PhD in Instrumentation Engineering

Design of a LabVIEW-based multi-channel high-speed data acquisition platform with real-time signal conditioning, spectral analysis and automated report generation for industrial process monitoring and research laboratories.

Hardware-in-the-Loop platform for liquid-level, temperature and flow processes using LabVIEW Real-Time, CompactRIO and myRIO — enabling rapid controller prototyping, PID/MPC tuning and educational ABET-aligned experiments.

Development of soft sensors for difficult-to-measure process variables (composition, viscosity, quality) using LabVIEW data acquisition, feature extraction and Python/MATLAB machine-learning models deployed at the edge.

Implementation of digital filters, FFT, peak detection and custom control algorithms on NI FPGA targets using LabVIEW FPGA module for deterministic high-throughput instrumentation applications.

Complete automation of a multi-variable batch reactor (temperature, pressure, flow, level) using Siemens S7 or Allen-Bradley PLC, SCADA/HMI (WinCC / FactoryTalk), recipe management and historical data trending.

Implementation and experimental validation of adaptive, fuzzy and fractional-order PID algorithms on Siemens/Allen-Bradley platforms for processes with varying dynamics, compared against classical PID performance.

Development of constrained and unconstrained MPC algorithms suitable for PLC/PAC execution, with HIL validation on level, temperature or multivariable process plants and comparison with classical cascade control.

Software-defined automation architectures based on IEC 61499 function blocks for flexible manufacturing, dynamic reconfiguration and multi-vendor interoperability of PLC and soft-PLC systems.

Architecture and implementation of an OPC-UA enabled sensor network integrating 4-20 mA / HART / Modbus field devices, edge computing for anomaly detection and secure cloud dashboards for process visibility.

Development of intelligent pressure, temperature and level transmitters with digital communication (HART, Foundation Fieldbus), self-diagnostics, and LabVIEW-based automated calibration and uncertainty evaluation.

LabVIEW/Python-based vibration and acoustic emission monitoring system for rotating machinery with feature extraction, machine-learning fault classification and integration into plant SCADA for predictive maintenance alerts.

Design of reliable, low-power wireless sensor networks (ISA100, WirelessHART or custom LoRa/Wi-Fi) for temperature, pressure and level monitoring in hazardous areas with energy harvesting and mesh networking studies.

LabVIEW-based systems for non-invasive estimation of blood glucose (NIR spectroscopy), SpO2, heart rate and blood pressure using multi-wavelength optical sensors, advanced signal processing and regression / deep-learning models.

Design and validation of wearable multi-parameter sensor nodes with low-power wireless transmission, on-node feature extraction and LabVIEW/cloud dashboards for continuous health monitoring and activity recognition.

Model-free / data-driven iterative learning control algorithms for repetitive industrial processes, implemented and validated on LabVIEW or PLC platforms with convergence and robustness analysis.

Creation of high-fidelity process digital twins using MATLAB/Simulink or Modelica, integrated with PLC/SCADA via OPC-UA for virtual commissioning, operator training and what-if analysis before physical deployment.