Embedded Files
Operations Research
Architecting large-scale MILP-based supply chain optimizers, real-time predictive models, and AI-driven decision systems that drive hundreds of millions in profit.
About Me
Passionate about solving the world's most challenging optimization problems
As an Operations Research practitioner, I specialize in mathematical programming, stochastic optimization, and AI-driven decision systems. I've architected large-scale MILP-based supply chain optimizers, real-time predictive models, and heuristic decision frameworks that have driven hundreds of millions in profit across major corporations.
My expertise spans demand-supply matching, vehicle routing, ETA forecasting, and cloud-scale AI pipelines. I hold a M.Sc. in Industrial Applied Mathematics from Oakland University and have extensive experience with companies like Gurobi Optimization, Infosys Consulting, Toyota North America, Ford Motor Company, Marposs, and Auto-Owners Insurance.
Adam DeJans Jr: Decision architect & strategist
Technical lead and certified data professional with over a decade of successful experience leading teams to develop and deploy data-intensive applications while overcoming complex architectural and scalability issues. Currently a data science supervisor, directing the technical implementation and strategy of supply chain optimization for Toyota North America.
Software development
A data scientist's true value shines when their models are effectively integrated into production. Writing scalable code is pivotal in crafting robust data science solutions. Drawing from my software engineering background, I ensure that every model I develop is not just a theoretical construct but a practical tool enhancing customer experiences
Data science
I specialize in operations research, focusing on optimization, algorithms, machine learning, and broad-spectrum data science. My accomplishments include devising real-time routing solutions, developing streaming deep-learning applications that analyze over 300 million data points daily, and optimizing resource allocation strategies that generated an additional $400 billion within a year.
Areas of Expertise
Specialized knowledge across multiple optimization domains
With an advanced specialization in optimization and a solid software background, I excel in crafting data-driven solutions using languages like Python and Java. My expertise encompasses statistical modeling, big data management, and applying operations research across diverse industries, from logistics to automotive. Coupling my technical proficiency with strong leadership abilities, I consistently translate complex data insights into actionable strategies for organizational success.
Supply Chain Optimization
Designed Toyota's North American supply allocation engine using Mixed-Integer Linear Programming in Gurobi, optimizing profit, greenhouse gas reduction, and volume.
AI-Driven Decision Systems
Developed automated vehicle ordering systems and real-time AI-driven logistics using deep learning (TensorFlow) on Azure for 300M+ data points daily.
Vehicle Routing & Fleet Optimization
Invented and patented dynamic programming-based route optimization algorithms, developed VRP algorithms for ride-hail, shuttle, and delivery services.
Stochastic Programming & Forecasting
Built tree-based regression models for regional demand forecasting, integrating uncertainty and real-time data for optimal decision-making.
Cloud-Scale AI Pipelines
Architected end-to-end cloud-based AI pipelines using Kafka, Spark (Databricks), Docker, Kubernetes, and Azure Event Hubs for billions of records.
Customer Segmentation & Heuristics
Mathematical background and expertise in operations research and optimization.
Featured Projects
Supply Allocation Engine
Designed and implemented a supply allocation engine using MILP in Gurobi. Generated two-year strategic production plans, increasing production by 40,000 vehicles and yielding $390M in additional profit.
MILP Gurobi Supply Chain
Automated Vehicle Ordering System
Developed ordering recommendation engine using tree-based regression models for demand forecasting. Linearized forecasts into MILP model, increasing profit by $64M.
Machine Learning MILP Forecasting
Real-time Package Delivery ETA
Designed real-time AI-driven logistics system using deep learning on Azure, processing 300M+ data points daily to predict ETA for package deliveries with wide & deep architecture.
Deep Learning Azure Real-time AI
Dynamic Route Optimization
(Patented)
Invented and patented dynamic programming-based route optimization algorithm (US20210133643A1). Deployed as Android application for multimodal route planning in public transit.
Dynamic Programming Patent Mobile App
Vehicle Fleet Simulation
Led development of discrete event simulation tool for fleet sizing, achieving 27% fleet size reduction while ensuring service reliability. Built with Python (SimPy) and React UI.
Simulation Python Fleet Optimization
Accessories Recommendation System
Built customer segmentation model using demographic, financial, and geographic data. Optimized $700M in inventory with explainable heuristic model, increasing profits by $42M.
Customer Segmentation Heuristics Inventory
Get In Touch
Let's discuss how operations research and AI can solve your complex business challenges
adam.dejans@gmail.com
Reach out with any questions about how I can assist you, or simply drop an email to touch base.
+1 (xxx) xxx-xxxx
Feel free to text or call with any inquiries about my services.
Detroit, MI
I'm open to face-to-face meetings in the Metro Detroit region.
Google Sites
Report abuse