About
I am passionate about sustainability, with a focus on energy systems, net zero communities and green transportation. I hold a Double MSc in Sustainable Energy Systems, data analytics and AI (Distinction), a certificate in Business Management from ESADE, and a Bachelor's in Energy Engineering (First Class Honours). My expertise spans energy storage optimisation, energy advisory, renewable energy integration, and data-driven energy solutions.
Experience
Energy Engineer – Freelance
07/2025 – Present- Research, development and validation of a multi-market optimisation model for utility-scale energy storage (BESS) across arbitrage and balancing markets, demonstrating independent problem-solving and critical thinking.
- Integration of ML and deep reinforcement learning for enhanced market participation strategies, requiring adaptability and self-management in a fast-paced research environment.
- Enrichment with external data (weather and congestion indicators) to improve model accuracy through systematic analysis and attention to detail.
Energy Engineer
02/2025 – 06/2025- Development of a model to maximise revenue streams for utility-scale energy storage technologies (BESS) through participation in arbitrage and balancing markets, working collaboratively in cross-functional teams.
- Implementation using optimisation tools (Pyomo and Gurobi) and historical market data analysis, demonstrating analytical thinking and technical communication skills.
Energy Consultant
09/2024 – 05/2025- Designed sustainable off-grid energy system for an island resort, targeting 40% reduction of carbon emissions by 2030, requiring strategic thinking and effective stakeholder management.
- Conducted comprehensive energy audit and expanded solar PV capacity, presenting findings through clear client communication and presentation skills.
- Suggested innovative energy storage solutions and analysed additional renewable energy sources, balancing technical feasibility with client requirements.
Energy Analyst
09/2023 – 05/2024- Co-led project aimed at decarbonising and expanding district heating networks in Bristol to promote the city's green transition, demonstrating leadership and cross-functional collaboration.
- Led the modelling and environomic assessment of different technologies and options, applying project management and effective communication skills.
- Derived optimal solution through comprehensive analysis and evaluation, coordinating with multiple stakeholders and technical teams.
Operational & Maintenance Engineer
09/2021 – 08/2022- Operation, preventive, predictive and corrective maintenance of large-scale PV parks, requiring strong problem-solving skills and attention to detail.
- Monitoring of PV parks' performance, benchmarking and troubleshooting, demonstrating technical communication and time management.
- Drafting performance reports on operation and maintenance, effectively communicating technical findings to stakeholders.
- Contributed to the design of new combined solar-battery park projects, collaborating with engineering teams.
- Market research for battery technologies and products, analyzing technical specifications and market trends.
CEO & Design Engineer
12/2019 – 06/2021- Served as CEO and Lead Designer for IWES, an AI-driven system designed to reduce food waste in school canteens by estimating wasted food mass, demonstrating leadership and entrepreneurial mindset.
- Secured corporate sponsorship from Nvidia to support the project's technical development and AI integration, utilizing negotiation skills and effective stakeholder engagement.
- Designed and prototyped the camera and the electronics infrastructure using CREO, managing the project from concept to prototype.
Projects
Multi-Market Optimisation for Energy Storage (Master Thesis)
2024 – 2025 +Developed a multi-market optimization model for Battery Energy Storage Systems (BESS) operating in Belgium. The model enables storage operators to simultaneously access arbitrage markets (Day-Ahead and Imbalance) and ancillary service markets (FCR, aFRR).
Key methodology: Implemented in Pyomo using mixed-integer linear programming (MILP) with 15-minute resolution. The model captures operational constraints, round-trip efficiency losses, and battery degradation effects under multiple cycling scenarios. Market data from Elia (2024) was used to simulate real-world operation and validate the approach.
Key finding: Coordinated multi-market participation significantly improves BESS profitability over single-market strategies. Ancillary services provide stable baseline revenue while arbitrage exploits price volatility for additional gains.
Predicting Electricity Consumption Using Neural Networks
10/2024 – 01/2025 +Developed a Multilayer Perceptron (MLP) neural network to forecast electricity demand in Spain's peninsular region for the upcoming 2 hours, segmented into 30-minute intervals. The model was trained on real-world consumption data from February to August 2024.
Key methodology: Implemented a sliding window approach with a 25-hour lookback period (n=50) to capture temporal patterns. Integrated exogenous variables including temperature and wind speed to enhance predictive capabilities. The network architecture featured 3 hidden layers (128→64→32 neurons) with batch normalization and dropout regularization (0.2) to prevent overfitting.
Data-Driven Optimisation of Heating/Cooling System
10/2024 – 01/2025 +Developed a comprehensive methodology to optimize heat pump sizing for UK residential buildings using load disaggregation techniques on historical energy consumption data coupled with regional weather information.
Key methodology: Implemented Non-Intrusive Load Monitoring (NILM) using NILMTK toolkit and deep learning approaches to disaggregate heating/cooling loads from total household consumption. Integrated weather data correlation to identify temperature-dependent patterns and calculate optimal heat pump capacities for both electrified and non-electrified homes.
Moonshot Project: Underground Horizons
10/2024 – 01/2025 +Designed an innovative underground vertical farming system for Mars that addresses the unique challenges of Martian agriculture: extreme radiation, temperature fluctuations, and limited water resources. The system leverages underground lava tubes for natural radiation shielding and thermal stability.
Key innovations: Integrated precision farming technology with LED grow lights optimized for plant photosynthesis, closed-loop hydroponic systems for water recycling, and CO₂ extraction from the Martian atmosphere. Surface-mounted PV arrays provide sustainable power for the entire operation.
Modelling & Optimisation for Net Zero Communities (Bachelor Thesis)
10/2022 – 06/2023 +Developed a comprehensive multi-criteria optimisation framework for designing net-zero energy communities. The model integrates real-time meteorological data via APIs, energy generation/consumption profiles, and techno-economic parameters to evaluate renewable energy configurations.
Methodology: Analysed multiple scenarios combining solar PV, wind turbines, and battery storage systems. Optimization criteria included energy self-sufficiency, levelized cost of energy (LCOE), net present value (NPV), and carbon emission reductions. The tool helps communities identify the optimal balance between investment costs and environmental benefits.
Education
MSc in Digital Energy Systems
09/2024 – 07/2025
MSc in Sustainable Energy Systems
08/2023 – 06/2024
Entrepreneurship Integrated Programme
08/2023 – 05/2025
Summer School in Data Science & AI for Energy
07/2024 – 08/2024
BEng in Energy Engineering with Industry Year
09/2019 – 05/2023Photos
I've been passionate about street and travel photography since I was 16, capturing everyday moments, architecture, and natural light through a distinctive visual lens.
