Jake Hollins (2022 – Present, Co-supervised with Dr Konstantinos Agathos at the department of Engineering). Topic: Bayesian Multi-Objective Optimisation and Multi-Fidelity Reduced-Order Models for Digital Twinning.
Atanu Majumdar (2018 – 2022, Co-supervised with Prof Kaisa Miettinen, and Prof Jussi Hakanen at the University of Jyvaskyla, Finland). Thesis title: Novel Approaches for Offline Data-Driven Evolutionary Multiobjective Optimization. Thesis can be downloaded from https://jyx.jyu.fi/handle/123456789/78886. After PhD, Atanu started working as Postdoc researcher at the University of Jyvaskyla.
MSc Project Students
Zhou DingCheng (2022/23, MSc Computer Science, co-supervised with Dr Cyril Morcrette in Maths department). Predicting Cloud Fraction with ML
Chenming Fu (2022/23, MSc Computer Science). Image text quiz using multimodal deep learning
Zhuohang Liu (2022/23, MSc Computer Science). Analysis of user reviews of food delivery apps with NLP
Tejas Rajput (2022/23, MSc Data Science). Optimising Hyperparameters in CNNs using BO
Vishnu (2022/23, MSc Cyber Security). Automated system for real-time cyber threat detection with machine learning
Jiling Zhou (2022/23, MSc Cyber Security). Differential Privacy in DNNs
Ashish Loknath (2022/23, MSc Cyber Security). Encryption and Decryption with Symmetric and Asymmetric Algorithms.
Yogesh (2022/23, MSc Cyber Security). Steganography for hiding data in Images
Alex Evans (2022/23, MSci Computer Science Programme). Multi-objective Bayesian Optimisation.
Dingcheng Zhou (2022/23). Co-supervised with Dr Cyril Morcrette. ML in Climate.
Aayush Shah (2021/22, co-supervised with Dr Katy Sheen at the Department of Geography). Project title: Can artificial intelligence produce an effective early warning system for climate?
Lance Payne (2021/22, co-supervised with Dr Katy Sheen at the Department of Geography). Project title: Can artificial intelligence produce an effective early warning system for climate?
Dinesh Sundaravadive (2021/22, co-supervised with Prof Guangtao Fu at the Department of Engineering). Project title: Flood risk prediction using machine learning.
Gengxiao Li (2021/22, co-supervised with Prof Guangtao Fu at the Department of Engineering). Project title: Flood risk prediction using machine learning.
Yixuan Zhang (2021/22, co-supervised with Prof Guangtao Fu at the Department of Engineering). Project title: Flood risk prediction using machine learning.
Jack Page (2021/22). Jack was part of MSc Professional (Degree Apprenticeship) Programme.
Sourav Chakarobarty (2021/22). Sourav was part of MSc Professional (Degree Apprenticeship) Programme.
Bowen Xiao (2021/22): Bowen was part of MSc Professional (Degree Apprenticeship) Programme.
Chriss Finn (2021/22): Bowen was part of MSc Professional (Degree Apprenticeship) Programme.
Joshua Lillis (2021/22): Joshua was part of MSc Professional (Degree Apprenticeship) Programme.
Shahidul Haq (2021/22): Shahidul was part of MSc Professional (Degree Apprenticeship) Programme.
Endi Ymeraj (2020/21). Project title: Wind Farm Layout Optimisation Using Multiobjective Bayesian Over Sets. The work produced a conference paper (In the proceedings of the GECCO). Endi is working as Data Scientist at British Airways
Deepak Saini (2020/21). Project title: Model Predictive Control of Wind Turbines. Deepak is working as a Software Developer at Saggezza-Infostretch
Arif Malik (2020/21). Project title: Arif is working as Senior Python Developer at Bank of America Merrill Lynch
Rusen Alp (2020/21).
Tuli Saha (2020/21). Tuli was part of MSc Professional (Degree Apprenticeship) Programme.
Simon Stride (2020/21). Tuli was part of MSc Professional (Degree Apprenticeship) Programme.
Steven Hester (2020/21). Steven was part of MSc Professional (Degree Apprenticeship) Programme.
Simon Stride (2020/21). Simon part of MSc Professional (Degree Apprenticeship) Programme.
Rui Go (2020/21). Rui was part of MSc Professional (Degree Apprenticeship) Programme.
Mobayode Fashanu (2022/23) - Machine learning and AI to support Children with learning disabilities
Elsa Guenole-Harrison (2022/23, with G-Research London now) - Bayesian machine learning.
Tsun Hui (2022/23) - Deep Fake
Tanish Mehta (2022/23) - Sentiment analysis in Cricket
Miles Ress (2022/23) - Spatio-Temporal Modelling
Jack Stallard (2022/23, with Accenture London now) - ML to create Fantasy Football Team
Georgi Tarashev (2022/23) - Backtracking in DNN
Nguyen Tu (2022/23, with a startup in Hungary now) - Weather Forecasting using Drones
Thomas Bird (2022/23) - Wind farm layout optimisation
Joseph Wilson (2022/23) - Financial management software for student clubs and societies
Tom Boatman (2021/22). Machine Learning and Optimisation in Optimising Wind Farm Layout Design Under Uncertainty.
Benjamin Narbett (2021/22). Machine learning and optimisation to engineering problems
Alex Evans (2021/22). Machine learning and multi-objective optimisation in design of experiments. The work has been sent to the Artificial Evolution Conference 2022 to be held in Exeter.
Habib Zain (2021/22). How the pandemic affected employee attrition, why it’s happening and how to predict it.
Lilian Pintac (2021/22). Project title: Combining Multi-objective Evolutionary Algorithms with Machine Learning Algorithms to Solve Real World Engineering Problems
