Signal ML and Acoustic Analytics
Signal processing, acoustic signal processing, vibration diagnostics, spectral
analysis, envelope analysis, feature extraction, time-series modeling,
anomaly detection, and degradation modeling.
Uncertainty-Aware AI
Probabilistic deep learning, uncertainty quantification, confidence scoring,
calibration, robustness testing, out-of-distribution behavior, and safe
automation thresholds.
LLM Agents & Automation
LLM-powered agents, tool-use orchestration, Model Context Protocol (MCP),
retrieval over operational data, human-in-the-loop design, and automation of
analysis and reporting workflows — grounding AI outputs in real data with
deterministic logic for the engineering decisions.
Industrial Deployment
Predictive maintenance, condition-based decision support, operational
analytics, industrial IoT, model validation, stakeholder reporting, and
production-ready workflows.
Evaluation Rigor
Experiment design, baseline comparison, performance tracking, reproducible
pipelines, version-controlled experiments, and peer-reviewed scientific code.
Cloud and Engineering Tools
PythonSQLC/C++
MATLABScikit-learnTensorFlow
PyTorchNumPyPandas
AzureAWSDocker
GitPower BIApache Spark
COMSOLABAQUS
Collaboration
Cross-functional engineering, industrial partner coordination, technical
documentation, stakeholder communication, and mentoring students and junior
researchers.
