プロフィール詳細

プロジェクトを作成

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Dr. Sobhan N.に依頼

United Kingdom

PhD | Energy Systems · Machine Learning · Sustainability & Decarbonization Analytics

プロフィール概要

I am a Ph.D.-qualified researcher and scientific consultant with 10+ years of experience at the intersection of energy systems, machine learning, and sustainability analytics. Currently a Postdoctoral Research Fellow at Queen Mary University of London working on PV & BESS systems optimisation, and before that I worked on the UKRI-funded DIGEST project — building Python-based optimisation models for grid-scale energy storage deployment and CO₂ emissions analysis across the GB transmission network. Previously held postdoctoral roles at the University of Glasgow across three funded projects: the EU Horizon H2020 ENCLUDE project (citizen decarbonization clustering and GIS-based energy segmentation), the EPSRC Street2Grid project (AI-driven peer-to-peer energy trading platform and smart grid digital twin), and LLM-based sequence-to-sequence modelling for peptide sequencing. I offer freelance services in: data analysis and machine learning modelling (Python, Scikit-learn, PyTorch, TensorFlow), time-series forecasting, clustering and segmentation, energy systems consulting, scientific writing and peer-reviewed manuscript preparation, statistical analysis, literature reviews, grant writing support, and experimental design for data-driven research projects. I have published in peer-reviewed journals including Journal of Cleaner Production, IET Generation Transmission & Distribution, Energy Research & Social Science, and IEEE and have delivered official EU project deliverables and technical reports. I am comfortable working with both academic and industry clients and delivering high-quality outputs on tight timelines.

専門分野

• ☆ Electrical Engineering
• ☆ Batteries & Fuel Cells
• ☆ Power Engineering
• ☆ Signal Processing
• ☆ Microelectronics
• ☆ Energy Security
• ☆ Data Analysis
• ☆ Machine Learning
• ☆ Artificial Intelligence
• ☆ Statistics
• ☆ Renewable Energy
• ☆ Solar Energy
• ☆ Green Building Design/Sustainable Construction
• ☆ Python
• ☆ Matlab
• ☆ Tensorflow
• ☆ LaTex
• ☆ Scikit-learn
• ☆ Sustainable Development

サービス

• Writing
• Research
• Consulting
• Data & AI
• Product Development

Writing Technical Writing, General Proofreading & Editing, Translation

Research Feasibility Study, Fact Checking, Gap Analysis, Scientific and Technical Research, Systematic Literature Review

Consulting Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Image Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Data Visualization, Big Data Analytics, Text Mining & Analytics, Data Mining, Data Cleaning, Data Processing

Product Development Concept Development, Prototyping, Reverse Engineering, Device Fabrication

職務経験

Queen Mary University of London

- 現在

Postdoctoral Research Associate

Queen Mary, University of London

5月 2026 - 現在

Postdoctoral Research fellow

Brunel University London

10月 2024 - 4月 2026

Postdoctoral Research Associate

University of Glasgow

12月 2020 - 9月 2024

Consultant Engineer

Electricity Distribution Company of Hamedan

8月 2017 - 11月 2020

学歴

PhD

Shahid Beheshti University

9月 2012 - 5月 2017

認定資格

• 認定資格の詳細は未入力です。

出版物

BOOK CHAPTER

Sobhan Naderian, Hamidreza Arasteh (2025). Nonintrusive Load Monitoring in Smart Grids Using Deep Learning Approach . Data‐Driven Energy Management and Tariff Optimization in Power Systems.

Sobhan Naderian, Hamidreza Arasteh, Niki Moslemi, Majid Miri Larimi, Pierluigi Siano, Josep M. Guerrero (2025). Applications of Data Mining in Industrial Tariff Design and Energy Management . Data‐Driven Energy Management and Tariff Optimization in Power Systems.

JOURNAL ARTICLE

Sobhan Naderian, Anastasia Ioannou, Gioia Falcone (2025). A novel approach to deriving energy citizens profiles for effective energy Policies: Clustering and statistical analyses applied to UK data . Journal of Cleaner Production.

Sobhan Naderian, Nicola Tait, Graeme Hunt, Gioia Falcone (2025). Glasgow's hidden energy patterns: Energy clustering and social geospatial analysis for a just transition . Energy Research & Social Science.

Sobhan Naderian(2021). A Novel Hybrid Deep Learning Approach for Non-Intrusive Load Monitoring of Residential Appliance Based on Long Short Term Memory and Convolutional Neural Networks . arXiv

Sobhan Naderian, Ahmad Salemnia (2019). An implementation of S-transform and type-2 fuzzy kernel based support vector machine algorithm for power quality events classification . Journal of Intelligent & Fuzzy Systems.

Sobhan Naderian, Ahmad Salemnia (2017). An implementation of type-2 fuzzy kernel based support vector machine algorithm for power quality events classification . International Transactions on Electrical Energy Systems.

Sobhan Naderian, Ahmad Salemnia (2017). Method for classification of PQ events based on discrete Gabor transform with FIR window and T2FK‐based SVM and its experimental verification . IET Generation, Transmission & Distribution.

CONFERENCE PAPER

Sobhan Naderian, Naveen Kumar, Vihar Georgiev (2024). Peptide Sequencing Using Neural Machine Translation Based on Sequence-2-Sequence Architecture and Long Short-Term Memory Networks . ECSA-11.

E. Vega-Fuentes, S. Naderian, J. Yang, F. Déniz, R. Lazzari, C. Sandroni (2023). Power flow tracing validation based on digital signal processing techniques . IET Conference Proceedings.

Sobhan Naderian (2022). Machine learning approach for non-intrusive load monitoring in smart grids: new deep learning method based on long short-term memory and convolutional neural networks . 2022 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS).

Sobhan Naderian, Ahmad Salemnia (2015). Detection and classification of power-quality events using discrete Gabor transform and Support Vector Machine . The 6th Power Electronics, Drive Systems & Technologies Conference (PEDSTC2015).

Sobhan Naderian Cluster analysis of UK citizens based on CO2 footprint and energy consumption. ETP Annual Conference 2023.

REPORT

Sobhan Naderian D4. 3–Report on bridging clusters for decarbonization with energy models .

Sobhan Naderian D4.1 – Report on qualified clustering input attributes .

Sobhan Naderian, Gioia Falcone D4.2 – Report on the identification of citizens’ clusters for decarbonization .