Computer Science

Photo of Dr Tinkle Chugh

Dr Tinkle Chugh

Lecturer (E&R)

 T.Chugh@exeter.ac.uk

Overview

Office: Innovation Centre Phase 1, Room 13

Bio: Hello, I am Tinkle Chugh, working as Lecturer at the Department of Computer Science, University of Exeter, UK. Between Feb 2018 and June 2020, I worked as Postdoctoral Research Fellow in the BIG data methods for improving windstorm FOOTprint prediction (BigFoot) project. I received my Doctor of Philosophy (Ph.D.) in Mathematical Information Technology in 2017 from the University of Jyvaskyla, Finland and Master of Technology (M.Tech) in Chemical Engineering in 2012 from Indian Institute of Technology Hyderabad, India.

My research interests are in evolutionary optimisation, Bayesian optimisation, Multi and Many-objective optimisation, Robust optimisation, Benchmarking for optimisation algorithms, latencies in multi-objective optimisation, uncertainty quantification, Bayesian inference, and applications including wind farm layout optimisation, design of centrifugal pumps, time series modelling, and polymerisation.

Google Scholar profile

If you are interested in doing your Undergraduate, Master or PhD project with me, feel free to contact me for a discussion.

Check these links if you are looking for a PhD position

Grants

1. South Asia Development Fund (2021, University of Exeter), £3600 - PI. I received an award of £3600 to support the travelling of my Indian collaborators to visit the University of Exeter. The award aimed to strengthen the existing collaboration on designing wind farms using machine learning techniques.

2. National Environment Research (NERC) Fellow (2020 - 2021, NERC UK) - £10000 - PI. I received a grant of £10000 as a NERC fellow in the Constructing a Digital Environment Programme funded by NERC, UK. The programme aimed to use machine learning tools in promoting citizen science, visualization and decision making.

3. Research-led Initiative award (2019, University of Exeter) - £1000 - PI. I received an award of £1000 from the University of Exeter under the Research-led initiative programme to organize a workshop on Multiple Criteria Decision Making. The workshop attracted more than 40 participants in different disciplines and received positive feedback.

Teaching and Supervision

1. Coordinator and Lecturer of COMM510 (2020/21 - Present): Multi-objective Optimisation and Decision Making module in MSc Computer Science Programme

2. Coordinator and lecturer of COM3023 (2020/21 - 2022/23 ): Machine learning and AI module in BSc Data Science Programme

3. Coordinator and lecturer of ECMM459 (2020/21 - Present): Statistical Modelling module in MSc Data Science (Professional) Degree Apprenticeship Programme 

4. Supervisor in ECM3401 (2020/21 - Present): Individual Literature Review and Project in the BSc Computer Science Programme

5. Supervisor in ECMM433 (2020/21 - Present): Data Science Project 1 in the MSc Data Science (Professional) Degree Apprenticeship Programme

6. Supervisor in ECMM451, ECMM453, ECMM465 (2020/21 - Present): MSc (Computer Science, Data Science and Cyber Security) Research Project

Awards and Membership

1. Best paper award (2017). I received the best paper award for my paper 'Surrogate-assisted evolutionary multiobjective shape optimization of an air intake ventilation system' at the IEEE Congress on Evolutionary Computation (IEEE CEC) Conference, San Sebastian, Spain. Press release at the University of Jyvaskyla and Press release at the University of Surrey

2. Academic Excellence Award (2012). I received the Academic Excellence Award from former President of India Dr APJ Abdul Kalam at the Indian Institute of Technology Hyderabad, India.

3. Member of International Society on Multiple Criteria Decision Making (2014 - Present)

Invited Talks

  1. Mono-surrogate vs Multi-surrogate at the workshop on Multi-objective Bayesian Optimisation, University of Warwick (Feb 27, 2023)
  2. Multi-objective Bayesian Optimisation and Applications at the Data Science, Machine Learning and Optimisation in Support of the Society of the Future workshop at PPSN 2022 (Sep 11, 2022)
  3. Multi-objective Bayesian Optimisation over Sets at the Multi-objective Optimisation Group, University of Jyvaskyla, Finland (Dec 7 2021, online)
  4. Conflicting Expensive Objectives: Theory and Applications of Machine Learning + Optimisation at the Artificial Intelligence Society, University of Exeter, UK (Dec 14, 2020, online)
  5. Calibrating Citizen Weather Stations at the National Oceanographic Center, UK (May 13, 2020, online)
  6. Evolutionary Computation and Applications at the Met Office, Exeter, UK (January 31, 2019)
  7. Handling Expensive Multiple Objective with Different Latencies at the University of Surrey, UK (April 11, 2018)
  8. Evolutionary Computation in Practice at the Aalto University, Finland (November 24, 2017)

