I build intelligent decision-support systems that combine Mathematical Optimization, Artificial Intelligence, and Software Engineering to solve complex real-world problems in logistics, supply chain, resource planning, and business operations.
Graduating from IIT Bombay with an M.Sc. in Industrial Engineering & Operations Research, I enjoy transforming mathematical models into scalable software that delivers measurable business impact.
Mathematical Optimization: Pyomo · Gurobi · OR-Tools · PuLP · CBC · GLPK · HiGHS
Programming: Python · SQL · PostgreSQL · MongoDB · Git
Data Engineering: Pandas · NumPy · ETL Pipelines · Airflow
AI/ML: Scikit-learn · XGBoost · LLMs · Prompt Engineering
Backend: FastAPI · REST APIs · Database Design
Simulation: SimPy · Mesa · Streamlit
| Project | Description |
|---|---|
| vrptw-solver | VRPTW solver with exact MILP, Nearest Neighbor heuristic, and ALNS metaheuristic. Solomon benchmark instances. |
| stochastic-network-design | Two-stage stochastic program for facility location under demand uncertainty. Computes Value of Stochastic Solution (VSS). |
| LLM-OR-Solver | LLM-powered solver that translates natural-language business problems into mathematical optimization models. |
| Production-Scheduling-System | Enterprise-grade finite-capacity production scheduling using Pyomo + MILP (HiGHS/CBC). |
| Emergent-SCIP | Agent-based supply chain simulation (Mesa) with RL agents and MLflow experiment tracking. |
| McCormick-Relaxation | Analysis of McCormick relaxations vs. convex/concave envelopes for bilinear optimization. |
As an Operations Research Scientist, I have worked on production-scale optimization systems involving:
- Mixed Integer Linear Programming (MILP)
- Vehicle Routing Problems (VRP)
- Supply Chain Optimization
- Network Optimization
- Scheduling & Workforce Planning
- GPS Route Analytics
- Decision Support Systems
- Forecasting
- SQL & MongoDB ETL Pipelines
- Backend API Development
An AI-powered Career Operating System designed to help technical professionals learn, build, track progress, prepare for interviews, manage applications, and create recruiter-ready proof of work.
My public engineering knowledge base documenting daily learning, technical notes, experiments, research, case studies, and engineering practices.
Learn publicly. Build consistently.
Production-inspired optimization projects including:
- Vehicle Routing
- Inventory Optimization
- Production Planning
- Workforce Scheduling
- Hospital Resource Allocation
- Dynamic Pricing
- EV Charging Infrastructure Planning
- ✔ Build CareerOS MVP
- ✔ Publish optimization case studies
- ✔ Master Data Engineering fundamentals
- ✔ Build AI-powered decision support systems
- ✔ Contribute to open source
- ✔ Share technical articles and engineering notes
- ✔ Continue learning in public through Career Lab
I don't measure progress by certificates or completed courses.
I measure progress by:
- Systems built
- Problems solved
- Knowledge shared
- Consistency maintained
- Business impact created
Every repository represents a step toward becoming a better engineer.
I'm continuously exploring:
- Advanced Operations Research
- Large Scale Optimization
- AI Agents
- Decision Intelligence
- Data Engineering
- Distributed Systems
- Supply Chain Analytics
- Software Architecture
- Cloud Technologies
💼 LinkedIn: linkedin.com/in/sachinpatel-or
🌐 Portfolio: sachinpatel-or.github.io
📧 Email: sachinpatel.or@gmail.com
"Great software automates tasks. Great optimization transforms decisions."
⭐ Thanks for visiting my GitHub profile. If you're interested in optimization, AI, or building intelligent systems, feel free to connect.