Xiaoli Li's Home Page - Nanyang Technological University

Xiaoli is currently a department head (Machine Intellection department, consisting of 100+ AI and data scientists, which is the largest AI and data science group in Singapore) and a principal scientist at the Institute for Infocomm Research, A*STAR, Singapore. He is a technical director of AI for Manufacturing COE (AIMfg) supported by MTI (35m). He also holds adjunct professor position at Nanyang Technological University (He was holding adjunct position at National University of Singapore for 6 years). He is an IEEE Fellow and Fellow of Asia-Pacific Artificial Intelligence Association (AAIA). He has been recognized as Clarivate's Highly Cited Researcher. Xiaoli is also serving as KPMG-I2R joint lab co-director. He has been a member of Information Technology Standards Committee (ITSC) from ESG Singapore and Infocomm Media Development Authority (IMDA) since 2020. Moreover, he serves as a health innovation expert panel member for the Ministry of Health (MOH), expert panel member for Ministry of Education (MOE), as well as an AI advisor for the Smart Nation and Digital Government Office (SNDGO), Prime Minister s Office, highlighting his extensive involvement in key Government and industry initiatives.

The Machine Intellection department has established itself as a leader in the industry, with a proven track record of successful collaborations with various partners, including SIA, KPMG, Lam Research, GLOBALFOUNDRIES, DBS, Singtel, Mclaren, AIA, Standard Chartered Bank, NEC, and NCS. Moreover, the department has also achieved remarkable success on the international stage, having won prestigious competitions such as the IJCAI Competition (Stage 1), which is considered the top AI Conference in the world, in 2015, and KDD Cup (Part of First Place Winning Team), which is the best data mining competition in the world, in the same year. Additionally, the department also emerged victorious in the GE Flight Quest Challenge in 2013, further solidifying its reputation as a world-class research team.

Research: Xiaoli's research interests span a wide range of topics, including data mining, machine learning, artificial intelligence, and bioinformatics. He is highly respected in the academic community and has served in various leadership positions (Area Chairs/Senior PC members/workshop chairs/session chairs) in the most prominent AI/data mining/machine learning related conferences such as KDD, ICDM, SDM, PKDD/ECML, ACML, PAKDD, WWW, IJCAI, AAAI, ACL, and CIKM. Additionally, he has also edited six books and has numerous highly cited papers, with over 20,000 citations and 70+ h-index. In recognition of his outstanding contributions to the field, Xiaoli's global standing in the field of Computer Science has been acknowledged by his ranking at #713 among the Best Scientists by Research.com. Additionally, Stanford University has recognized his contributions, designating me as one of the world's top 2% scientists in the AI domain. His research has been widely published in top-tier academic journals and conference proceedings, and some of his representative publications can be found at the following link: publications

• Time Series Data Analytics (more than 3000 citations). Xiaoli's contributions to the field of time series sensor data analytics are particularly noteworthy. His groundbreaking work has been widely cited, with over 4000 citations to date. As one of the pioneers in this area, he was one of the first researchers to formulate the sensor feature learning problem using deep neural networks. His seminal paper on this topic, presented at the IJCAI conference in 2015, has been cited over 1,500 times, highlighting the significance and impact of his research. In addition to his early work in sensor feature learning, Xiaoli has also made significant contributions to deep learning-based remaining useful life prediction. His research in this area has been widely recognized and cited, with his paper on this topic having been cited over 1,100 times. Overall, Xiaoli's work has had a significant impact on the field of time series sensor data analytics, and his contributions continue to shape research in this area.
• Positive unlabelled based learning (more than 3000 citations). Xiaoli's contributions to positive unlabelled (PU) based learning have been widely recognized and cited, with over 3000 citations to his work. He was instrumental in formulating the PU learning problem, and the term itself was coined in his 2005 paper, co-authored with Prof Bing Liu, presented at the ECML 2005. His seminal work in this area includes papers presented at the ICDM conference in 2003, which has received over 1,000 citations, the ICML conference in 2002, which has over 800 citations, and the IJCAI conference in 2003, which has received over 600 citations. His work has significantly advanced the field of machine learning and has been a catalyst for further research in PU learning.
• Social/biological network mining (more than 3000 citations). Xiaoli's research in social and biological network mining has been highly influential. His contributions in this area have been recognized with three Best Paper Awards at international conferences. His work in social network mining has explored various aspects of social networks, including community detection, rising star detection. He has also made significant contributions to the field of biological network mining, including the development of novel algorithms for gene function prediction, protein complex detection, disease gene prediction and drug discovery.

