Nikolaos (Nikos) Nikolaou

Available PhD Opportunities

Applications for the September 2025 cohort of UCL's CDT in Data Intensive Science (UCL CDT-DIS) will open in October (link)! We offer a 4-year PhD programme, at the intersection of Machine Learning / Artificial Intelligence & Physics, with multiple training & industrial placement opportunities!
I will be offering my PhD projects via the CDT-DIS. Anyone interested is welcome to apply and/or contact me for more details.

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Student Supervision

I have (co-)supervised or I am currently (co-)supervising 7 PhD students, 38 MSc Students, 1 BSc student summer project & 4 industrial placement group projects involving 9 PhD students (listed below). Several of my students' projects have received prizes (5 MSc & 1 PhD) and/or led to publications, with more under preparation. Unless otherwise specified, all my students were from UCL P&A.

Students wishing more details added (project title, current affiliation, links etc.), please get in touch.

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PhD Students

• Main supervisor:
• James K. Ray - Interpretable galaxy imaging from large surveys using supervised & unsupervised machine learning (2022-present)
• Jools D. Clarke - Investigating performance, interpretability & resource efficiency trade-offs of machine learning models for exoplanet data (2023-present)
• Emily Lewis - Physics-informed neural networks for accelerating plasma simulations on the JET fusion reactor (2024-present)
  Co-supervised by Dr. Stanislas Pamela at UKAEA. Currently in her final year, took over supervision from Yiannis Andreopoulos after he left UCL.
• Tara Tahseen - Using deep learning to model complex chemistries of exoplanet atmospheres (2024-present)
  Co-supervised by Prof. Giovanna Tinetti. Currently in her 3rd year, took over supervision from Ingo Waldmann while on his secondment.


• Co-supervisor:
• Paul Nathan - Anomaly detection in DESI spectra using autoencoders and other machine learning techniques (2022-present)
  Main supervisor: Ofer Lahav
• Alex Saoulis - Simulation-Based Inference for Seismic Source Inversion (2022-present)
  Main supervisors: Benjamin Joachimi, Ana Ferreira
• Max Hipperson - Characterising the surfaces of solar system planets using deep learning (2019-present)
  Main supervisor: Ingo Waldmann
• Mario Morván - Deep learning, shallow dips: transit light curves have never been so trendy (2018-22)
  *UCL Physics & Astronomy Jon Darius Memorial Prize 2022*
  Main supervisor: Ingo Waldmann
• Kai Hou (Gordon) Yip - Expect the unexpected: deciphering exoplanetary signals with machine learning techniques (2018-21)
  Main supervisor: Giovanna Tinetti


• Auxiliary Supervisor:
• Angelos R. Nikolopoulos (2022-present, Electrical and Electronic Engineering, University of Southampton)
  Main supervisor: Efstratios Batzelis


• Visiting PhD Students
• Mengfei Sun (2024-present, School of Astronomy and Space Science, Nanjing University)
  Main supervisor: Jiwei Xie


• UCL Supervisor of 3-month CDT-DIS Industrial Partner Group Projects
• Toby Dixon, Dakshesh Kololgi & Jason Ran (2024, UCL Computational Radiation Biology & Oncology Lab)
• Antónia Vojteková, James K. Ray & Noah C. Hall (2023, The London Data Company)
• Philipa Duckett & Matthew Docherty (2022, ASOS)
• Petr Mánek & Graham Van Goffrier (2020, UKAEA)

