Hi, my name is

Tzu-Tang Lin

AI × Bioinformatics R&D

Motivated to tap into the potential of AI and data science to reveal game-changing capabilities that accelerate the advancement of precision medicine and maximally benefit public health.

CV (pdf)

About Me

AI × Bioinformatics researcher & developer with extensive cross-disciplinary R&D experience spanning drug discovery, genomics, and biomedical AI. Passionate about transforming complex biological data into actionable insights for advancing precision medicine and improving public health outcomes.

Proven expertise in AI-driven RNA–small molecule drug modeling, antimicrobial peptide and functional protein design, next-generation sequencing (NGS) and genome-wide association studies (GWAS), as well as electronic health records (EHR)–based medical applications.

Experienced in independent research, publishing peer-reviewed articles, serving as a scientific reviewer, and mentoring students. Skilled in leading end-to-end research pipelines—from dataset curation to deep learning model development—and collaborating effectively with academia, hospitals, and industry partners.

Research Interests
  • Bioinformatics
  • Data Science
  • Machine Learning
  • AI Drug Discovery
  • Precision Medicine
  • Genetic Analysis

News

  • Jul 2025 — Seeking full-time opportunities in AI-driven bioinformatics, drug discovery, and precision medicine.
  • May 2024 — Started Ph.D. at the University of Florida College of Pharmacy, focusing on AI-driven drug discovery.
  • Dec 2023 — Developed AI antimicrobial peptide platform ‘AI Fleming’ at Academia Sinica (2018–2022), awarded the 20th National Innovation Award.
  • Sep 2023 — Joined Virginia Tech as Research Assistant in Computer Science, enrolled in the Genetics, Bioinformatics, and Computational Biology program.
  • Apr 2023 — Published research Intelligent De Novo Design of Novel Antimicrobial Peptides against Antibiotic-Resistant Bacteria Strains in the International Journal of Molecular Sciences.

Experience

Research Assistant - University of Florida — College of Pharmacy
May 2024 – Aug 2025
  • Built a cross‑domain multimodal contrastive framework for RNA–ligand affinity, integrating RiNALMo & SMI‑TED LLMs plus 3D structure into CLIP‑based foundation models; Test RMSE 1.68 vs 1.85 benchmark.
  • Applied biomolecule GNNs (GIGN), 3D-CNNs, and a custom representation module for fine-tuning and transfer learning.
  • Curated RNA–small molecule datasets (PDB, PDBbind, HARIBOSS); automated ligand-pocket detection, structure‑based clustering (RNA3DB, RMalign), and feature extraction (RDKit, Biopython, PyMOL).
  • Performed 10M-scale virtual screening (RNAmigos), docking score evaluation (AutoDock Vina), and decoy generation (DeepCoy).
  • Explored generative AI protein design with RFdiffusion, AlphaFold, and ProteinMPNN.
Research Assistant - Virginia Tech — Dept of Computer Science
Aug 2023 – Apr 2024
  • Conducted metagenomic analysis of wastewater treatment plants for ARGs/AMPs using Diamond BLAST, Minimap2, MEGAHIT, MetaSPAdes, Kraken2 and related tools.
  • Built PathoVF, a pathogen/virulence‑factor predictor using multi‑modal DNA encodings and protein LLMs (ProtBERT, ESM‑1b).
Data Scientist - Cathay Financial Holdings — Data Science Lab
Dec 2022 – May 2023
  • Improved ICU sepsis early‑warning and drug recommendations via Feature Tokenizer Transformer (FT‑Transformer) on EHR data; achieving accuracy 0.915.
  • Contributed to FinTech AI projects: signature recognition, synthetic banking data (Generative AI), and a federated-learning financial AI agent; deployed at scale on AWS EC2/SageMaker/S3.
  • Leveraged AWS cloud services for project workflows, including EC2 for scalable compute, SageMaker for model training and deployment, and S3 for secure data storage and retrieval.
  • Served as instructor for the Cathay General Hospital Data Science Workshop, delivering Python programming and data processing training for hospital staff.
  • Achieved Bronze (Top 9%) in Kaggle Novozymes Enzyme Stability Prediction Challenge (solo).
Bioinformatics Engineer / Research Assistant - Academia Sinica — Institute of Information Science
Jul 2018 – Dec 2022
  • Developed an AI-driven antimicrobial peptide platform; curated datasets and applied CNN, LSTM, Doc2Vec, and WGAN-gp for prediction and generation.
    • Designed two peptides with in vitro activity against cancer and antibiotic-resistant bacteria (MIC 2–45 μg/mL).
    • Packaged models into AI4AXP web platform (antibacterial, antifungal, anticancer, antivirus, anti-coronavirus, hemolysis).
    • Invited to Healthcare+ Expo Taiwan (2021, 2022); won the 20th National Innovation Award (2023) for ‘AI Fleming’.
  • Analyzed Taiwan Biobank genomes; developed DL models for disease phenotypes from SNPs for precision medicine.
  • Performed GWAS on aquatic species using PLINK, GATK, DeepVariant; transferred patented know-how for aquaculture SNP microarray design.
  • Supervised four summer interns at Academia Sinica, Institute of Information Science (2019-2022), guiding them to successfully complete their research projects.
  • Proposed PC6 physicochemical protein encoding; integrated into AI4AMP deep-learning predictor surpassing prior SOTA.

