Instrumentation & Control engineer with hands-on experience in industrial process systems, P&ID development, HAZOP analysis, Safety Instrumented Systems, and IoT-based field monitoring — bridging physical measurement with control system design.
Applied ML engineer combining deep learning, signal processing, and domain physics knowledge — from 1D-ResNet crystal classification (88.4% accuracy on 127K+ spectra) to soft sensor development and ensemble regression for industrial process prediction.
Energy systems engineer with field experience in RDF plant energy auditing, solar PV aerator design (3.2 kWp, 98.3% autonomy), and computational modeling for renewable energy performance optimization and efficiency analysis.
01 — ABOUT
I'm an Engineering Physics graduate from Universitas Gadjah Mada with a strong foundation in physical measurement, control systems, and computational modeling. My work sits at the intersection of instrumentation engineering, applied machine learning, and energy systems — domains that naturally overlap in modern industrial environments.
Over the course of my studies, I've worked on end-to-end engineering projects ranging from industrial instrumentation design (P&ID, HAZOP, SIS per IEC 61511) to deep learning pipelines processing 127,000+ data points, to solar PV field commissioning with live IoT monitoring. I bring both the theoretical rigor of physics and the practical mindset of an engineer.
I'm particularly drawn to roles where data and physical systems converge — whether that's a smart sensor network, a predictive maintenance model, or an energy optimization framework. I work best in cross-functional teams where technical depth matters.
02 — EDUCATION
03 — SKILLS
Instrumentation & Field
Process Safety & Control
Machine Learning & Data Science
Energy & Sustainability
IoT & Embedded Systems
04 — EXPERIENCE
05 — PROJECTS
End-to-end deep learning pipeline classifying 7 crystal systems from XRD diffraction spectra. Custom 1D ResNet-18 architecture trained on 127,430 simulated spectra from 850+ CIF polymer files (Crystallography Open Database). Reduced manual analysis from hours to seconds.
88.4% validation accuracy · 4.2s inference · 0.32 val loss Thesis documentation available on requestEnsemble AdaBoost-Decision Tree soft sensor replacing a 2-hour offline GC cycle with continuous real-time CO₂ inferential measurement. Trained on 18 months of simulated DCS data (240,000+ samples) from a 50 MMSCFD gas sweetening unit. 23 engineered features including thermodynamic calculations, time-lagged variables, and rolling statistics.
RMSE: 0.71 mol% (↓18.4% vs baseline) · R² > 0.94 Academic project — documentation availableComplete instrumentation engineering package for a hypothetical refinery distillation unit revamp: 15 P&ID sheets, instrument index with 180+ field devices, 45 ILDs, 12-node HAZOP worksheets, and control valve datasheets per ISA-5.1 and ISO 10628.
180+ instruments · SIL-2 SIS · 22 control valve calculations Full documentation available on requestField-deployed 3.2 kWp solar PV system powering a 1.5 HP DC aerator for aquaculture. Integrated IoT monitoring (ESP32, MQTT, InfluxDB, Grafana) tracking 7 parameters at 1-min intervals. Optimized via PVsyst to achieve 24/7 grid-independent operation.
98.3% autonomy · Rp 18–24M/yr savings · 10,000+ data pts/week Field report & dashboard screenshots availableLaboratory-scale closed-loop instrumentation system simulating utility process operations (pressure, temperature, flow) with continuous real-time monitoring. ESP32-based DAQ, MQTT communication, InfluxDB storage, and Grafana dashboard with 10+ real-time visualizations including trend analysis and predictive maintenance indicators.
500+ sensor streams @ 1 Hz · ±2% full-scale accuracy Hardware documentation available on requestComprehensive energy performance audit across 7-unit RDF plant (2.5 tons/day). 45-day operational dataset analysis, Sankey energy flow mapping, gap analysis vs theoretical performance, and a 5-point improvement roadmap with full financial projection and ROI estimation for plant management.
$8,500–12,000/yr savings · 15–22% energy intensity reduction Confidential — summary available on request06 — CERTIFICATIONS
07 — CONTACT
Open to full-time opportunities, research collaborations, and project-based work in Instrumentation & Control, Applied Machine Learning, and Energy Systems. Based in Jakarta — open to relocation and remote work globally.
suryonaufal.official@gmail.com +62 858-2466-5742