Research Group, Computer Science, University of Hull
We are the Big Data Analytics research group (BDA) in the Department of Computer Science and Technology (CST) at the University of Hull.
We collaborate with the Dependable Intelligent Systems (DEIS) research group in CST,
and also work closely with other parts of the university, including the
Viper HPC team, the
Energy and Environment Institute, and the
Aura Centre for Doctoral Training Centre in Offshore Wind Energy and the Environment.
We first came together as a group in 2017 and have since been growing an interdisciplinary research portfolio in artificial intelligence and
data analytics, particularly focusing on research in (deep) machine learning, interactive systems and natural language processing, and increasingly
AI for sustainability and environmental modelling. We have an increasing number of collaborations with partners in academia, industry and the
public sector, generating novel fundamental research, knowledge transfer and impact acceleration projects.
We apply machine learning, mostly deep learning, in all our research projects, due to its ability to learn features from large datasets and identify patterns in disparate, large and noisy datasets. Most of our work on natural language processing and other time-series applications uses LSTM/GRU or transformer models (e.g. for sentiment analysis, natural language generation) while other projects in image analysis and sensory output analysis have used CNNs or autoencoders.
Our research in this area focuses on deep learning models that are transparent and interpretable and can explain the rationales behind their actions - this is important in many commercial and real-life applications to increase trust, helps to avoid bias and discrimination in AI models, and makes them generally more accountable.
We are also interested in fast learning systems and investigate topics in transfer learning, divide-and-conquer approaches to learning and efficiency. See our deep learning publications for details.
Natural language processing (NLP) refers to approaches that analyse, generate and process natural language automatically using computational techniques and algorithms, mostly based on machine learning. Our strengths lie in natural language generation, that is the automatic generation of language from non-linguistic data sources, such as data-to-text generation, (spoken) dialogue systems, i.e. systems that engage in conversations with users to solve problems or provide information, sentiment analysis in text and social media and text classification and analysis.
We are also interested in social media analysis, including projects on sentiment analysis and mental health based on linguistic profiling, flood forecasting and emergency situation assessment from social media and topics in digital conservation, such as public opinion mining and the monitoring of species. See our natural language processing publications for details.
Interactive systems can interact with their users in different ways, including text, speech, haptic or other multimodal input. A common distinction is between task-oriented interactive systems that target a particular domain, e.g. answering user queries on restaurant or tourist attractions in the local area, and open-domain systems who attempt to answer any question, e.g. using information retrieval methods from the web. Most personal assistant fall into the latter category. Finally, chatbots have no purpose of informing but rather aim to entertain users by engaging in casual chat.
Our group is interested in human-like behaviour of interactive systems, e.g. the incremental planning of utterances and the analysis of linguistic features in different conversational contexts. Most recently we have worked on interactive decision support systems for various real-life applications, most notably in the wind domain, where we use interaction as a way to provide easy and intuitive access to the inner workings of wind turbines to support operations and maintenance. See our interactive systems publications for details.
We are applying AI and machine learning techniques to help solve problems in sustainability and environmental research. We are part of the EPSRC Aura CDT on Offshore Wind and the Environment, and we have a strong interest in the digitalisation of offshore wind. As part of this, we use AI to improve operations and maintenance of wind turbines to improve their reliability and usability as an alternative to fossil fuel-based energy sources. We achieve this through detailed and explainable fault forecasting and the automatic generation of maintenance strategies from expert knowledge sources.
Other research includes the forecasting of floods from high-frequency and social media data sources and the monitoring of water quality in the North Sea from sensory data and satellite images to achieve longer-term forecasting of the effects of human activity or environmental factors on water quality. We are currently growing our research on using AI towards the conservation of species. See our sustainability publications for details.
This is an impact acceleration project that enables rapid analysis of text documents from interactive feedback and sparse human labels, by leveraging our previous research in NLP and language models.
HEIF, 2022-23 (PI)
This project proposes an industry-compatible step-change advance in accumulated fatigue assessment via novel integration of physical modelling and machine learning.
With the EEI and University of Sheffield.
EPSRC Supergen ORE, 2021-22 (PI)
Read moreWe develop novel algorithms to improve stability testing of new product formulations and accelerate their launch from initial conception and design through to testing and manufacturing. This will accelerate product improvement and enhance Reckitt's capacity to react to customer feedback and product reviews.
Innovate UK, 2021-23 (PI)
We are part of the EPSRC Aura CDT on Offshore Wind and the Environment and research theme lead for "Big data, sensors and digitalisation for the offshore environment".
