ChemBioAI (CBA)
-
Exploring complex biomolecular systems through molecular modeling, simulations, and artificial intelligence.
ChemBioAI (CBA) is a research-oriented, interdisciplinary team that applies computational approaches—including molecular modeling, molecular dynamics simulations, and machine learning—to understand and predict the behavior of complex biomolecular systems. Our projects address research questions at the intersection of chemical engineering, biochemistry, chemistry, biology, and artificial intelligence. Example projects include modeling ligand-receptor interactions to understand and predict human sensory perception, such as odor, and developing machine learning models to predict enzyme activity and protein function.
We welcome undergraduate and graduate students from Chemical Engineering, Biomolecular Science, Computer Science, Chemistry, Biochemistry, Biology, and related disciplines. Through collaborative research projects, students will develop computational and analytical skills, gain experience critically evaluating scientific literature, and apply interdisciplinary approaches to real-world scientific problems. Graduate students may also serve as mentors, providing research guidance and supporting undergraduate team members.
Methods and Technologies
- Molecular Modeling and Simulation
- Molecular Dynamics (MD) Simulations
- Molecular Docking
- Machine Learning
- Computational Protein Modeling
- Bioinformatics and Sequence Analysis
- Python Programming and Scientific Computing
- Data Analysis and Visualization
- Scientific Literature Review and Critical Analysis
- Interdisciplinary Research and Collaboration
Areas of Interest
- Artificial Intelligence and Machine Learning
- Computational Biology and Bioinformatics
- Protein Engineering and Enzyme Function
- Molecular Modeling and Simulation
- Computational Biochemistry
- Biomolecular Interactions
- Human Sensory Perception
- Biotechnology and Biochemical Engineering
Potential Project-based Sub-teams
- Computational Sensory Biology: Investigating ligand-receptor interactions through molecular modeling and simulations to understand and predict human sensory perception
- AI for Protein Function: Developing machine learning models that integrate protein sequence, structural, and biochemical data to predict enzyme activity and protein function. Sub-team organization may evolve based on student interests, expertise, and ongo
Primary Instructors