School of Mathematics and Computing, Yonsei University, Seoul, Korea, November 2020 (presented by Y.-M. Shin).
Personalized preference learning for caching: A data analytics perspective, International Conference on ICT Convergence (ICTC) - Special Session, Jeju Island, Korea, October 2020.
6G + AI: Future avenues for industrial applications, KIPS - IT 21 Global Conference, Seoul Korea, September 2020.
Network completion: Beyond matrix completion, Hankyong National University, Anseong, Korea, September 2020.
Artificial intelligence from an electrical engineer's perspective, Hanyang University, Virtual Event, August 2020.
Secrecy performance analysis of wireless network with potential eavesdroppers, KICS - Coding Information Theory Workshop (CITW), Pyeongchang, Korea, August 2020 (presented by B. C. Jung).
Network completion: Beyond matrix completion, KICS - Coding Information Theory Workshop (CITW), Pyeongchang, Korea, August 2020.
Deep learning on graphs, Hanyang University, Seoul, Korea, August 2020.
Network completion: Beyond matrix completion, POSTECH Wireless Summit, Pohang, Korea, July 2020.
Artificial intelligence from an electrical engineer's perspective, KMS Spring Meeting, Virtual Event, July 2020.
Deep learning on graphs, KMS Spring Meeting, Virtual Event, July 2020.
Introduction to recommender systems and their applications: Netflix meets Internet-of-Things, Korean Maritime and Ocean University, Virtual Event, June 2020.
Introduction to recommender systems and their applications: Netflix meets Internet-of-Things, Industrial AI Seminar, Seongnam, Korea, January 2020.
Introduction to machine learning in social networks/Internet of Things and its applications, KSCSE Machine Learning Winter School, Jeongseon, Korea, December 2019.
Introduction to deep learning in social networks and its applications, Hanyang University, Ansan, Korea, December 2019.
Introduction to deep learning in social networks and its applications, KIPS Lecture Series, Seoul, Korea, November 2019.
Deep learning on graphs: Network embedding in incomplete networks, ShanghaiTech-Yonsei Mathematics Conference, Shanghai, China, November 2019 (presented by Y.-M. Shin).
Learning from uncertainty: Network completion meets machine learning applications, ShanghaiTech-Yonsei Mathematics Conference, Shanghai, China, November 2019.
Introduction to game theory/recommender systems and their applications, Sookmyung Women's University, Seoul, Korea, November 2019.
Big data services based on recommender systems and their application to smart factories, Smart Factory Joint Workshop in the 5G Forum, Seoul, Korea, August 2019.
Learning from uncertainty in big data analytics, Hankyong National University, Anseong, Korea, July 2019.
Huge challenges on big social data analytics: Learning from uncertainty, KSIAM, Seoul, Korea, May 2019.
Huge challenges on big social data analytics using geo-information, Hanyang University, Seoul, Korea, April 2019.
Understanding fundamentals of recommender systems: How Netflix works, Hankyong National University, Anseong, Korea, April 2019.
Introduction to machine learning in social networks: Network embedding, KICS Workshop on Future Communication Technologies, Seoul, Korea, April 2019.
Understanding fundamentals of recommender systems: How Netflix works, CSE Winter School, Seoul, Korea, January 2019.
Understanding fundamentals of recommender systems: How Netflix works, Chungnam National University, Daejeon, Korea, November 2018.
Community recovery meets graph recovery: A data mining perspective, The University of Hong Kong, Hong Kong, November 2018.
Fundamentals of recommender systems and their applications, The University of Hong Kong, Hong Kong, October 2018.
Understanding fundamentals of recommender systems: How Netflix works, Harvard Kennedy School, Cambridge, MA USA, October 2018.
Machine learning trends: Introduction to recommender systems and their applications, IEIE Summer Workshop, Daejeon, Korea, August 2018.
Spatio-textual clustering on social media, Hanyang University, Seoul, Korea, August 2018.
Community recovery meets graph recovery: A data mining perspective, Coding Information Theory Workshop (CITW), Jeju Island, Korea, June 2018.
Community recovery meets graph recovery, Chung-Ang University, Seoul, Korea, May 2018.
The effect of missing nodes and edges on community detection, JCCI, Yeosu, Korea, May 2018.