With partner institutions Sheffield, Durham and Newcastle.
EPSRC, NERC 2019-27 (CI)
See DetailsWe apply research in data analytics, NLP and AI to analyse company documents, identify patterns, extract information and generate insights towards more effective workflows and informed decision support.
Innovate UK, 2020-22 (PI)
Research to address the openness, uncertainty, variability, and interplay of safety and security in multi-robot systems.
See DetailsEU H2020, 2021-24 (CI)
We research hierarchical decomposition approaches for fast learning in natural language generation systems that can produce high-quality outputs from sparse and unseen knowledge graphs.
Diffbot (industry grant), 2017-19 (PI)
The key aim of this project is to semi-automate the analysis of legal documents with an intelligent software that can extract prominent themes from a document, identify likely areas for legal attention and generate a list of suggested amendments to the document..
With legal firm rradar.
HEIF, 2019 (PI)
I am a Senior Lecturer in Computer Science at the University of Hull, Yorkshire, UK, where I lead the Big Data Analytics Research group.
I am also currently Director of Research for Computer Science and Technology and Aura CDT Theme lead for "Big data, sensors and digitalisation for the offshore environment".
Before coming to Hull, I was a Research Fellow in the The Interaction Lab at Heriot-Watt University, Edinburgh. I have a PhD in Computational Linguistics from the University of Bremen, Germany.
My research interests lie at the intersection of machine learning and natural language processing (NLP), particularly in the areas of data-to-text and natural language generation (NLG), interactive systems, assistive technologies, domain transfer and adaptability for data analytics in a wider AI context. I have spent the last few years working with neural networks as a primary algorithm family but have previously worked with graphical models, clustering and reinforcement learning. Most recently I have become interested in applying AI and NLP in "useful" contexts such as mental health and the environment, particularly towards sustainability. I am interested in the digitalisation of the offshore wind industry to make wind turbines more reliable. I am also interested in the effects of human activity on water quality and the forecasting of natural events such as floods. When I have time I do some research in digital conservation using AI and text classification.
Joyjit is currently a postdoctoral researcher and KTP Associate with the University of Hull and Reckitt. He is developing novel AI-based
techniques to automate certain stages in consumer care product testing. Joyjit holds a PhD from the University of Hull (2021).
His PhD focused on researching in the area of tackling climate change with AI, by helping make wind energy sources more reliable, through
explainable and intelligent decision support in their operations & maintenance. During his PhD., he closely collaborated
with leading wind farm operators and research organisations as a part of the Aura Innovation Centre, UK’s PhD. cluster. He is a
Chartered Engineer, MIET, MIEEE, AMIE, Jr. Member of Isaac Newton Institute for Mathematical Sciences, Cambridge & Life Member of
Indian Science Congress Association. He is a certified Professional Scrum Master (PSM-1) with a sound understanding of the
industry. Joyjit also holds a Postgraduate Diploma in Research Training (Hull, UK), Professional Certificate in AI (Oxford, UK),
and Bachelors in Electronics & Communication Engg. (Gold Medalist-Amity University, India). He has published an array of papers
in Computer Science & Engineering (including in leading A*/A ranked AI conferences/workshops such as NeurIPS, KDD, IJCNN, ECAI
etc., and reputed journals by Wiley, IOP etc.). As a global researcher, he has co-authored papers & filed patents with reputed
academicians from across Europe, North America and Asia in AI, NLG & Signal Processing, and delivered talks at leading research
institutions globally (such as Carnegie Mellon University, ETH Zurich etc.). Joyjit was also a Visiting Researcher at Tamkang
University, Taiwan on a government funded research project. Joyjit regularly serves on the programme committee/as reviewer for
leading international conferences/workshops (such as ICLR, NeurIPS etc.) and high-impact journals.
Joyjit is the recipient of several honours & awards including PhD. Scholarship (Hull, UK), Employability Award for Postgraduate
Researchers (Hull, UK), funding towards conference presentations from reputed international organisations such as IEEE CIS,
Microsoft Research etc., Scholarship for the Global Impact Challenge 2020 (Nudge, Netherlands), Young Researcher Award
(IEEE UK & Ireland Section), Gold Medal and Scholarship (Amity University, India), Alumni Achiever Award for Outstanding
Contribution in Education (Amity University, India) and several other awards, certifications and honours from governments,
industry and academia. His research interests span Deep Learning, Natural Language Generation, Data Analytics, Knowledge Graphs,
Causal Inference and Time-Series Analysis.