MSc Students

• Main supervisor:
• Metehan Ali - Uncertainty Quantification & Interpretability of CNN and ViT Models for Colorectal Histopathology Tissue Classification (2024-25)
• Ines Cocco - Uncertainty quantification & interpretability of deep learning models for skin lesion classification (2024-25)
• Cesar Cornejo Tyson - Uncertainty quantification & interpretability of deep learning models for the diagnosis of retinopathy of prematurity (2024-25)
• Zara Ercan - Optimising the Beta Poloidal Parameter in Fusion Reactors using Ensemble Machine Learning Methods (2024-25)
• Hanan Alaskar - Uncertainty quantification & interpretability of machine learning models for medical imaging (TBD) (2024-25)
• Jiayu Wang - Uncertainty quantification & interpretability of machine learning models for medical imaging (TBD) (2024-25)
• Linfang Guo - Uncertainty quantification & interpretability of machine learning models for medical imaging (TBD) (2024-25)
• Tianyu Zhang - Uncertainty quantification & interpretability of machine learning models for medical imaging (TBD) (2024-25)
• Xinyuan Chen - Machine Learning Models for Conditional Galaxy Generation (2024-25)
• Xingyue Li - Machine Learning Models for Causal Inference in Galaxy Properties (2024-25)
• Daniel Kornai - Machine Learning Methods for Causal Discovery in Observational Time Series Data (2023-24)
• Yutong (Ester) Li - Interpretable Deep Learning Models for Retinopathy Severity Classification (2023-24)
  *UCL Physics & Astronomy Harrie Massey Prize in Scientific and Data Intensive Computing (Best Overall MSc Student) 2024*
• Shiyuan Fang - Diagnosis of COVID-19 Pulmonary Infections Using an Interpretable Deep Learning Model (2023-24)
• Yu Fan - Investigating the Effects of Feature Selection and Calibration on Breast Cancer Survival Analysis (2023-24)
• Xilin Chen - Impact of Dataset Differences on Breast Cancer Survival Analysis (2023-24)
• Mengni Wang - Generative models of galaxy images (2022-23)
• Yanwenjing Qu - Generative models of galaxy images (2022-23)
• Runyang You - Improving the efficiency of exoplanet atmosphere characterization with active learning and knowledge distillation (2022-23)
  *UCL Physics & Astronomy Harrie Massey Prize in Scientific and Data Intensive Computing (Best Overall MSc Student) 2023*
• Ruichen Pan - Model interpretability exploration of exoplanet characterization models (2022-23)
• You Zuo - Transfer learning for short-term photovoltaic generation forecasting with deep neural networks (2022-23)
  *UCL MAPS Postgraduate (MSc) Innovation and Enterprise Prize 2023*
• Yumeng Liu - Improving machine learning models for treatment effect estimation with data augmentation (2022-23)
• Congxu Zhao - Interpreting the predictions of machine learning models for treatment effect estimation (2022-23)
• Jingyao Li - Examining the influence of the base-learner for treatment effect estimation (2022-23)
• Tianxi Wen - Interpreting vision transformers for melanoma classification using GradCAM (2022-23)
• Wenteng Ma - Interpreting vision transformers for melanoma classification from skin lesion images using attention maps (2022-23)
• Xinyi Hu - Dimensionality reduction for breast cancer survival prediction (2022-23)
• Duojiao Mu - Interpreting models for breast cancer survival prediction (2022-23)
• Yasona Neocleous - Interpretable machine learning models for melanoma classification from skin lesion images (2022-23)
  *UCL Physics & Astronomy Brian Duff Memorial Prize (Best MSci Project) 2023*
• Yahya Scerbo (2021-22, Industry-based MSc research project at ASOS)
• Rohit Sekhar (2021-22, Industry-based MSc research project at ASOS)
• Bowen Ding (2021-22, Industry-based MSc research project at ASOS)


• Co-supervisor:
• Yimeng (Erie) Fang - Machine Learning for Predicting Ionization Channels Interacting with High Photon Energy Pulses (2024-25)
  Main supervisor: Agapi Emmanouilidou
• Abdurrahman Arosi - Open source methods for parallel 3D Watershed segmentation (2023-24)
  Industry-based MSc research project at BP
• Longwen Hu - Tweet classification for OSR topics (2022-23)
  Industry-based MSc research project at the Office for Statistics Regulation, UK
• Cristian Ignat - Finding exoplanets using direct imaging and deep learning (2019-20)
  *UCL Physics & Astronomy Tessella Prize 2020*
  Main supervisor: Ingo Waldmann
• Adipol Phosrisom - Large-Scale structure cosmology with the KiDS survey (2019-20)
  Main supervisor: Benjamin Joachimi


• Auxiliary Supervisor:
• Jacob G. Ellen (2020-21)
  UCL; Industry-based MSc Project at AstraZeneca, Main supervisor: Natasha Markuzon
• Nour Skaf (2019-20)
  Imperial College London; Visiting Student at UCL, Main supervisor: Ingo Waldmann

BSc Students

• Yasona Neocleous (2022, 3rd Year DIS CDT Summer Project Supervisor)