🏆 Announcing the Winners of Amazon KDD Cup 2023: Get To Know Them

:wave:t3: Hello [Name],

:hourglass_flowing_sand: Amazon KDD Cup 2023 Challenge saw more than :busts_in_silhouette: 1990+ participants from :earth_americas: 60+ counties making :rocket: 10000+ submissions! Thank you for being an active participant.

:trophy: Here are the winners for the Amazon KDD Cup 2023 Challenge.

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:tada: Meet The Winners


Chris Deotte
After completing a B.A. in mathematics, Chris ventured into diverse fields such as graphic artistry, photography, carpentry, and teaching. Driven by a passion for computational science, Chris pursued a Ph.D. in mathematics with a focus on computational science. Currently, Chris holds the position of senior data scientist at Nvidia and proudly holds the esteemed title of a quadruple Kaggle Grandmaster.

Benedikt Schifferer:
Benedikt Schifferer, a manager of a deep learning team at NVIDIA, has a master’s degree in data science from Columbia University. With extensive experience in developing recommender systems for a German ecommerce company and serving as a data science consultant at McKinsey, Benedikt brings a wealth of knowledge to the field. Currently focusing on recommender systems at NVIDIA, Benedikt’s expertise spans various domains in the industry.

Jean-Francois Puget:
I am Jean-Francois Puget, also known as CPMP. I am a French national and currently work in France as the currency director at NVIDIA, where I lead a team of Kaggle competition grandmasters who showcase NVIDIA tools and hardware in machine learning competitions. Prior to joining NVIDIA, I obtained a PhD in Machine Learning in the previous century. I then worked on mathematical optimization and constraint programming at a startup and later at IBM. During my time at IBM, I transitioned back to machine learning and started participating in ML competition platforms to stay updated on the current state of the art in ML practices. Machine learning has been a passion of mine since my PhD, and I have published over 80 scientific papers in peer-reviewed conferences and journals. However, I have shifted my focus from publishing to demonstrating the value of my ideas through success in ML competitions.

Kazuki Onodera
After graduating from the Faculty of Economics, Kazuki Onodera worked as a financial consultant, where Kazuki was involved in creating models to analyze default risk. Subsequently, Kazuki gained experience in the recommendation system field at a major e-commerce site. Kazuki is currently working as Senior Deep Learning Data Scientist at NVIDIA. Kazuki has a lot of experience in RecSys comp and has been a Kaggle Competition Grandmaster since 2019 and has had six top two competition rankings.

Gilberto Titericz
Gilberto works as a Senior Data Scientist at NVIDIA. Prior to NVIDIA, he worked at Airbnb, Petrobras and Siemens. He is well known for his extensive track record in winning data science competitions and split his time between video games and machine learning. Gilberto holds a master’s degree in Electrical Engineering from UTFPR, Curitiba, Brazil.


He Zhouzhou:
I’m He Zhouzhou, also known as zzh, based in China. I hold a Bachelor’s degree in Computer Software Engineering from Northwestern Polytechnical University. Currently, I work at Mgtv (Hunantv.com Interactive Entertainment Media Co., Ltd.) and specialize in developing algorithms and an AI engineering framework for recommendation systems. I have previously won the RecSys Challenge 2022 and this challenge marks my second competition experience. Although I don’t have any specific interests, I greatly appreciate the platform this challenge provides to showcase talents. Throughout the competition, I discovered intriguing patterns in the data that proved valuable for my work. However, the challenge’s computational requirements posed a challenge due to limited resources, especially spare GPUs. Thank you for the opportunity to participate.

Wentao Tang:
Wentao Tang, hailing from China, holds B.E. and M.E. degrees from Huazhong University of Science and Technology. Currently associated with MGTV (Happy Sunshine Interactive Entertainment Media Co., Ltd.), Wentao has been actively involved in recommender systems for the past 2 years. When not immersed in AI, Wentao enjoys traveling, running, and playing badminton. As a competitor in the Amazon KDD Cup 2023 Challenge, Wentao finds it an honor to compete alongside world-class players.