Workshop and Reading Group Organisation

  1. Workshop on Surrogate-assisted Evolutionary Computation at the GECCO conference (2022 - Present) with Alma Rahat, Richard Everson, Handing Wang and Yaochu Jin
  2. Reading Group on Evolutionary Computation and Machine Learning (2020 - Present) at the University of Exeter with George De Ath
  3. Workshop on Evolutionary Computation + Multiple Criteria Decision Making at the GECCO conference (2019 - Present) with Richard Allmendinger and Jussi Hakanen (and Julia Handl from 2023 onwards)
  4. Workshop on Evolutionary Algorithms with Uncertainty at the GECCO conference (2021) with Khulood Alyahya, Jonathan Fieldsend and Juergen Branke
  5. Workshop on Multiple Criteria Decision Making at the University of Exeter (2019)
  6. Workshop on Data Science meets Multiple Criteria Decision Making at the International Conference on MCDM (2019) with Richard Allmendinger and Jussi Hakanen
  7. Workshop on Data-driven Optimization and Applications at the IEEE CEC conference (2017) with Handing Wang and Chaoli Sun

Other Activities

1. Reviewer of journals IEEE Transactions on Evolutionary Computation, IEEE Computational Intelligence Magazine, Soft Computing, Applied Soft Computing, Materials and Manufacturing Processes, Information Sciences, IEEE Transactions on Emerging Topics in Computational Intelligence, Natural Computing, Journal of Global Optimization, Complex and Intelligent Systems, IEEE Transactions on Cybernetics, and conferences GECCO, IJCNN, MCDM, and IEEE SSCI

2. Invited to participate in the Dagstuhl Seminar on Multi-objective Optimisation on a Budget (Sep 3-8, 2023)

3. Invited to participate in special group workshop on MACODA: Many Criteria Optimization and Decision Analysis (16 - 20 Sep 2019) in Leiden, Netherlands

4. Participated in Doctoral Network Training Cruise Seminar (arranged by Prof. Ahti Salo, Aalto University School of Science) from Helsinki to Tallinn, 29-30 May 2017

5. Visited Prof. Yaochu Jin at the University of Surrey, the UK as a Ph.D. student in July-August 2016 and September-November 2015

6. Invited to attend in workshop on surrogate-assisted multi-criteria optimization (SAMCO) from Feb 29 to March 4, 2016, Leiden, Netherlands

7. Participated in EURO PhD School on MCDM from Feb 17 to Feb 28, 2014, Madrid, Spain

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Publications

Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.

| 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 |

2024

2023

2022

2021

2020

2019

2018

2017

2016

  • Sindhya K, Rauhala T, Chugh T, Jin Y, Miettinen K, Hakanen J. (2016) Multiobjective Optimization in Assessment of Transmission Network Compensation Strategy, 28th European Conference on Operational Research 2016, Poznan, Poland, 3rd - 7th Jul 2016.
  • Chugh T, Yaochu J, Kaisa M, Jussi H, Karthik S. (2016) A Kriging-assisted evolutionary algorithm for many-objective optimization.
  • Chugh T, Jin Y, Miettinen K, Hakanen J, Sindhya K. (2016) A Surrogate-assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-objective Optimization, IEEE Transactions on Evolutionary Computation, volume 22, pages 129-142, DOI:10.1109/TEVC.2016.2622301. [PDF]
  • Chugh T, Sindhya K, Miettinen K, Hakanen J, Jin Y. (2016) On Constraint Handling in Surrogate-Assisted Evolutionary Many-Objective Optimization, PARALLEL PROBLEM SOLVING FROM NATURE - PPSN XIV, volume 9921, pages 214-224, DOI:10.1007/978-3-319-45823-6_20. [PDF]
  • Hakanen J, Chugh T, Sindhya K, Jin Y, Miettinen K. (2016) Connections of Reference Vectors and Different Types of Preference Information in Interactive Multiobjective Evolutionary Algorithms, PROCEEDINGS OF 2016 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (SSCI). [PDF]

