CV

Arastun's CV

Basics

Name Arastun Mammadli
Label MSc Student
Email arastun.mammadli24@imperial.ac.uk
Phone +44(0)7354997309
Url https://linkedin.com/in/arastun-mammadli
Summary MSc student in Applied Computational Science at Imperial College London focused on practical applications of machine learning, deep learning, and large language models. Interested in scientific machine learning and AI agent orchestrations. My dissertation work is on applying emerging agentic frameworks on campus energy management with Azure AI Services @ Microsoft under Prof. Lee Stott's supervision.

Education

  • 2024.09 - 2025.09

    London, UK

    MSc
    Imperial College London
    Applied Computational Science and Engineering
    • Computational Mathematics
    • Deep Learning
    • Data Science & Machine Learning
  • 2020.09 - 2024.05

    Exeter, UK

    BSc
    University of Exeter
    Computer Science
    • Dean’s List for Year 1 (top 5%)
  • 2018.09 - 2020.05

    Azerbaijan

    IB
    Dunya IB School
    International Baccalaureate Diploma
    • Extended Essay: Genetic Algorithms in Constrained Optimization Problems

Work

  • 2025.06 - 2025.09
    Research Intern
    Microsoft
    Worked on conversational multi-agent workflows for campus energy management.
    • Developed a full-stack prototype using Azure AI Agent Services, Azure AI Search (RAG), and Azure AI Language.
    • Applied Azure Evaluation SDK for model selection, prompting, query complexity, and routing ablations.
    • Independently managed project timelines and reported weekly progress to Microsoft stakeholders.
  • 2025.05 - 2025.05
    Internal Project
    Imperial College London
    Developed genetic algorithm solvers for circuit design optimisation.
    • Built discrete and continuous genetic algorithm solvers.
    • Developed a circuit simulator (mass-balance solver) and a validity checker.
    • Managed team GitHub repository and collaborated with 8 team members.
  • 2025.01 - 2025.03
    Internal Project
    Imperial College London
    Developed deep learning models for real-time lightning storm prediction.
    • Developed DL (U-Net, Conv-LSTM) models for storm prediction.
    • Worked on satellite imagery and time-series analysis.
    • Strengthened expertise in deep learning and scientific computing.
  • 2023.05 - 2023.08
    Software Developer Intern
    EMBAWOOD LLC
    Developed and maintained Java-based applications using the Spring Framework.
    • Built Spring Boot RESTful APIs for internal tools.
    • Participated in code reviews and technical presentations.
    • Wrote unit and integration tests with JUnit to reduce production bugs.

Skills

Programming Languages
Python
C++
C
Java
C#
Tools & Frameworks
Git
REST APIs
Azure AI Services
Azure Foundry
React
PyTorch
MPI

Languages

English
Fluent
Azerbaijani
Fluent
Russian
Fluent
Turkish
Fluent
Spanish
Limited Working Proficiency

Interests

Competitive Programming
Research in LLM agents, ML, and Scientific Computing

References

Available upon request