Junyoung Hwang

AI Engineer with strong expertise in designing and deploying agentic AI systems within mobility environments. Skilled in building vehicle-integrated AI agents that deliver personalised, context-aware services by leveraging real-time driving and user data.

Experienced in developing and optimising AI agents for Android-based automotive platforms, ensuring low-latency performance and efficient resource utilisation under constrained hardware conditions. Proficient in Agentic AI , and advanced algorithm design, with the ability to translate complex AI models into robust, production-ready systems.

• KDD Cup’23, Amazon Multilingual Recommendation Challenge, 9th place
• 3rd KAKAO ARENA, Melon Playlist Recommendation Challenge, Bronze Prize
• 한국 대학생 프로그래밍 경시대회, 동상, 2016-11-05
• 한국 대학생 프로그래밍 경시대회, 동상, 2014-11-08
• 2016 Coder’s High, sponsored by NEXON, Advanced to onsite final round (11th place)
• ACM-ICPC Asia, Advanced to 2016 ACM-ICPC, Asia, Daejeon, Korea (11th place)
• ACM-ICPC Asia, Advanced to 2016 ACM-ICPC, Asia, NhaTrang, Vietnam
• ACM-ICPC Asia, Advanced to 2014 ACM-ICPC, Asia, Daejeon, Korea (13th place)
• ACM-ICPC Asia, Advanced to 2014 ACM-ICPC, Asia, Bangkok, Thailand
• ACM-ICPC Asia, Advanced to 2013 ACMICPC, Asia, Daejeon, Korea (15th place)
• ACM-ICPC Asia, Advanced to 2013 ACM-ICPC, Asia, Danang, Vietnam (Honorable Mention)
• Samsung Software Membership Project Award, Android Character Lock Screen using aho-corasick algorithm (1st place)
• 삼성전자 대학생 프로그래밍 경시대회, Advanced to SCPC 2016 onsite final round (Online qualification rounds 1 and 2 passed)
• 숭실대학교 경진대회, 2016 숭실대학교 IT학부 프로그래밍 경진대회, 1st place
• 숭실대학교 경진대회, 2014 숭실대학교 IT학부 프로그래밍 경진대회, 1st place
• 숭실대학교 경진대회, 2013 숭실대학교 IT학부 프로그래밍 경진대회, 4th place
• 숭실대학교 경진대회, 2012 숭실대학교 IT 학부 프로그래밍 경진대회, 26th place

• Product Recommendation for cross-market seller, 2022-01-01
• E-commerce Product Recommendation, 2021-01-01
• Btv Content Recommendation, 2020-01-01
• Point-Of-Interests Recommendation from card payment data, 2017-06-01

• A Closer Look at Masked Item Prediction for Sequential Recommendation, J Hwang, W Kweon, S Lee, SH Jang, H Ju, and H Yu (preprint)
• Capturing User Interests from Data Streams for Continual Sequential Recommendation, GS Lee, HS Yu, J Hwang, SK Kang, and H Yu, The ACM Web Search and Data Mining Conference (WSDM’26)
• Multi-Domain Sequential Recommendation via Domain Space Learning, J Hwang, H Ju, SK Kang, SH Jang, and H Yu, ACM SIGIR Conf. on Research and Development in Information Retrieval (SIGIR’24)
• Multi-Domain Recommendation to Attract Users via Domain Preference Modeling, H Ju, SK Kang, D Lee, J Hwang, SH Jang, and H Yu, AAI Conference on Artificial Intelligence (AAAI’24)
• Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering, SK Kang, D Lee, W Kweon, J Hwang, and H Yu, The Web Conference (WWW’22)
• Topology Distillation for Recommender System, SK Kang, J Hwang, W Kweon, and H Yu, ACM Conf. Knowledge Discovery and Data Mining (KDD’21)
• Item-side Ranking Regularized Distillation for Recommender System, SK Kang, J Hwang, W Kweon, and H Yu, Information Sciences, 2021
• PUMAD: PU Metric Learning for Anomaly Detection, H Ju, D Lee, J Hwang, J Namkung
• Deep Rating Elicitation for New Users in Collaborative Filtering, W Kweon, SK Kang, J Hwang, and H Yu, The Web Conference (WWW’20 short)
• Multi-Modal Component Embedding for Fake News Detection, SK Kang, J Hwang, and H Yu, IEEE Int. Conf. Ubiquitous Information Management and Communication (IMCOM’20)
• Semi-Supervised Learning for Cross-Domain Recommendation to Cold-Start Users, SK Kang, J Hwang, D Lee, and H Yu, ACM Conf. Information and Knowledge Management (CIKM’19)
• Action Space Learning for Heterogeneous User Behavior Prediction, D Lee, CY Park, H Ju, J Hwang, and H Yu, Int. Joint Conf. Artificial Intelligence (IJCAI’19)