See Joyjit's blog articles on The Good AIfor further background on his thesis and the use of AI in renewable energy.
I am a researcher working in Natural Language Processing and Big Data Systems. Over the last five years, I have worked as
a full time researcher on several topics related to Natural Language Understanding and Generation, Deep Learning, Big Data
Analysis and Text Mining of scientific documents.
Bikash is currently an KTP Associate with Spencer Ltd and is applying modern deep learning techniques to text analysis and document classification to optimise Spencer's workflows and productivity. Bikash holds a PhD from the Université de Lorraine in France (2015).
Bobby is a coastal geomorphologist interested in the physical processes influencing coastal dynamics and delta morphodynamics.
Research projects incorporate: coastal vegetation, sediment fluxes, and hydrodynamics. His current primary research project
investigates the role of seagrass on hydrodynamics and wave attenuation via experimental flume research,
validated by field measurements as part of international collaboration within the Hydralab+ protect. A range of
interdisciplinary data collection techniques are applied to the research in order to quantify complex interactions
and non-linear processes associated with vegetation, wave dynamics and sedimentation.
Bobby is a member of the Energy and Environment Institute and a postdoctoral researcher on our EPSRC Supergen ORE grant, working on hybrid methods for fatigue forecasting in wind turbine monopiles, bridging physical and machine learning methods.
The aim of my PhD project is to investigate how different combined stressors act in the environment, with particular attention to biological responses in mussels.
I obtained an MSc in Marine Biology at Marche Polytechnic University (Ancona, Italy), working on a project concerning the modulatory effect of climate change (global warming and ocean acidification) and heavy metals exposure on biological responses of the Mediterranean mussel Mytilus galloprovincialis.
The first part of my PhD involves the exposure of the blue mussel Mytilus edulis to several stress compounds. At the moment, I’m studying how different temperatures and phthalate exposure can affect biological responses of blue mussels. Finally, the second part of my project will involve data analysis: at the end of my PhD, I would like to have collected enough data to use artificial intelligence and machine learning for simulating future climate conditions and consequence for mussel populations.
I Licentiated in Nuclear Medicine in 2006 from Escola Superior de Tecnologia da Saúde de Lisboa – Instituto Politécnico de Lisboa (ESTeSL-IPL). Following, I finnished my MSc in Biophysics and Medical Physics in 2009, from Instituto de Biofísica e Engenharia Biomédica, da Faculdade de Ciências da Universidade de Lisboa (IBEB-FCUL. Concluded one Biomedical Engineering Specialization in 2014 from Faculdade de Ciências e Tecnologias da Universidade de Coimbra (FCTUC). I am presently student PhD Student in University of Hull.
From September of 2008 to September of 2018, I was full-time Assistant Lecturer in ESTeSL-IPL. Lecturing in the degrees of Nuclear Medicine and Medical Imaging and RadiotherapyDuring this time, I collected some experience of lecturing in different Institutions abroad under Erasmus Program in 2010 (Karolinska Institutet – Sweden); 2012 and 2013 in NuPHiCos (Medical University of Plovdiv – Bulgaria); 2015 (Institute Paul Lambin – Brussels). And From 2012 to 2018 I coordinate the entrepreneurship Program of ESTeSL-IPL.
I collaborated with some research teams and projects and have being member of Member of the Research Groups GI-MOSM and GIRES. I have collaborated in some funded research projects by Instituto Politécnico de Lisboa, with the fellowship (IDI&CA) do IPL – 2016.
As hobbies I am also a writer, blogger and volunteer.
We are proud that our very own Joyjit has been named in Forbes 30 under 30 Europe this year under the Manufacturing and Industry category - people that create the products, methods and materials of tomorrow! Congrats Joyjit, well deserved!
We're part of the Faculty's new Centre of Excellence for Data Science, Artificial Intelligence and Modelling (DAIM). You can join us a taught MSc student, PhD student, or as a new member of academic staff.
Nina is extremely excited to have received the Inspired in Hull Award for "Excellence in Supervision". What an honour seen the amazing colleagues that were nominated, having a brilliant cohort of PhD students like our BDA bunch is a real advantage!
We're thrilled to be hosting a Social session at ICRL 2022 - featuring a panel discussion with a set of experts from the wind and renewables sector, branching across academia and the industry. We hope to explore the opportunities and risks of AI in the transition towards Net Zero. See our dedicated page here.