Community recovery meets graph recovery, Hanyang University, Seoul, Korea, February 2018.
Multi-cell-aware opportunistic random access, Korean Railway Research Institute (KRRI), Eiwang, Korea, January 2018.
Applications of machine learning in big social networks, Korea Information Processing Society, Seoul, Korea, August 2017.
Applications of machine learning in big social networks, Chung-Ang University, Seoul, Korea, July 2017.
Six degrees of separation and Erdos-Bacon number, Hankyong National University, Anseong, Korea, May 2017.
Huge challenges on Twitter analytics using geo-information, Sogang University, Seoul, Korea, March 2017.
Take note of big social data, Chungnam National University, Daejeon, Korea, December 2016.
Huge challenges on big social data analytics using geo-information, Chung-Ang University, Seoul, Korea, November 2016.
Huge challenges on Twitter analytics using geo-information, Hankyong National University, Anseong, Korea, October 2016.
Huge challenges on big data analytics using geo-information, Chonbuk National University, Jeonju, Korea, August 2016.
Tutorial on Big data application technologies: Huge challenges on big data analytics using geo-information, IKEEE Summer Conf., Incheon, Korea, July 2016.
Tutorial on Big data/data mining: Huge challenges on big data analytics using geo-information, KICS Summer Conf., Jeju Island, Korea, June 2016.
Huge challenges on Twitter analytics using geo-information, Chung-Ang University, Seoul, Korea, May 2016.
Introduction to game theory and its real-world applications, Dongduk Womens University, Seoul, Korea, May 2016.
Twitter analytics using geo-information: Data collection, JCCI, Sokcho, Korea, April 2016.
Take note of big social data, The creative center for convergence culture, Seoul, Korea, February 2016.
Huge challenges on Twitter analytics using geolocation information, Chungnam National University, Daejeon, Korea, December 2015.
Close coupling between Engineering and Social Science: Big social data analytics, Hankyong National University, Anseong, Korea, December 2015.
Huge challenges on Twitter analytics using geolocation, The University of Electro-Communications, Chofu, Tokyo, Japan, November 2015.
Huge challenges on Twitter analytics using geolocation, Korea National University of Transportation, Chungju, Korea, November 2015.
Google Maps meet Twitter for location-based services, Coding Information Theory Workshop (CITW), Seoul, Korea, October 2015.
Friendship analysis in space: Complex networks meet Twitter, Seoul National University, Seoul, Korea, August 2015.
Big data analysis via Twitter API, Korean Railway Research Institute (KRRI), Eiwang, Korea, August 2015.
Friendship analysis in space: Complex networks meet Twitter, Hankyong National University, Anseong, Korea, July 2015.
Friendship analysis in space: Complex networks meet Twitter, Coding Information Theory Workshop (CITW), Seoul, Korea, May 2015.
Friendship analysis in space: Complex networks meet Twitter, Hanyang University, Seoul, Korea, May 2015.
Friendship analysis in space: Complex networks meet Twitter, Google Korea, Seoul, Korea, May 2015.
Interference management via elastic routing in wireless networks, JCCI, Buyeo, Korea, April 2015.
Big data analysis via Twitter API, Konkuk University, Seoul, Korea, March 2015.
Opportunistic interference alignment in poor scattering channels, POSTECH, Pohang, Korea, January 2015.
Interference alignment for cognitive radio systems, Cognitive Radio Technol. Workshop, Seoul, Korea, November 2014.
A huge challenge with directional antennas: Elastic routing, ICTC, Busan, Korea, October 2014.
A brief overview of diversity-multiplexing tradeoff, Hankyong National University, Anseong, Korea, October 2014.
Mobile networks meet social networks, Kwangwoon University, Seoul, Korea, September 2014.
A brief overview of diversity-multiplexing tradeoff, Gyeongsang National University, Tongyeong, Korea, August 2014.
Mobile networks meet social networks, UNIST, Ulsan, Korea, July 2014.
Recent results on large-scale ad hoc networking - Part II, Hankyong National University, Anseong, Korea, July 2014.
Recent results on large-scale ad hoc networking, MCW, Jeju Island, Korea, June 2014.
Recent results on large-scale ad hoc networking - Part I, Hankyong National University, Anseong, Korea, June 2014.
