ADITYA ANIL

Software Developer & AI/ML Engineer

B.Tech Computer Science (AI) @ Amrita Vishwa Vidyapeetham

Software Developer and AI/ML Engineer specialising in local agentic AI architectures, deep learning pipelines, and bio-computational systems engineering. Core interests centers on developing Agentic AI tools, terminal-based local LLM execution loops, computer-aided drug design (CADD) pipelines, quantum machine learning (QML), and open-source developer tooling. Global Top 0.5% open-source contributor with over 6,000 contributions and primary author of peer-reviewed deep learning research in medical image segmentation.

• I write software and build systems around local LLMs, agentic workflows, and computational biology tooling.
• Most of my recent work sits at the intersection of terminal-based agents, deep learning pipelines, and drug discovery infrastructure. I’m also a fairly active open-source contributor (6k+ contributions, currently in the global top 0.5%).
• I have one peer-reviewed paper on medical image segmentation using an EfficientNet-B0 U-Net (IEEE ICCCNT 2025).

• Top 0.5% Global Open Source Contributor: 6,000+ contributions across Python, C++, Go, and JS ecosystems.
• AI Drug Discovery R&D Intern @ PSPM Technologies: I am working on automated CADD and molecular dynamics pipelines orchestrated via Model Context Protocol (MCP) and local LLMs. Main stack: AlphaFold2, DiffDock, OpenMM, AMBER.
• Software Engineer & AI Model Evaluator @ PlatinaData.AI: Building evaluation repositories, containerized terminal environments, and test suites used to audit autonomous coding agents.
• Published IEEE Researcher: Authored an medical image segmentation research using EfficientNet-B0 U-Net architectures (IEEE ICCCNT 2025).
• ACM SIGAI Member: Active in global AI research frameworks, model evaluation standards, and open-source infrastructure initiatives.

• Agentic Architectures: Terminal-based coding assistants (AgentTool), local LLM tool-calling execution loops (Ollama / LM Studio), and MCP server integration.
• In-Silico Bio-AI Systems: End-to-end computational drug discovery pipelines: Structure Prediction (AlphaFold2) -> Docking (DiffDock/GNINA) -> MD Simulations (OpenMM/AMBER) -> ADMET Profiling.
• SWE Benchmarking: Designing multi-file repos, auditing LLM terminal execution trajectories, and building reproducible evaluation environments.
• Quantum Machine Learning: Researching hybrid quantum-classical physics-informed neural networks (HQ-PINNs) and quantum circuit execution.

• AI, LLMs & Agents
  • PyTorch, LangChain, Hugging Face, Ollama, Llama 3.1, Model Context Protocol (MCP), TensorFlow, OpenCV, Scikit-learn.
• Core Languages & Frameworks:
  • Python, C/C++, Go, TypeScript, JavaScript, Lua, Solidity, FastAPI, Next.js, React, Node.js.
• Developer Tools & Infrastructure:
  • Arch Linux, Neovim, Docker, Git, GitHub Actions CI/CD, Pytest, Bash/Shell Scripting, LaTeX.
• Database:
  • MySQL, MongoDB, PostgreSQL
• Unix:
  • Arch Linux, Debian and Ubuntu
• Research:
  • R, Matlab, LaTEX, Markdown
• CLI:
  • Bash / Shell

• LLM Evaluation & AI Safety Domain Certifications : PlatinaIQ
• Quantum Computing Certification (Merit) : C-DAC & IIT Roorkee
• AWS Cloud Practitioner Essentials : Amazon Web Services (AWS)
• Web3 & Blockchain Developer Certificate : EtherAuthority

I am actively seeking collaboration on agentic systems, scientific AI tooling, open-source infrastructure, and deep-tech research.

• Email: aditya.anil.productions@gmail.com
• LinkedIn: aditya-an1l
• X / Twitter: @aditya_an1l

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