Aditya Srivastava

Explores the LLM output possibility space by sampling across parameter configurations (temperature, top_p, persona, domain) and semantically clustering results. FastAPI backend with Metal-accelerated TinyLlama inference, priority-queue tree search for diverse response paths, and a Next.js frontend for real-time exploration of generation variability.

Deep learning embedding model combining lexical similarity and contextual semantic representation via a BiLSTM encoder. Custom contrastive loss pulls semantically similar pairs together and pushes dissimilar ones apart. Reproducible training pipeline with real-time embedding space visualisation across epochs.

Multi-layered framework detecting, analyzing, and mitigating LLM misuse in hostile information operations. Real-time transformer-based classifiers (>90% accuracy) identify AI-generated content across text and multimedia. Forensic watermarking and fingerprinting trace outputs to source models and operators. Graph-based threat intelligence maps disinformation clusters and propagation chains. Privacy-preserving architecture via federated learning and differential techniques for national security defense.

Event-driven AI automation system on AWS EC2 using n8n orchestration, integrating Telegram, Gmail, and Google Gemini APIs with Firestore for persistent state. Intent classification, multi-branch routing, and automated email pipelines; full deployment lifecycle managed on Linux infrastructure.

Production-grade multi-tenant email platform for synthrun.site — decoupled static frontend on Vercel and Node.js REST backend on Render. Firebase Auth with server-side ID token verification, per-user Firestore mailbox isolation, SMTP relay via Nodemailer + Brevo with SPF/DKIM/DMARC, and infrastructure-as-code deployment via render.yaml.