2015

  • Chugh T, Sindhya K, Hakanen J, Miettinen K, Jin Y. (2015) A surrogate assisted inverse model based evolutionary multiobjective optimization algorithm for computationally expensive problems, Multiple Criteria Decision Making (2015), Hamburg, Germany, 2nd - 7th Aug 2015.
  • Chugh T. (2015) An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems. [PDF]
  • Chugh T, Sindhya K, Hakanen J, Miettinen K. (2015) Handling Computationally Expensive Multiobjective Optimization Problems with Evolutionary Algorithms: A Survey.
  • Chugh T, Sindhya K, Hakanen J, Miettinen K. (2015) An Interactive Simple Indicator-Based Evolutionary Algorithm (I-SIBEA) for Multiobjective Optimization Problems, EVOLUTIONARY MULTI-CRITERION OPTIMIZATION, PT I, volume 9018, pages 277-291, DOI:10.1007/978-3-319-15934-8_19. [PDF]

2014

  • Chugh T. (2014) Handling computationally expensive multi-objective optimization problems using evolutionary algorithms: A survey, n International conference for Mathematical Modeling and Optimization in Mechanics (MMOM) 2014, Jyvaskyla, Finland, 6th - 7th Mar 2014.
  • Mogilicharla A, Chugh T, Majumdar S, Mitra K. (2014) Multi-Objective Optimization of Bulk Vinyl Acetate Polymerization with Branching, MATERIALS AND MANUFACTURING PROCESSES, volume 29, no. 2, pages 210-217, DOI:10.1080/10426914.2013.872271. [PDF]

2013

  • M. A, Chugh T, Mitra K, Majumdar S. (2013) Effect of live radical species in controlled branching of bulk free radical polymerization system: A multi objective evolutionary approach, International Conference on Advances in Chemical Engineering (ACE 2013), Roorkee, India, 22nd - 24th Feb 2013.

2012

  • Chugh T, M. A, Mitra K, Majumdar S. (2012) Optimal process conditions for the controlled branching of free radical polymerization: A case study, Chemcon 2012, Jalandhar, India, 27th - 30th Dec 2012.

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Further information

Students

PhD students

  1. 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.
  2. 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

  1. Taylor, Gabrielle (2023/24, MSc Data Science). Multivariate Time series Correlations and Predictions in CFD (collaboration with Center of Hydraulic Research Czech Republic)
  2. Arthur Finch (2023/24, MSc Data Science). Bayesian inference of wake models in Wind Farm layout optimisation
  3. Daniel Burke (2023/24, MSc Data Science). Bayesian inference of wake models in Wind Farm layout optimisation
  4. Duc Dat Hoang (2023/24, MSc Data Science). (Multi-objective) Optimisation of Network on Chip (collaboration with Souyma J at BITS Pilani Hyderabad, India)
  5. Torntan Chainant (2023/24, MSc Data Science). (Multi-objective) Optimisation of Network on Chip (collaboration with Souyma J at BITS Pilani Hyderabad, India)
  6. 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)
  7. Hao Liu (2023/24, MSc Data Science with AI). Model-based evolutionary multiobjective RL for continuous control
  8. Zhou DingCheng (2022/23, MSc Computer Science, co-supervised with Dr Cyril Morcrette in Maths department). Predicting Cloud Fraction with ML
  9. Chenming Fu (2022/23, MSc Computer Science). Image text quiz using multimodal deep learning
  10. Zhuohang Liu (2022/23, MSc Computer Science). Analysis of user reviews of food delivery apps with NLP
  11. Tejas Rajput (2022/23, MSc Data Science). Optimising Hyperparameters in CNNs using BO
  12. Vishnu (2022/23, MSc Cyber Security). Automated system for real-time cyber threat detection with machine learning
  13. Jiling Zhou (2022/23, MSc Cyber Security). Differential Privacy in DNNs
  14. Ashish Loknath (2022/23, MSc Cyber Security). Encryption and Decryption with Symmetric and Asymmetric Algorithms.
  15. Yogesh (2022/23, MSc Cyber Security). Steganography for hiding data in Images
  16. Alex Evans (2022/23, MSci Computer Science Programme). Multi-objective Bayesian Optimisation.
  17. Dingcheng Zhou (2022/23). Co-supervised with Dr Cyril Morcrette. ML in Climate.
  18. 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?
  19. 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?
  20. Dinesh Sundaravadive (2021/22, co-supervised with Prof Guangtao Fu at the Department of Engineering). Project title: Flood risk prediction using machine learning.
  21. Gengxiao Li (2021/22, co-supervised with Prof Guangtao Fu at the Department of Engineering). Project title: Flood risk prediction using machine learning.
  22. Yixuan Zhang (2021/22, co-supervised with Prof Guangtao Fu at the Department of Engineering). Project title: Flood risk prediction using machine learning.
  23. Jack Page (2021/22). Jack was part of MSc Professional (Degree Apprenticeship) Programme.
  24. Sourav Chakarobarty (2021/22). Sourav was part of MSc Professional (Degree Apprenticeship) Programme.
  25. Bowen Xiao (2021/22): Bowen was part of MSc Professional (Degree Apprenticeship) Programme.
  26. Chriss Finn (2021/22): Bowen was part of MSc Professional (Degree Apprenticeship) Programme.
  27. Joshua Lillis (2021/22): Joshua was part of MSc Professional (Degree Apprenticeship) Programme.
  28. Shahidul Haq (2021/22): Shahidul was part of MSc Professional (Degree Apprenticeship) Programme.
  29. 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
  30. Deepak Saini (2020/21). Project title: Model Predictive Control of Wind Turbines. Deepak is working as a Software Developer at Saggezza-Infostretch
  31. Arif Malik (2020/21). Project title: Arif is working as Senior Python Developer at Bank of America Merrill Lynch
  32. Rusen Alp (2020/21).
  33. Tuli Saha (2020/21). Tuli was part of MSc Professional (Degree Apprenticeship) Programme.
  34. Simon Stride (2020/21). Tuli was part of MSc Professional (Degree Apprenticeship) Programme.
  35. Steven Hester (2020/21). Steven was part of MSc Professional (Degree Apprenticeship) Programme.
  36. Simon Stride (2020/21). Simon part of MSc Professional (Degree Apprenticeship) Programme.
  37. Rui Go (2020/21). Rui was part of MSc Professional (Degree Apprenticeship) Programme.

