Building production-grade systems at the intersection of finance, AI, and distributed architectures

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🚀 About Me

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⚡ OmniQuant

Unified Quantitative Research & Trading Simulation Platform

A hybrid Python / Rust / TypeScript system for strategy research, alpha generation, backtesting, and low-latency execution simulation.

• oms-core: Native Rust Order Management System with BTreeMap order book matching, ITCH 5.0 feed parser, and WAL event journal.
• execution-algos: Implementations of TWAP, VWAP, POV, and Almgren-Chriss Implementation Shortfall.
• alpha-layer: PyTorch (LSTMs & Transformers) and XGBoost predictions coupled with dynamic risk/portfolio optimizers.

Rust Python Next.js FastAPI

🎙️ pv-openai-agents-js

Multi-Agent Workflows & Voice Agent Framework

A lightweight, powerful TypeScript framework for orchestrating complex multi-agent collaborative workflows and streaming real-time voice agents.

• multi-agent: Event-driven communication channels allowing cooperative problem-solving between specialized agent nodes.
• voice-streaming: Native integration with WebRTC and WebSocket voice streaming pipelines for zero-latency conversations.
• extensible tools: Modular tool registration using structured JSON Schemas and self-documenting function calls.

TypeScript OpenAI WebRTC WebSockets

📡 FIX-SBE-Engine

High-Performance Low-Latency Protocol Engine

High-speed implementation of FIX (Financial Information eXchange) and SBE (Simple Binary Encoding) protocols for ultra-low-latency electronic trading.

• FIX session-layer: Safe state machine implementing logon, heartbeats, sequence number gap-fills, and automatic TCP/TLS reconnections.
• SBE serialization: Fast binary encoder/decoder optimized to operate directly on packet byte streams with zero allocation overhead.
• ocaml-dune: Engineered in OCaml, compiling to optimized native assembly with type safety and predictable GC profiles.

OCaml FIX Protocol SBE Low Latency

🔥 isp_ban

Supabase & Postgres Ban & Auth Management Engine

A specialized backend service built for network/ISP-level client ban management, user authorization, and row-level security policy control.

• RLS & Policies: Implements secure PostgreSQL Row Level Security (RLS) configurations and custom database triggers.
• Supabase Auth: Leverages Supabase Go/JS SDKs and database schema structures to handle fast client-side validations.
• Database Maintenance: Idempotent SQL migrations tracking system tables, indexes, and performance metrics.

PostgreSQL Supabase SQL Auth Management

💎 ZenithFi

Decentralized Finance Portal & Dashboard

A full-stack, visually rich decentralized finance (DeFi) portal for monitoring assets, liquidity pools, and real-time yield analytics.

• DeFi Integration: Front-end dashboard connecting to major Web3 protocols for fast asset tracking and analytics.
• Interactive UI: Engineered with Next.js App Router, Tailwind CSS, and custom charting components for premium visualization.
• TypeScript Safety: Safe execution models utilizing TypeScript typing structures for contract ABIs and token statistics.

TypeScript Next.js TailwindCSS Web3 DeFi

🚢 Maritime-Vessel-Tracking

Full-Stack Maritime Vessel Tracking System

A geospatial tracking and mapping application designed to monitor maritime vessel coordinates, route history, and real-time transit telemetry.

• Geospatial Mapping: Real-time mapping rendering client coordinate feeds, route vectors, and custom overlays.
• Full-Stack Architecture: Built with TypeScript, React, and server-side components processing concurrent telemetry updates.
• Data Serialization: Optimized ingest parsers mapping vessel AIS signals and structural state reports.

TypeScript React Geospatial API

🧠 assig-ai-tut

Career Recommendation & Matching Engine

A machine learning engine focused on mapping student and user attributes to optimal career paths using scoring models.

• Model Development: Python-based machine learning pipeline generating confidence scores and mapping models.
• Evaluation Pipelines: Automated validation metrics measuring classification accuracy and recommendation distribution.
• Predictive Analytics: Modular design engineered for ingestion of user attributes and fast offline inference iterations.

Python Scikit-Learn Machine Learning

👁️ TheDecentralEye

Collaborative Career Roadmap & Mentor Platform

A community-driven, decentralized platform helping students and aspiring developers kickstart their careers in modern tech spaces.

