User:Xiaolili2r/sandbox

Xiaoli Li (born 1969) is a principal scientist  of computer science who specialized in Artificial Intelligence, data mining, machine learning, Bioinformatics. He is current with Institute for Infocomm Research, A*STAR, Singapore. He also holds adjunct professor position at Nanyang Technological University https://www.ntu.edu.sg/home/xlli/ Xiaoli's web page at Nanyang Technological University.

Academic research

 * 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 3000 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 1,000 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 700 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 800 citations, the ICML conference in 2002, which has over 700 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 2000 citations). Xiaoli's research in social and biological network mining has been highly influential, with over 2000 citations to his work. 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.

Honors and awards

 * In 2023, he was named Fellow of Asia-Pacific Artificial Intelligence Association.
 * In 2024, he was named Fellow of IEEE (Institute of Electrical and Electronics Engineers).