About me

I'm an AI Engineer and Data Scientist with a PhD in Data Science and a passion for developing AI-powered applications that solve real-world problems. With experience across academia and industry, I specialise in AI engineering, software development, machine learning, data science, and optimisation. I combine rigorous research with hands-on engineering to deliver impactful, scalable solutions.

What i'm doing

  • AI Engineering

    Building intelligent systems using LLMs, LangChain, RAG, and modern AI frameworks.

  • Software Engineering

    Designing and implementing robust software solutions with best practices in coding and architecture.

  • Data Science

    End-to-end data pipelines, analysis, and visualization to drive decision-making.

  • Machine Learning

    Developing and deploying models for forecasting, classification, and optimization.

My skills

Programming Languages
  • Python
  • JavaScript/TypeScript
  • SQL
  • MATLAB
  • R
  • Markdown
  • LaTeX
AI & ML
  • LangChain
  • LangGraph
  • LangSmith
  • Pinecone
  • Chroma
  • PyTorch
  • TensorFlow
Software Development
  • FastAPI
  • Node.js
  • Express.js
  • Bootstrap
Data & Visualisation
  • Pandas
  • NumPy
  • Matplotlib
  • Seaborn
  • Plotly
  • Pyomo
  • PostgreSQL
  • MySQL
  • SQLite
  • MongoDB
  • Power BI

Resume

Download CV

Experience

  1. Data Scientist

    October 2025 — March 2026
    heatly
    Leeds
    • Built a complete autonomous ETL pipeline to provide the necessary data for the company’s database: extracting data from various sources, such as PDFs and charts, via LLMWhisperer, the OpenAI API, and WebPlotDigitizer. Transforming the raw data into structured data using Python (Pandas). Storing the structured data in a database using SQL.
    • Developed a full-stack web application using Node.js to estimate and compare operational costs for customers using a heat pump and a gas boiler for heating. Customers’ energy consumption and weather data are extracted from their smart meter via the Glow API and the Open-Meteo API.

  2. Postdoctoral Research Associate in Data Science

    August 2024 — October 2025
    Newcastle University
    Newcastle upon Tyne
    • Quantify and evaluate the value of low-carbon technologies, such as solar panels, electrical and thermal storage systems, and heat pumps, within the smart home energy management system (SHEMS) framework.
    • Review and evaluate the roof-rental mechanisms in the UK and internationally and propose the potential research directions and technologies for further improvement.

  3. Data & Analytics Intern

    April 2024 — June 2024
    Essex County Council
    Chelmsford
    • Analysed the dependence between the demand for services (i.e., Waste and Recycling, Children and Adults Social Care, and Highways) and corresponding complaints received by the Essex County Council using Granger Causality Test and Distance Correlation. The data preprocessing and analysis are implemented in R and RStudio.
    • Examined and visualised different measures for each district in Essex, such as Business, Economy and Industry, Education and Skills, Population and Community Information, Health and Social Care, and Road and Transportation, using Power BI.

  4. Research Officer

    April 2023 — July 2023
    University of Essex
    Colchester
    • Developed dynamic programming and Dijkstras-based algorithms using Python to solve the shortest path problem with multiple destinations.

  5. Assistant Lecturer

    October 2021 — April 2023
    University of Essex
    Colchester
    • Taught machine learning techniques (e.g., regression, classification, clustering) in Statistical Methods, Modelling Experimental Data and Applied Statistics.
    • Taught to code each algorithm using R and RStudio and marked assignments.

  6. Research Assistant

    April 2022 — July 2022
    University of Essex
    Colchester
    • Developed a novel mixed-integer linear programming (MILP) model for optimal energy allocation and pricing under the uncertainty of renewable energies using MATLAB. It solved it using a genetic algorithm (GA).

Education

  1. Ph.D. in Data Science

    October 2020 — July 2024
    University of Essex
    Colchester
    • Developed a smart hierarchical transactive energy system that considers multi-energy, renewable energies and demand side management using bilevel optimisation models and metaheuristics approaches, such as GA, particle swarm optimisation (PSO) and simulated annealing (SA) algorithms.
    • Developed a Transformer-based long-term time-series forecasting model for multi-energy load prediction using PyTorch.

  2. M.Sc. in Banking and Finance

    September 2018 — September 2019
    University of Sussex
    Brighton
    • Grade: Distinction (79%)
    • Thesis: The magnitude of the impact of crude oil prices’ shock on different commodity markets: evidence from DCC-GJR-GARCH model
    • Best Student Award:
      • Accounting & Finance prize for the Best Student in MSc. Banking and Finance

Portfolio

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