OptiDec is the Optimization & Intelligent Decision Systems Lab led by Sharan Srinivas in Industrial & Systems Engineering at the University of Missouri. The group develops and applies operations research, analytics, simulation, and AI methods to complex operational systems.
Faculty Lead: Sharan Srinivas
OptiDec combines established operations-research foundations with AI, adaptive algorithms, simulation, autonomous decision systems, and emerging computational methods.
MILP · Stochastic & Robust Optimization · Multi-Objective Optimization · Decomposition & Relaxation · Matheuristics
Explore related projects →AlgorithmsLearning-Guided Search · Adaptive Metaheuristics · Surrogate-Assisted Optimization · Hybrid Exact-Heuristic Methods · Learning-Augmented Optimization
Explore related projects →AIMachine Learning · Explainable AI · Forecasting · GenAI & Text Analytics · Explainable Optimization · Interpretable Decision Models
Explore related projects →SimulationDiscrete-Event Simulation · Scenario Analysis · Computational Experimentation · Digital Decision-Support Platforms
Explore related projects →AutonomyMulti-Agent Coordination · Human-Robot Systems · Dynamic Assignment · Reinforcement Learning · Autonomous Decision-Making
Explore related projects →EmergingAI–OR Integration · Learning-Augmented Optimization · Quantum-Assisted Optimization · Hybrid Quantum-Classical Methods · QUBO Formulations
AI–OR integration and emerging computational approaches.Explore related projects →OptiDec is recruiting 1–2 PhD students for Fall 2027 for research at the intersection of operations research and artificial intelligence. My research group works on optimization, AI, simulation, and intelligent decision systems with applications across logistics, mobility, human-robot operations, and production and service systems.
Experience with optimization solvers and modeling tools such as Gurobi, CPLEX, Pyomo, or similar platforms is particularly useful. Experience with reinforcement learning, metaheuristics, simulation, or learning-augmented optimization may also be relevant depending on the research direction.
Prospective students should include:
Generic requests for admission or funding without information on research preparation may not receive a response.
Prior research experience is strongly preferred. Students applying directly from a bachelor's program are welcome, but should demonstrate substantial research preparation beyond regular coursework.
12 graduate researchers · 3 undergraduate researchers listed below
PhD Researcher
Research focuses on computer vision and multimodal AI for intelligent industrial systems, with emphasis on real-time perception, monitoring, and decision support from image, video, and multimodal data in manufacturing and warehouse environments.
PhD Researcher
Research focuses on optimization of collaborative human–autonomous mobile robot (AMR) operations in warehouse order picking under uncertainty. Current work develops robust and stochastic optimization models for order batching, assignment, sequencing, and routing, supported by scalable metaheuristics for large operational instances.
Collaborative human-robot order picking and AMR coordination
PhD Researcher
Research focuses on predictive and decision analytics for steel procurement under price uncertainty. Current work integrates time-series forecasting, simulation, and interactive decision support to connect market forecasts with purchasing and inventory decisions.
1st Place, 2026 IISE DAIS Mobile/Web App Competition, with Sharan Srinivas and James Noble.
MS completed · Spring 2026
Research story ↗PhD Researcher
Research focuses on optimization for emerging transportation and logistics systems, with emphasis on coordinated electric truck–drone operations. Current work examines routing, fleet, charging, and operational decisions using mathematical optimization and advanced computational algorithms.
NSF PFI-TT electric truck-drone route management research program
PhD Researcher
Research focuses on machine learning, explainable AI, and predictive analytics for risk assessment and decision support in complex systems. Current work emphasizes interpretable prediction and statistical modeling across healthcare and industrial applications.
MS completed · Spring 2025
PhD Researcher
Research focuses on stochastic optimization and adaptive decision-making for collaborative human–robot order picking in warehouse intralogistics. Current work examines autonomous mobile robots (AMRs), including fleet planning and task coordination under uncertainty and dynamic operating conditions.
Cobot iCommander · human–robot warehouse operations
NSF I-Corps research translation and customer discovery.
PhD Researcher
Research focuses on optimization of last-mile e-grocery delivery systems that integrate drones with ground transportation. Current work examines routing, scheduling, and coordination decisions under product-availability and operational constraints using mathematical optimization and adaptive metaheuristics.
PhD Researcher
Research focuses on optimization of additive manufacturing and integrated production–delivery systems, including order acceptance, batching, machine assignment, scheduling, and coordinated delivery decisions.
Additive manufacturing scheduling and integrated production-delivery planning
MS completed · Spring 2025
MS Researcher
MS Researcher
MS Researcher
MS Researcher
Research combines methodological development, real operational problems, sponsored projects, and scholarly or translational outputs. Researchers may contribute across several of these dimensions simultaneously.
MILP · Stochastic & Robust Optimization · Learning-Augmented Search · Reinforcement Learning · Quantum-Assisted Optimization
Human-Robot Operations · Multi-Agent Coordination · Truck-Drone Logistics · Resilient Logistics · Contested Logistics
Simulation · Scenario Analysis · Predictive Analytics · GenAI Analytics · Digital Decision-Support Platforms
Sponsored Research · Publications · Prototypes & Software · I-Corps / Research Translation · Operational Implementation
Mentored research connects analytical methods, research communication, and exposure to funded projects.
Research with international partners, including Germany, develops technical collaboration and professional skills.
Program story ↗Stakeholder discovery and problem definition help students explore how technical research can be put to use.
Program story ↗
First place — Pyam Oveys, Sharan Srinivas, and James Noble.
Exploring practical uses of research on human–robot warehouse operations.
Read the story ↗Pyam Oveys earned first place for steel-market decision-support research.
Read the story ↗Ray Wood earned first place for manufacturing workforce-optimization research.
Read the story ↗OptiDec brings together graduate and undergraduate researchers through project teams, research training, conferences, mentoring, and informal group activities.
U.S. Air Force
Postdoctoral Researcher · Wayne State University
Faculty of Management and Economics
Kunming University of Science and Technology · China
Visiting Assistant Professor
Edwardson School of Industrial Engineering
Purdue University
Data Scientist · Centene Corporation
Spring 2026
Undergraduate Research Scholar
IE Innovation Fellow
Undergraduate Researcher
50+ undergraduate students mentored across university and NSF-supported research experiences.
