distributed-optimization

Scalable Algorithms for Multi Period Optimal Power Flow (MPOPF) in Active Distribution Systems (with Batteries and Solar PVs) complete with OpenDSS Validation

Parallel optimizer based on the Global Function Search

Consensus-Based Bundle Algorithm (CBBA) & Distributed Multi-Agent Weapon-Target Assignment Auction Kernel for combat drone fleets in contested EW.

A benchmarking framework for decentralized optimization

A Production-Grade Federated Learning Engine built from scratch in PyTorch. Orchestrates decentralized FedAvg optimization across non-IID data topologies using Kubernetes, gRPC, and robust MLOps infrastructure.

A custom package for distributed design optimization written in Python.

Alternating Direction Method of Multipliers (ADMM) consensus coordinator solving decentralized multi-agent rendezvous and velocity matching.

Alternating Direction Method of Multipliers (ADMM) consensus coordinator solving decentralized multi-agent rendezvous and velocity matching.

Optimal mixing matrices for graphs: fastest-mixing Markov chains, gossip and consensus weights

Persian-language workshop materials on numerical optimal control, model predictive control, and distributed optimization — MATLAB/CasADi and Python/CVXPY codes with lecture videos. University of Tehran.

Persian-language Distributed Optimization Workshop with theory and hands-on CVXPY/CasADi implementations, developed at the Smart Network Systems Laboratory, University of Tehran.

Official code and reproducibility package for D-SCEOS: swarm-inspired peer-to-peer control for resource-aware flexibility sharing in cyber-physical energy systems (CPES), distributed energy resources and virtual power plants; CLF/HOCBF safe control. Energy Conversion and Management: X 31 (2026) 102212. DOI: 10.1016/j.ecmx.2026.102212

Unified DOIN participant node: optimizer, evaluator and network roles in one configurable runtime with shared-population optimization on a proof-of-optimization chain

CORDIS: A scalable framework for coordinated resource allocation in distributed cell-free ISAC systems, with reproducible simulations and supporting materials.

[TRO 2026] riMESA is a robust and incremental collaborative SLAM algorithm.

Event-triggered DIGing and Push-DIGing algorithms for communication-efficient distributed optimization.

Advanced Mathematical Optimization & Deep Learning Optimizers from scratch. Covers KKT duality, L-BFGS, proximal methods (ADMM, FISTA), stochastic algorithms (SVRG, Lion), and cutting-edge deep learning optimizers like K-FAC, Shampoo, Sophia, SAM, and Muon. Bridging strict convex calculus with large-scale Transformer training.

Distributed Multidisciplinary Design Optimization

Bio‑inspired algorithms for compression, encryption, and distributed optimization.

A stochastic AI agent and critic system developed for advanced fault detection and root cause analysis in network telemetry.