About
I am a PhD student in Computer Science at the University of Central Florida, working in the Computational Biology Lab at the intersection of computational research and software engineering. My academic interests span single-cell multi-omics, quantitative methods, high-performance computing, and machine learning applied to scientific problems.
Alongside research, I build reliable, efficient software — from systems-level C++ and Rust libraries to full-stack web applications, AI privacy/security tools, and quantitative finance simulators. I am drawn to problems that demand both mathematical rigor and clean engineering.
Interests
- Quantitative finance & stochastic modeling
- Computational biology & single-cell multi-omics
- Deep learning, dynamical systems & optimization
- AI privacy, synthetic data auditing & LLM/RAG security
- High-performance systems (C++, Rust, parallel computing)
Selected Highlights (2026)
ChronoGRN & Multi-Omics Research
Delay-aware, enhancer-gated Neural ODE gene regulatory network inference from paired scRNA-seq + scATAC-seq trajectories and cross-cohort single-cell foundation models.
Quantitative Finance, AI Security & Clinical Systems
Orderbook & Black–Scholes simulators, Kalshi-style prediction markets (Tejas Trading), Rust-to-Quant curriculum, AI privacy firewalls (SyntheticShield, RAGGuard), and clinical AI platforms (HelixMatch, AURA Clinical).
Education
Links
Contact
network.with.tejas@gmail.com · Orlando, FL