• Xiaoli is a prolific researcher and has made significant contributions to the fields of AI, NLP/text analytics, and data mining. He has published more than papers at top-tier conferences in these areas. Specifically, he has published 20+ papers at leading AI conferences such as AAAI and IJCAI, which are highly competitive and selective. Additionally, he has published 20+ papers at top NLP/text analytics conferences, including ACL, EMNLP, which are renowned for their contributions to natural language processing and text analytics. Furthermore, Xiaoli has published 20+ papers at top-tier data mining conferences, such as KDD, WSDM, ICDM, SDM, and PKDD, which are known for their innovative approaches to data analysis and knowledge discovery. His extensive contributions to these conferences showcase his expertise in multiple areas and demonstrate his commitment to advancing these fields.

In 2005, Xiaoli Li was honored with the Best Paper Award in the 16th International Conference on Genome Informatics (GIW 2005), recognizing his research in the field of AI for bioinformatics. In 2008, he received the Best Poster Award in the 12th Annual International Conference Research in Computational Molecular Biology (RECOMB 2008). Xiaoli also received the Best Paper Runner-Up Award in the 16th International Conference on Database Systems for Advanced Applications (DASFAA 2011) in recognition of his research on database systems. In addition, Xiaoli's achievements have been recognized in several international benchmarking competitions, including the bioinformatics competition DREAM 2007 USA and the EU activity recognition challenge 2011, where he won two Best Performance Awards. He also received the Best Paper Award in the International Conference on Bioinformatics (InCoB 2016). In 2020, Xiaoli Li was honored with the Best Paper Award Runner-Up in the top Web Analytics conference, the 13th ACM International WSDM Conference (WSDM 2020), for his contribution to the field. In the same year, he was also recognized with the Finalist Academic Paper Award at The IEEE International Conference on Prognostics and Health Management (ICPHM 2020) for his exceptional research. More recently, Xiaoli Li received the Best Paper Award at the 18th IEEE Conference on Industrial Electronics and Applications (ICIEA 2022), further highlighting his excellence in the field.

Xiaoli has published more than 350 peer-reviewed papers across a wide range of disciplines. His research has appeared in some of the most prestigious conferences and journals in the fields of Data Mining, Machine Learning, Artificial Intelligence, Information Retrieval, and Bioinformatics. Specifically, he has published in top-tier conferences such as KDD, ICDM, SDM, PKDD/ECML, PAKDD, ICDE, ICML, IJCAI, AAAI, CVPR, ACL, EMNLP, SIGIR, CIKM, and UbiCom. His work has also been featured in leading journals such as IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Instrumentation & Measurement, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Transactions on Big Data, IEEE Transactions on Sustainable Computing, IEEE Transactions on Vehicular Technology, IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Transactions on Reliability, and more. Notably, Xiaoli has also published many impactful papers in the field of Bioinformatics, which have been featured in top-tier conferences such as ISMB/ECCB, CSB, and in journals such as PLOS Computational Biology, Bioinformatics, BMC Genomics, PLOS ONE, BMC Bioinformatics, Annals of the New York Academy of Sciences, and the Journal of Computational Biology. His work in this area has made significant contributions to the field of genomics and computational biology. Overall, Xiaoli's extensive publication record underscores his broad expertise and his exceptional ability to conduct innovative and impactful research across multiple fields.

Industry Applications: Xiaoli has extensive industry experience in leading research teams to tackle real-world applications. He has successfully led over 10 R&D projects in collaboration with industry partners from various verticals, including leading aerospace, telecom, insurance, and airline companies. His expertise in AI, data mining, and machine learning has enabled him to provide innovative solutions to address the challenges faced by different organizations.