Available Oct–Nov 2026 · International mobility
Williams Maikol Bouzid — complex systems engineer and research intern.
Engineering complex systems from signals to intelligent machines.
I am Williams Maikol Bouzid, a final-year MSc engineering student and research intern working across biomechanics, OpenSim and SCONE modelling, signal processing, computer vision, estimation, control and embedded systems, with a focused academic track in radar and sonar.
Radar & sonar
Signal processing
Computer vision
Control
Embedded systems
Biomechanics · OpenSim · SCONE
FIG. 01 — SYSTEM LOOP
y = h(x) + v
ẋ = f(x,u)
u = −Kx̂
France · Italy · Open internationally
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Profile / 01
A research mindset grounded in engineering practice.
I study how complex systems can be observed, modelled and controlled — and how mathematical methods become reliable engineering tools.
My path combines information engineering, applied mathematics and experimentation. I enjoy moving between theory and implementation: from robust estimation and detection to embedded sensing, musculoskeletal simulation and validation. My current research includes biomechanics, OpenSim, SCONE and human stability in marine environments, alongside radar and sonar signal processing, statistical decision theory and optimal filtering.
Radar & sonar focus / 02
Academic focus · depth in progressRadar and sonar as problems of estimation, detection and decision.
My interest is grounded in verified coursework and independent study. I am building from a strong analytical base toward applied R&D in sensing, statistical signal processing and multisensor systems.
Radar signal processing
17.3/20
A solid foundation, recognised through sustained work.
Master’s-level radar coursework taught by Jean-Marc Lopez, Doctor of Engineering at the French Directorate General of Armament. Ranked 3rd out of 25 students and supported by an academic recommendation.
Sonar systems
18/20
Acoustic sensing connected to statistical detection.
Coursework in sonar systems, complemented by modules in detection theory and stochastic signal processing, developed a coherent view from measurements to decisions.
Optimal filtering
17.5/20
Performance assessed under uncertainty and noise.
Wiener and Kalman filtering, covariance modelling, ROC analysis and Monte Carlo evaluation provide the methodological bridge between radar, sonar and broader sensing problems.
Research direction
Seeking junior engineering, funded PhD or industrial doctorate opportunities where I can deepen these foundations through modelling, simulation, experimentation and validation.
Selected work / 03
Projects built around evidence, not buzzwords.
A curated selection of academic engineering projects. Each one highlights the question, method and validation logic rather than claiming production-level maturity.
01
Geometric Vision & 3D Reconstruction
Camera calibration and scene reconstruction using normalised DLT, SVD decomposition, RANSAC-based fundamental matrix estimation and triangulation.
Method
DLT · SVD · RANSAC · Reprojection analysis
02
Quadcopter Autonomy, Estimation & Control
A modular drone study spanning IMU-based attitude estimation, Raspberry Pi–MultiWii integration, ground-station communication and virtual waypoint missions.
Kalman + PIDMSP / MAVLinkPWMSITL
03
Multivariable Process Control
Coupled level–temperature modelling from mass and energy balances, followed by linearisation, LQR design and stability analysis.
MATLABSimulinkLQRLyapunov
04
Radar, Sonar & Statistical Detection
A focused academic track combining radar signal processing and sonar systems with Neyman–Pearson detection, covariance estimation and optimal filtering. Performance was evaluated through ROC curves and Monte Carlo experiments.
Academic evidence
Radar 17.3/20 · 3/25 · Sonar 18/20 · Filtering 17.5/20
05
Multispectral & Industrial Vision
Image-analysis pipelines for counting, classification and spectral interpretation using geometric, colour and histogram descriptors.
OpenCVMATLABNDVISAM
06
Blind Source Separation with AMUSE
Recovery of latent signals from mixed sensor observations using lagged covariance matrices, generalised eigendecomposition and spectral checks, followed by Gaussian-noise stress tests.
AMUSECovarianceGeneralised EVDWelch PSD
07
Instrumentation & Embedded Interfaces
Laboratory work connecting bridge-sensor conditioning and ADC modelling with microcontroller, embedded Linux, digital-bus and inertial-sensor experiments.
AD8237LTspiceATmega328Raspberry Pi
Current research / 04
Erasmus+ research internship · DITEN, University of Genoa
01
02
03
Applied modelling and validation at the intersection of human movement and marine environments.
My final-year internship studies Motion Induced Interruptions and postural stability in marine environments. The work combines OpenSim musculoskeletal modelling, SCONE simulations, biomechanical data processing, inverse kinematics, inverse dynamics, static optimisation, seakeeping concepts and critical model validation. Technical details remain selective while the project is ongoing.
Traceable assumptions
Document what the model knows, what it ignores and why.
Validation before claims
Compare analytical, numerical and observed behaviour.
Critical interpretation
Treat limitations as part of the engineering result.
Academic path / 05
An international route through science and engineering.
Built across Italy and France, extended through research in Genoa.
2026
Research experience
Erasmus+ Research Intern · University of Genoa, DITEN
Biomechanics, OpenSim, SCONE, postural stability, scientific computing and validation in a multidisciplinary marine-research setting.
2024
—26
—26
Master’s degree
MSc Complex Systems Engineering · VISTA
Vision, signal processing, tracking, estimation, automatic control and embedded systems at Université de Toulon.
2021
—24
—24
Bachelor’s degree
BSc Engineering Sciences
Foundations in electronics, electromagnetism, signals, automatic control, numerical technologies and embedded Linux.
2021
Scientific education
Scientific High School Diploma
Scientific secondary education completed in Parma, Italy.
Toolbox / 06
Methods and tools, tied to where I used them.
A realistic snapshot of an early-career profile: strong analytical foundations, growing implementation depth.
Methods
- Radar / sonar signal processing
- Bayesian estimation & Kalman filtering
- Detection, ROC & Monte Carlo analysis
- Blind source separation & covariance analysis
- DLT, SVD, RANSAC & triangulation
- PID, LQR & state-space methods
- OpenSim: IK, ID & static optimisation
- SCONE biomechanical simulation & validation
Software
- MATLAB / Simulink
- Python · NumPy · pandas
- OpenCV
- ArduPilot · SITL · Mission Planner
- LTspice · Vivado
- OpenSim · SCONE
Systems
- Raspberry Pi & embedded Linux
- ATmega328 · MultiWii · Pixhawk
- I²C · SPI · UART · GPIO
- MSP · MAVLink · PWM
- IMU acquisition & sensor fusion
Languages
ItalianNative
EnglishC1 · EF SET
FrenchB2 · TCF
SpanishB1
Contact / 07
Let’s discuss a problem worth modelling.
Open to graduate engineering roles, applied R&D and funded PhD or industrial doctorate opportunities from October–November 2026, especially in biomechanics, modelling and simulation, radar, sonar, statistical signal processing, control and multisensor systems.