Pioneering the Next Era of Molecular Design.
Our mission is to redefine the boundaries of modern drug discovery. By synergizing the rigorous accuracy of Quantum Chemistry with the scalable efficiency of Machine Learning, we develop next-generation computational platforms, including AVENGERS and SAGE. Moving beyond conventional screening, these advanced tools proactively design and validate novel therapeutics, unlocking chemical spaces that were previously inaccessible.
Bridging Quantum Precision and AI Innovation.
Rapidly identifies potential hit molecules from ultra-large chemical libraries or via advanced de novo generation.
Refines hit molecules through precise quantitative structure-activity relationship (QSAR) analysis to maximize target efficacy.
Accurately forecasts ADME/T properties and proposes optimized derivatives with enhanced safety and drug-likeness.
Screens extensive mutant libraries to discover variants with superior binding affinity, selectivity, and enzymatic activity.
Enhances protein function and thermal stability by leveraging machine learning and 3D structural molecular modeling.
Predicts critical biophysical properties, such as immunogenicity, aggregation propensity, and cleavage sites, to ensure viable biotherapeutic development.
Thesis Advisors
Prof. Kyoung Tai NoThesis
“Development of Accurate Virtual Engines and Effective Ranking Systems (AVENGERS) for Drug Design and Protein Engineering”Cumulative GPA: 4.24 / 4.30
Thesis Advisor
Prof. Kyoung Tai NoThesis
“Application of Fragment Molecular Orbital to Analysis of Protein-Protein Interactions”Cumulative GPA: 4.24 / 4.30
Valedictorian
Cumulative GPA: 4.14 / 4.30
Salutatorian