Tian Guo

Current responsibilities
Tian collaborates closely with Equity Portfolio Managers to design and implement innovative investment strategies. His primary focus lies in developing advanced Machine Learning models that integrate diverse structured and unstructured datasets to enhance alpha prediction. Recently, his efforts have concentrated on fine-tuning Large Language Models for feature extraction and return forecasting. Beyond his research, Tian contributes to the broader Machine Learning community as a reviewer for prestigious conferences such as ICLR, NeurIPS, and ICML.

Career
Tian joined RAM AI in August 2019, bringing a strong academic background from his tenure at the Swiss Federal Institute of Technology, ETH Zurich, where he served as a post-doctoral Scientist from 2017 to 2019. During this time, his research focused on interpretable Deep Learning, Natural Language Processing, automated Machine Learning, multi-task learning and transfer learning. 
Earlier, from 2012 to 2017, Tian pursued his doctoral studies as a Research Assistant at École Polytechnique Fédérale de Lausanne (EPFL), where he worked on neural networks for temporal data, streaming data mining, and distributed Machine Learning. In 2015, he further broadened his expertise by contributing to NEC Laboratories Europe as a member of the Network Data Analytics Research Group.

Education
Tian holds PhD in Computer Science from the Ecole Polytechnique Fédérale de Lausanne (EPFL). Tian graduated from Shanghai Jiao Tong University (SJTU) and the East China University of Science and Technology (ECUST). Tian has an impressive publication record, with contributions to some of the most prestigious conferences in Machine Learning and Data Mining.