BSc Project Students

  1. 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)
  2. 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)
  3. Kelsey Holdgate (2023/24). BSc Computer Science. Simulating Human Approach in Solving Rubik's cube
  4. Dimitar Sivrev (2023/24). BSc Computer Science. ML in Time-series Forecasting
  5. Simran Sahota (2023/24). BSc Computer Science. Supervised and Unsupervised ML in Cricket
  6. Will Riddy (2023/24). BSc Data Science. Supervised and Unsupervised ML in Squash
  7. Ruslan Prigarin (2023/24). BSc Computer Science. Game to Mimic Evacuation during Flooding
  8. Zhixuan Cai (2023/24). BSc Computer Science. Optimal location to build wind farms
  9. Joshua Curry (2023/24). BSc Computer Science. ML to simulate tipping points in Climate Change
  10. Ghali Benlghadane (2023/24). BSc Computer Science. Bayesian vs Frequentist Approach in analysing Sports data
  11. Rohit Pawar (2023/24). BSc Data Science. Multi-task Bayesian optimisation
  12. Matt Morris (2023/24). BSc Computer Science. Multi-task Bayesian optimisation for Process Engineering Application
  13. Toby Slump (2023/24). BSc Computer Science. Supervised ML to quantify the effect of cyclones
  14. Montgomery Batt (2022/23) - Spatio-Temporal Modelling
  15. Mobayode Fashanu (2022/23) - Machine learning and AI to support Children with learning disabilities
  16. Elsa Guenole-Harrison (2022/23, with G-Research London now) - Bayesian machine learning.
  17. Tsun Hui (2022/23) - Deep Fake
  18. Tanish Mehta (2022/23) - Sentiment analysis in Cricket
  19. Miles Ress (2022/23) - Spatio-Temporal Modelling
  20. Jack Stallard (2022/23, with Accenture London now) - ML to create Fantasy Football Team 
  21. Georgi Tarashev (2022/23) - Backtracking in DNN
  22. Nguyen Tu (2022/23, with a startup in Hungary now) - Weather Forecasting using Drones
  23. Thomas Bird (2022/23) - Wind farm layout optimisation
  24. Joseph Wilson (2022/23) - Financial management software for student clubs and societies
  25. Tom Boatman (2021/22). Machine Learning and Optimisation in Optimising Wind Farm Layout Design Under Uncertainty.
  26. Benjamin Narbett (2021/22). Machine learning and optimisation to engineering problems
  27. 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.
  28. Habib Zain (2021/22). How the pandemic affected employee attrition, why it’s happening and how to predict it.
  29. Lilian Pintac (2021/22). Project title: Combining Multi-objective Evolutionary Algorithms with Machine Learning Algorithms to Solve Real World Engineering Problems
  30. Ashley Richter (2021/22). Project title: Neural Style Transfer.
  31. Jamie Nottage (2020/21). Project title: Bayesian framework to measure the correlation between traffic and COVID-19 cases
  32. Matthew (2020/21). Project title: Optimisation and Analysis of Neural Networks for AI Gameplay
  33. Nicklas Wenzler (2020/21). Project title: Importance of differential privacy.
  34. Benjamin Trotter: Investigating Trading Strategies via Multi-objective Optimisation

Research Updates

  1. March 2024 - The EvoStar conference paper on Integrating Bayesian and Evolutionary Approaches for Multi-objective Optimisation is now online. 

