Portfolio

Applied research prototypes and engineering work. Items are experimental or under active development unless a publication or demo link is listed.

Dempster–Shafer Theory for Industrial Diagnostics

Role: Research prototype / published research support

Dempster–Shafer Theory · Belief Functions · Uncertainty Modeling · Industrial Diagnostics · Continuous Casting (CCM)

Context
Industrial diagnostics under uncertainty, incomplete observations, and conflicting evidence — focused on continuous casting machines in metallurgy.
Problem
Classical probabilistic models may be brittle when evidence is sparse, imprecise, or conflicting across temperature, vibration, and acoustic sensors.
Approach
Use Dempster–Shafer belief functions to represent uncertainty and combine evidence from diagnostic sources; adaptive combination rules (Dempster / Yager) depending on conflict coefficient.
Evidence
Outcome
Experimental validation on CCM diagnostic scenarios reported in the published work: improved diagnostic accuracy and reduced false confidence under high-conflict evidence (see project page for details).
Status
Published research support with working diagnostic prototype demo.

Industrial MRO Optimization with Hierarchical MARL

Role: Simulation-based research prototype

Reinforcement Learning · MARL · HRL · CMDP · HITL · Industrial Maintenance · Simulation

Context
Industrial maintenance planning under limited maintenance resources and equipment degradation.
Problem
Reactive or fixed-schedule maintenance policies may lead to avoidable downtime or inefficient resource use under stochastic failures and partial observability.
Approach
Simulation-based decision-support prototype using hierarchical RL / MARL, HITL operator feedback, constrained decision-making (CMDP / action masking), and latency-aware intervention logic at the strategic level.
Evidence
Outcome
Simulation experiments compare learned maintenance policies against baseline strategies such as reactive or schedule-based maintenance. Reported trends include a shift toward more preventive planning under resource limits (see working paper draft; no production deployment).
Status
Active research prototype — under development.

RL Simulation Environments

Role: Experimental environment

Python · Gymnasium · PyGame · Simulation · RL Environments · Experiment Logging

Context
Reproducible testbeds for hierarchical and multi-agent RL beyond toy benchmarks.
Problem
Maintenance and resource-allocation experiments need configurable simulation environments with logging hooks.
Approach
Custom Gymnasium-style environments modeling equipment fleet dynamics, maintenance actions, and resource constraints.
Evidence
  • Repository: not publicly linked yet
Status
Experimental environment — iterative development.

Data / ML Engineering Sandbox

Role: Engineering sandbox (under development)

Python · SQL · FastAPI · Docker · Experiment Tracking

Context
Small research-oriented prototypes: data-processing scripts, API experiments, and reproducible experiment pipelines.
Problem
Bridging research experiments with lightweight data workflows and serving stubs.
Approach
Python / SQL-based data and ML prototypes; containerized API experiments; tracked experiment runs.
Evidence
  • Repository: not publicly linked yet
Status
Under development — no public artifact yet.