Education

May 2024 – Aug 2025
Ph.D. in Pharmaceutical Sciences — Withdrawn
University of Florida, College of Pharmacy
Focus: AI Drug Discovery (AIDD)
Sep 2015 – Jun 2019
B.S. in Agronomy (Specialization in Experimental Design and Biostatistics)
National Taiwan University
Awarded Undergraduate Research Fellowship, Ministry of Science and Technology (MOST), Taiwan.

Tools

AI4AXP
Academia Sinica — Institute of Information Science
AI4AXP, a user-friendly web platform for predicting peptide activities (antibacterial, antifungal, anticancer, antivirus, hemolysis).
AI Fleming Introduction Video
Academia Sinica — Institute of Information Science
AI Fleming: a generative-plus-predictive AMP platform using GANs and AI4AMP to design, identify, and validate new candidates.

Projects

Cross-Domain Multimodal Contrastive Learning for RNA–Ligand Binding Affinity
RNA Ligand CLIP LLM Python Prediction
Cross-Domain Multimodal Contrastive Learning for RNA–Ligand Binding Affinity
CLIP-style cross-modal foundation model integrating RNA sequences, LLM SMILES (RiNALMo/SMI-TED), and 3D features for RNA–small-molecule affinity; supports downstream fine-tuning.
GIGN for RNA–Ligand Binding Affinity
RNA Ligand GNN GIGN Python Benchmarking Prediction
GIGN for RNA–Ligand Binding Affinity
Fine-tuned/retrained Geometric Interaction Graph Neural Network (GIGN) for RNA–ligand interaction modeling with packaged training/inference.
Sepsis Early Prediction with FT Transformer (CGH)
Healthcare EHR Transformer Python Pipeline Prediction
Sepsis Early Prediction with FT Transformer (CGH)
EHR-based early sepsis prediction prototype using FT Transformer—data processing → featurization → training/evaluation; reproducible notebooks & scripts.
RLaffinity — 3D-CNN Contrastive Inference
RNA Ligand 3D-CNN Contrastive Python Benchmarking Prediction
RLaffinity — 3D-CNN Contrastive Inference
Reproducible inference & retraining workflow for a 3D-CNN contrastive model on nucleic acid–ligand binding; scripts for data prep and evaluation.
Hariboss Processing & Pocket Extraction
RNA Ligand Bash Pipeline Dataset
Hariboss Processing & Pocket Extraction
Hariboss cleaning, RNA/ligand splitting, and pocket extraction; SLURM batch for HPC and integration with RNA3DB.
PDBbind RNA–Ligand Processing Pipeline
RNA Ligand Bash Python Pipeline Dataset
PDBbind RNA–Ligand Processing Pipeline
Batch download/parse from PDBbind NL, RNA chain & ligand extraction, format conversions, and sequence export for training/pocket maps.
DeepCoy — Property-Matched Decoy Generation
Ligand Decoys Benchmarking Python Dataset
DeepCoy — Property-Matched Decoy Generation
Automated decoy generation for benchmarking/model evaluation; runnable examples, training/eval scripts, and pretrained pointers.
RNA & Molecular Analysis Toolkit
RNA Toolkit RDKit Python
RNA & Molecular Analysis Toolkit
Handy scripts (RDKit/Biopython/PyMOL) for RNA–ligand analysis—fingerprints, distance/contact maps, and inter-format conversions.
AI4AMP — Antimicrobial Peptide Predictor
Peptides AMP CNN LSTM Python Web Prediction
AI4AMP — Antimicrobial Peptide Predictor
PC6 encoding + CNN/LSTM for antimicrobial peptide prediction; CLI + quick demo + web workflow.
AI4AVP — Antiviral Peptide Predictor
Peptides AVP CNN Python Web Prediction
AI4AVP — Antiviral Peptide Predictor
PC6 + CNN with GAN-based data augmentation for antiviral peptide prediction; demo scripts and training code.
Cheminformatics & Molecular DB Playbook
Protein RDKit Python Tutorial
Cheminformatics & Molecular DB Playbook
From RDKit basics and MolDB exploration/screening to protein design (RFdiffusion + ProteinMPNN + AlphaFold) in one tutorial set.
CGH Data Science Workshop (Teaching)
Healthcare Python Tutorial Workshop
CGH Data Science Workshop (Teaching)
Hospital-oriented Python/Data Science materials (data processing, EDA, feature engineering, modeling & evaluation) with hands-on notebooks.

Get in Touch

Always happy to connect — feel free to reach out about potential collaborations