Bioinformatics · AI/ML

I'm passionate about using generative AI models and ML to solve problems in toxicology and health:

• 🧬 Using generative AI for cross-domain translation, such as in vitro → in vivo extrapolation, treatment → control profiles, etc.
• 🧪 Modeling toxicological responses from high-dimensional data
• 🧱 Building foundations for scalable data & ML workflows in toxicology and risk assessment

• Generative models (GANs, VAEs, etc.) for biological data
• Toxicology, Genomics, Microbiome
• ML for biomedical and clinical data
• Statistical models

Languages & ML

• Python · R · SQL · UX
• PyTorch / TensorFlow · scikit-learn
• Bioinformatics: Metagenomics, Metatranscriptomics, BLAST, QIIME2, Network Analysis

• 🧪 AIVIVE
  GAN-based IVIVE framework published in Toxicological Sciences. 👉 Read the paper: https://doi.org/10.1093/toxsci/kfaf100

• 🦠 SIR Model Simulation – COVID-19
  SIR simulation with visualization and herd-immunity plots.

• 🧫 Network Modeling for Bacterial Communities
  SPIEC-EASI network construction + stats for 16S sequencing data.

• 🤖 ML for Beginners (Examples)
  ML starter codes: regression, BERTopic, medical classification, Naive Bayes.

• LinkedIn: www.linkedin.com/in/mansi-chandra-6992001bb
• Email: mchandra@ualr.edu