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saltypal/README.md

Satya Srinivas Paladugu

AI & Data Science undergraduate at Amrita Vishwa Vidyapeetham, Bengaluru.

I work on AI, high-performance computing, networking, and communications. I like understanding how systems work, building parts of them myself, and seeing where they break.

Website · Portfolio · LinkedIn · Email

Currently building

  • SuperPie Runtime — an inference module to simplify running AI models locally, in the cloud, or elsewhere.
  • Sahakaram MCP — shared rooms, messages, and tasks for supervised collaboration between coding agents.
  • RDMA over Ethernet — exploring communication between two laptops.
  • TrueFace3D — 2D-to-3D facial reconstruction.
  • Parallel stochastic gradient descent — exploring parallel training and optimization.

Interests

  • Reinforcement learning and multi-agent systems
  • GPU programming and high-performance computing
  • Computer networks and distributed systems
  • Wireless and semantic communications

Technologies I work with

Area Technologies
Languages Python, C, C++, Java, JavaScript
AI & data PyTorch, scikit-learn, NumPy, Pandas
Parallel computing CUDA, OpenMP, MPI
Networks & communications ns-3, GNU Radio, Wireshark, OpenWrt
Tools Linux, Git, GitHub, MCP

A few projects

Contact

Email: satyaspaladuguplus@gmail.com
Discord: sp.9696

Pinned Loading

  1. Sahakaram Sahakaram Public

    Python MCP plugin for supervised collaboration between coding agents. Shared rooms, messages, tasks and usage observations.

    Python 1

  2. Hierarchical-multi-agent-RL-for-Urban-Traffic Hierarchical-multi-agent-RL-for-Urban-Traffic Public

    A hierarchical multi-agent reinforcement learning (HMARL) framework for large-scale urban traffic orchestration using SUMO + TraCI over real Bangalore road networks.

    Jupyter Notebook