Dr Burak Suslu.
Senior R&D and algorithm engineer. Cranfield PhD on multi-objective sensor optimisation (MOSOF, NDCI); three first-author Sensors (MDPI) papers; founder of AcoustR; five years of prior industrial-automation founder experience. Based in London, UK; available immediately.
Industry-track CV (this page) · academic profile for university and post-doc tracks.
- Founded and ran a 5-yr industrial-automation business serving state-run oil & gas — high-voltage retrofits delivering 20% energy-efficiency uplift on the cracking-tower programme; delivered on time, under budget, follow-on maintenance contract.
- Built and shipped AcoustR — acoustic diagnostics for engines and machines; live with early customers. First product application of MOSOF / NDCI.
- Published 3 first-author papers in Sensors (MDPI) (2023, 2025, 2026) defining MOSOF and the Normalised Diagnostic Contribution Index (NDCI).
- Defended PhD at the Cranfield IVHM Centre (Nov 2025); reduced an 18-sensor B737-800 ECS to a 12-sensor Pareto-optimal suite at ~0.69 normalised diagnostic performance.
- Shipped open-source reference implementations at github.com/ssl8 — MOSOF (NSGA-II driver), NDCI calculator, Pareto data pipeline; with an annotated walkthrough essay.
- Active peer reviewer for Sensors (MDPI) and adjacent venues in sensor optimisation, IVHM, and diagnostics.
[email protected]
Founder · AcoustR ↗
Lead venture — a product application of the MOSOF / NDCI sensor-optimisation methods, building diagnostic systems that work from the sound an asset already makes. Currently live with early customers.
Founder · Sensorry ↗ (prototype)
An applied tool packaging the MOSOF / NDCI workflow for engineering teams designing or auditing sensor networks. Currently in prototype.
Independent technical advisor
Consulting engagements with engineering and R&D teams on sensor optimisation audits, custom multi-objective optimisation frameworks, and ongoing technical advisory.
Founder & Lead Research Engineer · SSL Elektrik-Elektronik
Founded and ran a five-year applied R&D and industrial-automation business serving state-run oil & gas — drove 20% energy-efficiency uplift on the cracking-tower retrofit programme through algorithm-driven control of high-voltage industrial systems in hazardous environments. Integrated IoT sensors and ML-driven decision logic into legacy machinery; managed the full R&D lifecycle from functional specification to commissioned on-site hardware.
- Managed full R&D lifecycle from conceptual functional specifications to fully commissioned, on-site hardware solutions
- Phased-retrofit cracking-tower control systems for a state-run petroleum facility (delivered on time, under budget, follow-on maintenance contract)
- Cross-functional delivery with utilities, operators, and EPC contractors — the operational reality that now grounds the optimisation research
MOSOF with NDCI: A Cross-Subsystem Evaluation of an Aircraft for an Airline Case Scenario ↗
Cross-subsystem evaluation applying MOSOF + NDCI across Engine, Fuel, EPS, and ECS subsystems for an airline-case aircraft. Demonstrates compact Pareto-efficient sensor suites with knee solutions of approximately 12 sensors at ~0.69 normalised diagnostic performance.
NDCI Integration to Multi-Objective Sensor Optimisation Framework — An ECS Case ↗
Introduces the Normalised Diagnostic Contribution Index and integrates it into MOSOF. Validated on the Environmental Control System of a reference aircraft.
Understanding the Role of Sensor Optimisation in Complex Systems ↗
Foundation paper for the doctoral programme. Frames sensor selection as a multi-objective rather than single-axis problem.
Full publications archive →
PhD · Transport Systems (Sensor Optimisation)
Thesis: Sensor Optimisation for Aircraft Health Management Systems (defended November 2025). Produced the Multi-Objective Sensor Optimisation Framework (MOSOF) and the Normalised Diagnostic Contribution Index (NDCI), evaluated across Engine, Fuel, EPS, and Environmental Control subsystems with repeated nested cross-validation.
- Supervisor: Prof. Ian K. Jennions · Associate Supervisor: Dr Fakhre Ali
- Three first-author peer-reviewed publications in Sensors (MDPI), 2023, 2025, and 2026
- Methodological focus: multi-objective genetic algorithms (MOGA), information-theoretic diagnostic scoring, Pareto-front trade studies, Fault Detection and Isolation (FDI)
MSc · Advanced Electrical and Electronic Engineering (Merit)
Final project: high-efficiency preamplifier design for radiation sensors in high-temperature well-logging applications.
BEng · Electrical & Electronics Engineering (2:1)
Final project: design and implementation of a compact radar prototype with a 2D object-tracking system.
Peer reviewer
Active reviewer for peer-reviewed venues in the sensor-optimisation and diagnostics space, including Sensors (MDPI).
References available on request. Doctoral supervisors at Cranfield University's IVHM Centre, plus industrial referees from prior automation work, can be supplied for academic and industry roles respectively.
Open to the right role.
For academic positions, industrial research roles, or technical leadership opportunities at companies working on diagnostic and decision systems — get in touch with a short note about the role and timing.
[email protected] →