Teaching

Course Teaching

✍ Statistics 623-423 Probability in Bioinformatics and Genetics at Rice University

    ☺ Instructors: Professor Marek Kimmel, Professor Wenyi Wang

    This course focuses on the application of probability and statistical models to analyze large-scale biological data in genomics, proteomics, and related fields. It introduces key methods like hidden Markov models, evolutionary models, and statistical tools such as BLAST and mutation calling. Students are expected to have a basic background in probability and statistics, while biological concepts are explained as needed.

    Semsters:

  • Spring 2025: Tue/Thur 9:25-10:40am Maxfield Hall 251
  • Spring 2024: View Syllabus

National Workshop Teaching

✍ CGSI

    CGSI (Computational Genomics Summer Institute) was established to bridge gaps between various subfields of computational genomics and computational medicine by fostering collaboration and interaction. The program combines the structure of a summer school and a scientific conference, featuring tutorials, research talks, and social events throughout the month, which promotes both academic growth and networking, creating a vibrant community for over a hundred researchers and trainees.


✍ SSACB

    SSACB (Spring School on Algorithms for Cancer Biology) aims to foster collaboration between diverse groups of researchers from fields like genomics, mathematics, and computer science by bringing together around 30 faculty and a select group of trainees. The program features talks, tutorials, and discussions on computational methods in cancer biology. Trainees will also showcase their research through posters and lightning talks. Additionally, social activities are included to promote interdisciplinary engagement, creating opportunities for participants to exchange ideas in both formal and informal environments.


✍ LFSA

Community Education

✍ StatsUpAI

    StatsUpAI is a community-driven initiative focused on empowering statisticians to engage more actively in artificial intelligence (AI) research and leadership. The platform emphasizes the integration of statistical methods with AI tools to solve real-world challenges. It provides resources such as curated datasets, review articles, and ready-to-use analysis pipelines, aimed at facilitating advancements in both fields. The goal of StatsUpAI is to foster collaboration, innovation, and leadership among statisticians working at the intersection of statistics and AI, helping them take a more influential role in shaping these fields.

  • Upcoming: Github hosted standardized data processing pipelines to empower statisticians.