• roles/: Structured directories cataloging modern tech roles, required skills, and growth pathways.
• roadmap/: Community-validated, step-by-step guides and milestones to direct learning journeys.
• tools/: Curated lists of development environments, boilerplate templates, and educational resources.

Markdown Community Driven Open Source

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🎯 Domain Expertise & Skills Matrix

🤖 Artificial Intelligence & Machine Learning Engineer

🤖 AI Agents & Agentic Automation Architect

📊 Quantitative Analyst & Trading Systems

🔧 Backend Engineer & API Architect

📊 Data Scientist & Analytics Expert

🚀 DevOps & Infrastructure Engineer

💼 Software Development Engineer (SDE)

🗄️ Database Engineer & Architect

🎯 Product Management & Strategy

Python TypeScript JavaScript C++ HTML5 CSS3 SQL Bash

PyTorch TensorFlow scikit-learn Pandas NumPy OpenAI Jupyter

CrewAI LangChain n8n Make Zapier LiveKit Vapi ElevenLabs

FastAPI Node.js Express.js GraphQL gRPC Pytest

React Next.js Vite TailwindCSS

PostgreSQL Redis MySQL Supabase Prisma

Docker Kubernetes AWS GCP Linux Git

class PushkarKumarVats:
 def __init__(self):
 self.name = "Pushkar Kumar Vats"
 self.role = "Full-Stack Engineer | Quant Developer | AI Agent & Automation Architect"
 self.location = "India 🇮🇳"
 def current_work(self):
 return {
 "Quantitative Systems": [
 "High-Frequency Trading (HFT)",
 "Algorithmic Trading Engines",
 "Risk Analytics & Portfolio Optimization"
 ],
 "AI/ML Engineering": [
 "Large Language Models (LLMs)",
 "NLP Pipelines & Retrieval Systems",
 "Model Deployment & MLOps",
 "Computer Vision Systems"
 ],
 "AI Agents & Automation": [
 "Multi-Agent Orchestration (CrewAI, AutoGen)",
 "Stateful Workflows (LangGraph, Inngest)",
 "Real-Time Voice Agents (Vapi, LiveKit, ElevenLabs)",
 "Workflow & Order Automation (n8n, Make)"
 ],
 "Full-Stack Engineering": [
 "Real-Time WebSocket Architectures",
 "Microservices & Distributed Systems",
 "API Gateways & Service Mesh",
 "Cloud-Native Applications"
 ],
 "Infrastructure": [
 "Kubernetes Orchestration",
 "Docker Performance Optimization",
 "CI/CD Automation",
 "Scalable Cloud Infra (AWS/GCP)"
 ]
 }
 def learning_next(self):
 return [
 "Advanced C++ for Ultra-Low-Latency Systems",
 "Distributed Systems Internals & CAP Theorem",
 "Voice Streaming & WebRTC Protocols",
 "Rust for High-Performance Computing",
 "Real-Time Event Streaming (Kafka)",
 "Advanced Quant Research & Strategies"
 ]
 def tech_stack(self):
 return {
 "Languages": [
 "Python", "TypeScript", "JavaScript", "C++", "SQL", "Bash"
 ],
 "AI/ML": [
 "PyTorch", "TensorFlow", "Scikit-learn", "Pandas", "NumPy"
 ],
 "AI Agents & Automation": [
 "CrewAI", "LangGraph", "LangChain", "n8n", "Make", "LiveKit", "Vapi"
 ],
 "Backend": [
 "FastAPI", "Node.js", "Express", "GraphQL", "gRPC"
 ],
 "Frontend": [
 "React", "Next.js", "Vite", "TailwindCSS"
 ],
 "Databases": [
 "PostgreSQL", "Redis", "MySQL", "Supabase"
 ],
 "DevOps": [
 "Docker", "Kubernetes", "AWS", "GCP", "Linux"
 ],
 "Tools": [
 "Git", "Pytest", "Jupyter", "Prisma"
 ]
 }
me = PushkarKumarVats()

If you find my work valuable and want to support my open-source contributions and projects, consider buying me a coffee!

pushkarkumarvats@upi

Thanks for visiting! Let's build something amazing together! 🚀