Research

Computational Molecular Design

• Computer-aided drug design
• AI for drug development

Metabolomics

• Biomarker detection
• Precision medicine

Quantum Computing

• Quantum algorithms for drug discovery and patent search
• Variational quantum eigensolver (VQE) for molecular properties
• Evaluation of quantum programming platforms

Medical Image Computing

• Video-based movement and motor-symptom quantification
• Parkinsonian and movement-disorder assessment
• Clinical image analysis and image-to-image translation
• Semi-supervised learning for clinical image interpretation

AI Agent Systems

• Scientific literature analysis and citation agents
• Regulatory and chemical risk assessment automation
• Retrieval-augmented generation (RAG) knowledge bases
• Large language models (LLM) for clinical assessment

A robust and interpretable graph neural network-based protocol for predicting p-glycoprotein substrates

P-glycoprotein (P-gp), a key member of the ATP-binding cassette (ABC) transporter family, plays a significant role in drug absorption and distribution by binding to diverse xenobiotics and actively transporting them out of cells. Given P-gp’s widespread expression, including its critical presence at the blood–brain barrier, identifying whether a compound functions as a P-gp substrate or inhibitor is essential in drug development to evaluate its ability to penetrate the central nervous system.

A Clinical Breathomics Dataset

This study entailed a comprehensive GC-MS analysis conducted on 121 patient samples to generate a clinical breathomics dataset. Breath molecules, indicative of diverse conditions such as psychological and pathological states and the microbiome, were of particular interest due to their non-invasive nature.

DeePFAS: Deep-Learning-Enabled Rapid Annotation of PFAS: Enhancing Nontargeted Screening through Spectral Encoding and Latent Space Analysis

Detecting PFAS is challenging due to their diverse chemical structures, lack of standards, complex sample matrices, and the need for sensitive equipment to measure trace levels. Background contamination and the sheer number of PFAS further hinder the development of a universal detection method.

Advantages of two quantum programming platforms in quantum computing and quantum chemistry

Quantum computing is at the forefront of technological advancement and has the potential to revolutionize various fields, including quantum chemistry. Choosing an appropriate quantum programming language becomes critical as quantum education and research increase.

FastEval Parkinsonism: an instant deep learning–assisted video-based online system for Parkinsonian motor symptom evaluation

The Motor Disorder Society’s Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) is designed to assess bradykinesia, the cardinal symptoms of Parkinson’s disease (PD). However, it cannot capture the all-day variability of bradykinesia outside the clinical environment.

Analyzing Generative AI and Machine Learning in Auto-Assessing Schizophrenia’s Negative Symptoms

Traditional assessments of schizophrenia’s negative symptoms rely on subjective and time- consuming psychiatric interviews. To provide more objective and efficient evaluations, this study examines the efficacy of an automated system utilizing generative AI (GenAI) and machine learning (ML) to assess negative symptoms of schizophrenia, including expression (EXP) and motivation and pleasure (MAP) domains.