Ye Tang:
Ye Tang, hailing from China, holds a Master of Computer Science and Technology degree from Nanjing University. Currently part of the AI Department in MGTV Corporation, Ye Tang’s interests lie in machine learning algorithms used in Recommendation Systems, Computer Vision, and Natural Language Processing. Participating in the KDD Cup 2023 Challenge, Ye Tang finds the competition’s dataset to be challenging, with various imbalances and sub-tracks. The team’s approach revolves around thoroughly exploring business features to enhance performance.

Jiangwei Luo:
Jiangwei Luo, currently a senior algorithm engineer with MGTV Corporation in Changsha, Hunan Province, China, specializes in recommendation algorithm research and development. Proficient in feature engineering, data analysis, and designing specialized modeling approaches, Jiangwei’s research interests lie in recommendation systems, data mining, and deep learning. With a Computer Science and Technology degree from Hunan University, Jiangwei has secured five gold medals in Kaggle and holds the title of Kaggle Competitions Grandmaster. Participating in the Amazon KDD Cup 2023 has provided invaluable experience and knowledge, showcasing Jiangwei’s skills and innovative abilities in the field.


Chenwang Wu:
Chenwang Wu, also known as “ustc-gobble” on AIcrowd, is currently pursuing a Ph.D. degree at the University of Science and Technology of China in Hefei, China. His research focuses on secure recommender systems and trustworthy machine learning, with his works being presented at prestigious journals and conferences such as TPAMI, SIGKDD, and SIGIR. Participating in the Amazon KDD Cup 2023 Challenge has been a thrilling experience for Chenwang, competing against the best players worldwide and witnessing the intensity of the competition. He extends his gratitude to the organizers for their hard work in bringing this remarkable event to a successful conclusion.

Leyan Deng:
Leyan Deng, hailing from China, is currently pursuing a Ph.D. degree at the University of Science and Technology of China in Hefei. Her research interests lie in anomaly detection and spatial-temporal data mining. Her works have been published in renowned journals and conferences, including TNNLS, TKDE, and NeurIPS.

Zhihao Zhu:
Zhihao Zhu, also from China, is currently pursuing a Ph.D. degree at the University of Science and Technology of China in Hefei. His research focuses on secure graph neural networks and recommender systems, and his works have been presented at prestigious conferences such as WWW and PKDD.

Defu Lian:
Defu Lian, from China, holds a Ph.D. degree in computer science from the University of Science and Technology of China in Hefei. He is a prolific researcher with numerous publications in referred journals and conference proceedings, including ACM Transactions on Intelligent Systems and Technology, ACM Transactions on Information Systems, and IEEE Transactions on Knowledge and Data Engineering, among others. Defu’s research interests encompass spatial data mining, recommender systems, and learning to hash.


Yuxuan Lei (Fire in AIcrowd):
Yuxuan Lei is a Ph.D. candidate in the Computer Science Department at the University of Science and Technology of China (USTC), jointly guided by Microsoft Research Asia (MSRA). His current research revolves around cross-domain sequential recommendation and large language models for recommendation. Prior to his Ph.D., Yuxuan received his B.S. degree from USTC in 2022. Participating in the Amazon KDD Cup 2023 has provided Yuxuan with a deeper understanding of engineering details in recommender systems and has fueled his enthusiasm and thinking regarding cutting-edge topics in cross-domain recommendation. The competition has instilled in him persistence and continuous learning skills for future research endeavors.

Xiaolong Chen (CXL in AIcrowd):
Xiaolong Chen is a first-year graduate student in the School of Data Science at the University of Science and Technology of China (USTC), under the guidance of Prof. Defu Lian. His research interests lie in recommendation systems and their intersection with other domains, such as natural language processing (NLP). Before joining USTC, Xiaolong received his B.S. degree from Harbin Engineering University (HEU) in 2022. Participating in the KDD Cup 2023 has provided Xiaolong with a deeper understanding of recommendation system models, particularly the significance of text features, which will inspire his future research.

