Profile
Dr Tinkle Chugh
Students
PhD students
- 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
- Taylor, Gabrielle (2023/24, MSc Data Science). Multivariate Time series Correlations and Predictions in CFD (collaboration with Center of Hydraulic Research Czech Republic)
- Arthur Finch (2023/24, MSc Data Science). Bayesian inference of wake models in Wind Farm layout optimisation
- Daniel Burke (2023/24, MSc Data Science). Bayesian inference of wake models in Wind Farm layout optimisation
- Duc Dat Hoang (2023/24, MSc Data Science). (Multi-objective) Optimisation of Network on Chip (collaboration with Souyma J at BITS Pilani Hyderabad, India)
- Torntan Chainant (2023/24, MSc Data Science). (Multi-objective) Optimisation of Network on Chip (collaboration with Souyma J at BITS Pilani Hyderabad, India)
- Franz Herm (2023/24, MSc Data Science with AI). Multi-agent Reinforcement Learning for Autonomous Driving in Mixed Traffic Environment (collaboration with Atanu Mazumdar at Aalto University, Finland)
- Hao Liu (2023/24, MSc Data Science with AI). Model-based evolutionary multiobjective RL for continuous control
- 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.
BSc Project Students
- Sanchi Chakraborty (2023/24). BSc Computer Science. Machine Learning in Educational Psychology (collaboration with Marek Urban and Kamila Urban, Institute of Psychology, Czech Academy of Sciences)
- Marcus Connolly (2023/24). BSc Data Science. LLMs in Educational Psychology (collaboration with Marek Urban and Kamila Urban, Institute of Psychology, Czech Academy of Sciences)
- Kelsey Holdgate (2023/24). BSc Computer Science. Simulating Human Approach in Solving Rubik's cube
- Dimitar Sivrev (2023/24). BSc Computer Science. ML in Time-series Forecasting
- Simran Sahota (2023/24). BSc Computer Science. Supervised and Unsupervised ML in Cricket
- Will Riddy (2023/24). BSc Data Science. Supervised and Unsupervised ML in Squash
- Ruslan Prigarin (2023/24). BSc Computer Science. Game to Mimic Evacuation during Flooding
- Zhixuan Cai (2023/24). BSc Computer Science. Optimal location to build wind farms
- Joshua Curry (2023/24). BSc Computer Science. ML to simulate tipping points in Climate Change
- Ghali Benlghadane (2023/24). BSc Computer Science. Bayesian vs Frequentist Approach in analysing Sports data
- Rohit Pawar (2023/24). BSc Data Science. Multi-task Bayesian optimisation
- Matt Morris (2023/24). BSc Computer Science. Multi-task Bayesian optimisation for Process Engineering Application
- Toby Slump (2023/24). BSc Computer Science. Supervised ML to quantify the effect of cyclones
- Montgomery Batt (2022/23) - Spatio-Temporal Modelling
- 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
- Ashley Richter (2021/22). Project title: Neural Style Transfer.
- Jamie Nottage (2020/21). Project title: Bayesian framework to measure the correlation between traffic and COVID-19 cases
- Matthew (2020/21). Project title: Optimisation and Analysis of Neural Networks for AI Gameplay
- Nicklas Wenzler (2020/21). Project title: Importance of differential privacy.
- Benjamin Trotter: Investigating Trading Strategies via Multi-objective Optimisation