I am interested in machine learning in biology and medicine. GuanLab Research Summary
Since 2013, our team has written the majority of the best-performing algorithms in DREAM challenges, the largest systems biology benchmark study. For our achievements in the DREAM challenges and in recognition of the open source software we have contributed to the bioinformatics field, I was awarded as the ‘Consistent Best Technical Performer’; as of now, I am the sole recipient of this award. I am one of the very few people globally who own multiple gold medals in the annual Data Science Bowl by Kaggle.
My team has written many award-winning deep learning methods. In traditional machine learning, I am the inventor of GuanRank, adaptive GPR and several other algorithms that are often used as the reference algorithms in benchmark studies/challenges. Relevant algorithms have been published in leading journals such as Science, Nature Methods, Nature Communication, etc. My writing 'The Art of Best-performing Algorithms' is one of the most widely-read documents in the field. I have coached numerous awardees in diverse machine learning competitions, including not just Ph.D and postdocs in international challenges, but also high school students who placed first in the Southeast Michigan Science Fair, or entered Intel STS finalist.
We welcome students interested in broad areas of machine learning, software engineering, bioinformatics, computational medicine or mathematical biology. Positions are open at all levels and fairly recruited through 1. Passing the 24-hour Guan Lab Entrance Exam; 2. CV submission, interview/trial and voting by current members; 3.Signing off the GuanLab Guide. Interested students may email email@example.com to obtain the Exam, the Voting Form, and the Guide.