Peiyan Zhang (xu_tai_yu_ in AIcrowd):
Peiyan Zhang is a Ph.D. candidate in the Computer Science and Engineering Department at the Hong Kong University of Science and Technology (HKUST). His research interests revolve around graph representation learning and trustworthy recommender systems. Prior to joining HKUST, Peiyan received his B.S. degrees in Computer Science from the Beijing Institute of Technology in 2020. Despite the complex and intense nature of the competition, Peiyan thoroughly enjoyed every moment of it. Participating in the KDD Cup 2023 challenged him to think critically, strive for innovation, and continually learn. It pushed him beyond his comfort zone, leading him to discover new strategies, tools, and a profound passion for recommender systems.

Jianxun Lian (master2023 in AIcrowd):
Jianxun Lian is a senior researcher at Microsoft Research Asia, focusing on recommender systems and deep learning techniques, particularly knowledge-aware recommendations, sequential user modeling, and social recommendations.

Defu Lian (Dove in AIcrowd):
Defu Lian is a professor at the School of Computer Science and Technology, University of Science and Technology of China (USTC). He holds a B.E. and Ph.D. degree in computer science from USTC. His research interests encompass spatial data mining, recommender systems, and learning to hash.

We Bare Bear

Honghee Lee:
I am Honghee Lee, a Master’s student at Sungkyunkwan University (SKKU) in South Korea, under the guidance of Prof. Youngjoong Ko. My research focuses on knowledge-grounded dialogue systems, with a recent interest in persona-consistent dialogue systems. Throughout the competition, generating the next product titles presented challenges, including multilingual issues and cold-start problems. Exploring various techniques, from simple statistical models to complex language models, provided valuable insights into session-based recommendations in demanding environments.

Youngjae Chang:
Greetings! I am Youngjae Chang, currently pursuing a master’s program at Sungkyunkwan University in South Korea. As a member of SKKU NLP LAB, my research revolves around different aspects of Natural Language Processing. I have worked on domain adaptation techniques, multi-party conversations, and multimodal systems. Lately, my focus has shifted to large language models and parameter-efficient fine-tuning. The title prediction task in the competition proved challenging due to the vast number of products and sessions. Applying methods I was accustomed to, such as dual encoders using transformers, was not feasible. This experience enlightened me on the power of lightweight methods and simple heuristics.

Kyuri Choi:
Hello, I’m Kyuri Choi from South Korea, currently pursuing a Master’s degree at the Natural Language Processing Lab at Sungkyunkwan University (SKKU). Under the supervision of Prof. Youngjoong Ko, my research has primarily centered around few-shot and zero-shot text classification, along with a dedication to AI ethics and mitigating bias in pretrained language models. Recently, I have developed an interest in Explainable AI, particularly in its application to QA systems. Participating in Task 3 of the KDD Cup, the ‘Next Product Title Generation’ challenge, taught me the significance of thoroughly understanding the data and leveraging simple yet effective methods. I am sincerely grateful for this invaluable opportunity. Thank you.


senkin13 is a data scientist with a bachelor’s degree in applied mathematics. Currently working at DataRobot, they are passionate about using AI technology to solve complex machine learning problems for customers. In addition to their professional pursuits, senkin13 has a keen interest in data science competitions, football, and traveling. Reflecting on the challenge, senkin13 finds it well-designed and challenging, with strong competitors. They are grateful for the opportunity to achieve a prize and have learned valuable new technologies throughout the process.

Zhongshan Huang:
Zhongshan Huang is a mechanical engineer with experience in predicting the life of materials through statistical methods. With a passion for AI technology, Zhongshan has participated in other AI challenge platforms to enhance their skills and knowledge. Currently based in Beijing, China, Zhongshan is excited to contribute their expertise to this well-designed and challenging competition.

I am from China and hold a Master’s Degree. Currently, I work at Meituan, China, with a specialization in industrial Recsys. Over the past 5 years, I have gained extensive experience in this field and achieved several gold medals in Kaggle competitions. While my primary focus is on Recsys, I am also actively learning and exploring NLP and CV. Thank you for the opportunity to share my journey and interests.