How can one intelligently combine interference alignment with opportunism?, KAIST, Daejeon, Korea, May 2014.
How can one intelligently combine interference alignment with opportunism?, JCCI, Yeosu, Korea, April 2014.
Opportunistic interference alignment for downlink cellular networks, JCCI, Yeosu, Korea, April 2014 (presented by H. J. Yang).
Opportunistic downlink interference alignment, Coding Information Theory Workshop (CITW), Seoul, Korea, February 2014.
Opportunism in multiuser networks, Yonsei University, Incheon, Korea, February 2014.
An asymptotic approach of in-network computation: A brief sketch of the proof, Hankyong National University, Anseong, Korea, December 2013.
Codebook-based opportunistic interference alignment, Coding Information Theory Workshop (CITW), Seoul, Korea, October 2013 (presented by H. J. Yang).
Distributed networks: Firefly communications, Mongolian University of Science and Technology (MUST), Ulaanbaatar, Mongolia, July 2013.
On the effects of user scaling over capacity in MIMO interfering uplink, JCCI, Kyungju, Korea, May 2013 (presented by B. C. Jung).
On the multi-user diversity in interference-limited MIMO networks, JCCI, Kyungju, Korea, May 2013 (presented by B. C. Jung).
Bind date theory & game theory, Hankyong National University, Anseong, Korea, April 2013.
Can one achieve multi-user diversity in interference-limited environments?, Coding Information Theory Workshop (CITW), Seoul, Korea, October 2012 (presented by B. C. Jung).
Opportunism in multiuser networks, Korea University, Seoul, Korea, August 2012.
Applications and implementation issues of the hierarchical cooperation scheme, KAIST Institute (KI), Daejeon, Korea, August 2012.
Opportunistic interference alignment for MIMO IMAC: Effect of user scaling over degrees-of-freedom, Coding Information Theory Workshop (CITW), Suwon, Korea, May 2012.
On the optimal degrees-of-freedom in interference-limited cellular networks, JCCI, Kangwon, Korea, April 2012 (presented by B. C. Jung).
A study on the design of D2D systems, Electronics and Telecommunications Research Institute (ETRI), Daejeon, Korea, May 2012.
Linear algebra applicable to computer science, Sejong University, Seoul, Korea, December 2011.
Linear algebra applicable to computer science, Gyeongsang National University, Tongyeong, Korea, December 2011.
Interdisciplinary studies and introduction to ocean IT, Sejong University, Seoul, Korea, May 2011.
On the research paradigm of underwater networks: Issues and solutions, POSTECH Ocean Science & Technology Institute (POSTI), Pohang, Korea, May 2011.
Interdisciplinary studies and introduction to ocean IT, Gyeongsang National University, Tongyeong, Korea, May 2011.
On the research paradigm of underwater networks: Issues and solutions, Yonsei University, Seoul, Korea, May 2011.
On the research paradigm of underwater networks: Issues and solutions, UNIST, Ulsan, Korea, May 2011.
Opportunistic interference mitigation for cellular networks, Coding Information Theory Workshop (CITW), Seoul, Korea, October 2010 (presented by B. C. Jung).
Communications, signal processing, and their application to biomedical engineering, Department of Neurology at Massachusetts General Hospital (MGH), Boston, MA USA, September 2010.
On the fundamental limit of underwater networks: An information-theoretic perspective, Woods Hole Oceanographic Institution (WHOI), Woods Hole, MA USA, July 2010.
Fundamental limits of wireless and underwater networks: A scaling law perspective, Alcatel-Lucent Bell Labs, Murray Hill, NJ USA, March 2010.
On the fundamental limit of underwater networks: An information-theoretic perspective, Division of Ocean Systems Engineering at KAIST, Daejeon, Korea, January 2010.
Improved power-delay trade-off in wireless ad hoc networks using opportunistic routing, KAIST Networking Seminar Series (KNSS), Daejeon, Korea, September 2007.
Improved power-delay trade-off in wireless ad hoc networks using opportunistic routing, Coding Information Theory Workshop (CITW), Yongin, Korea, February 2007 (presented by S.-Y. Chung).
Non-data-aided joint ML estimation of frequency offset and symbol timing in OFDM systems over time-varying frequency selective channels, Tsinghua-KAIST Joint Workshop, Beijing, China, July 2004.