  2. Feb 2024 - The conference paper on utilising machine learning in Friction stir welding with my Indian collaborators is now online. The paper was a result of Shubham's (first author) undergraduate thesis. 

  3. Feb 2024 - The conference paper on 'Integrating Bayesian and Evolutionary Approaches in Multi-objective Optimisation' with Alex Evans is accepted in the EvoStar Conference. The paper was a result of Alex's master thesis. 

  4. Jan 2024 - I joined 'The COST Action ''Randomised Optimisation Algorithms Research Network (ROAR-NER)''. I am a member of the 'Optimisation under Uncertainty' working group 

  5. Sep 2023 - The conference paper on multi-objective design of experiments with Alex Evans, BSc project student is now published and online.

  6. Aug 2023 - The book chapter on Identifying Correlations in Many-objective Optimisation in now published and online in the Many Criteria Optimisation and Decision Analysis Book (collaboration with A Gasper-Cunha at Minho, Portugal, Andre Deutz at Leiden, Joao Duro at Sheffield, Daniel Oara at Sheffield and Alma Rahat at Swansea).

  7. Aug 2023 -  The article on Treed Gaussian Processes in Multi-objective Optimisation is now published and online in the Evolutionary Computation Journal (collaboration with Atanu Mazumdar at Aalto University, Kaisa Miettinen at Jyvaskyla, Manuel Lopez Ibanez at Manchester and Jussi Hakanen at Silo AI).

  8. March 2023 - The article: Feature-Based Benchmarking of Distance-based Multi/Many Objective Optimisation Problems: A Machine Learning Perspective is now online

  9. Feb 2023 - I am the guest editor of the special issue of the ACM Transactions on Evolutionary Learning and Optimisation (TELO) journal on Data-driven Evolutionary Computation (with Prof Yaochu Jin, Hemant Kumar Singh, Xilu Wang and Alma Rahat)

  10. Feb 2023 - Invited to participate in the workshop on 'Multi-objective Bayesian Optimisation' at the University of Warwick on 27th Feb organised by Prof Juergen Branke and Dr Manuel Lopez-Ibanez

  11. Feb 2023 - Together with Arnaud Liefooghe, Sébastien Verel, Jonathan Fieldsend, Richard Allmendinger and Kaisa Miettinen, I published a paper: 'Feature-Based Benchmarking of Distance-Based Multi/Many-objective Optimisation Problems: A Machine Learning Perspective' in EMO 2023

  12. Nov 2022 - Joined the programme committee of GECCO 2023

  13. Oct 2022 - With Alma Rahat, I will organise a special session on Surrogate-assisted Optimisation in EvoStar, 10-14 April, 2023

  14. Oct 2022 - My BSc student Alex Evans presented our work on Multi-objective Design of Experiments at EA 2022

  15. Oct 2022 - Invited to participate in the workshop on 'Multi-objective Optimisation on a Budget' at Schloss Dagstuhl-Leibniz-Zentrum fur Informatik in Germany on 3-8 Sep 2023

  16. Sep 2022 - Joined the programme committee of EMO 2023

  17. July 2022 - I am appointed as Associate Editor of the Complex and Intelligent Systems journal. 

  18. July 2022 - Together with George De Ath and Alma Rahat, I published 'MBORE: Multi-objective Bayesian Optimisation using Density Ratio Estimation' in GECCO 2022

  19. July 2022 - I published my work on 'Mono-surrogate vs Multi-Surrogate in Multi-objective Bayesian Optimisation' in GECCO 2022

  20. July 2022 - I published my work on 'R-MBO: A multi-surrogate approach for preference incorporation in Multi-objective Bayesian Optimisation' in GECCO 2022

  21. July 2022 -  I and my MSc project student Endi Ymeraj published a conference paper titled 'Wind Farm Layout Optimisation Using Multi-objective Bayesian Optimisation Over Sets' in GECCO 2022

  22. July 2022 - I and my BSc project student Alex Evans sent a paper on Multi-objective Design of Experiments to the Artificial Evolution (EA) Conference 2022 to be held in Exeter, UK

  23. July 2022 - Dr Tomas Kratky from the Center of Hydraulic Research, Czech Republic visited Exeter from 16th - 22nd July

  24. July 2022 - Dr Bohumila Kracmarova from Nitra University Slovakia visited Exeter from 21st - 27th July 

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