Read our latest Conversation article! We discuss the carbon footprint of modern AI and how it contributes to furthering the divide between developed and developing countries.
Our (first) NERC discipline hopping Hackathon in AI for Sustainability took place w/c 28 March, jointly organised by Computer Science and the Energy and Environment Institute. We spotten hedges from the air, predicted the structural health of wind turbine monopiles, and predicted floods from social media. See our hackathon page here.
Congratulations to Bobby Houseago for winning the Early Career Researcher Poster Prize at the Supergen Annual Assembly this year for his poster on rapid fatigue assessment in offshore wind farms. Yay!
Thanks all who made it to our annual sparkly Christmas research workshop to present your work, discuss ideas, and eat some cake... Looking forward to next year!
We're massively proud of Joyjit who got selected for a Green Talents Award from amongst 25 researchers from around the globe. The German Ministry of Education and Research awards these prestigious titles + a fully funded research stay in Germany to young people that have made an outstanding contribution to research in sustainability.
The University are part of an amazing initiative to create a hedgehog-friendly campus, see here. This involves raising awareness of hedgehogs and their habitats, creating safe spaces, including bug hotels and hedgehog shelters, and keeping our campus clean and tidy. We're very excited about this!
Congratulations to Dr Joyjit Chatterjee, who has successfully passed his viva, completing his PhD on Explainable AI for O&M of Wind Turbines, see here. Well done Joyjit - and we're excited that you're staying with us in a postdoctoral role.
We won an EPSRC Supergen ORE grant with Agota Mockute at the EEI and Lizzy Cross from Sheffield and a group of strong industry partners. We'll be predicting fatigue levels of wind turbines using deep learning and physical modelling. See details here.
Congratulations to Joyjit for completing the Nudge Global Impact Challenge that selects young research leaders to develop their own sustainability research plans. See Joyjit's promotional video pitching his PhD project here.
Congratulations to Dr Annika Schoene, one of our founding members, who has successfully passed her viva and is leaving us to take up a postdoctoral position at the University of Manchester. Keep in touch, Annika!
We are really excited to be working with Reckitt on a 2-year KTP project to develop novel AI techniques to improve stability testing and new product development, and accelerate product development from design over testing to manufacturing. What an amazing opportunity!
Joyjit and Annika went to NeurIPS-2019 in Vancouver to present their papers Natural Language Generation for Operations and Maintenance in Wind Turbines and Dilated LSTM with ranked units for classification of suicide notes. Well done!
Annika went to Hong Kong to present her paper Dilated LSTM with attention for Classification of suicide notes at the LOUHI workshop at EMNLP-2019. See here.
Joyjit was part of a Uni Hull team to enter the Offshore Wind Hackathon in Glasgow, applying deep learning to predict the power availability in wind farms.
We are looking forward to working with the Spencer Group on a new Innovate UK-funded Knowledge Transfer Partnership (KTP) to integrate artificial intelligence and natural language processing into corporate workflows. Job advert to follow shortly.
We are part of Hull's new EPSRC and NERC-funded CDT in Offshore Wind and the Environment together with partners Durham, Newcastle and Sheffield. See here for website and PhD student recruitment.
Joyjit presented some early PhD work at the Northern Lights Deep Learning Workshop in Tromsø - doing some networking and seeing the Northern Lights. See his presentation and talk here.
We are hosting a 2-day GPU and CUDA programming course right after the Deep Learning Winter School 2019. The aim is to gain an understanding of GPU hardware and a competence in CUDA GPU programming for scientific applications, with a particular focus on deep learning. See here for details and registration.
On 7th December the Big Data Analytics Research group gathered for its annual Poster Workshop and Christmas Lunch.
Joyjit spent some time with the ORE Catapult in Glasgow last month. Read about this visit.
We're excited about our upcoming Christmas Workshop and Lunch on 7 Dec. See our flyer.
We are organising the 2nd Deep Learning Winter School on 22-23 January 2019 as a hands-on introduction to the theory and practice of deep learning, including talks from leading researchers in the field a tour of Viper See here for details and registration.
The new Aura wind energy PhD cluster met for a kick-off meeting with the 4 new students, including Joyjit from the Big Data Analytics group. Read Joyjit's report.
We're recruiting for a post-doctoral research assistant to work on an EPSRC-funded project on Transparent AI. See here. Deadline 15 Nov 2018.
We're recruiting a PhD student on a 3-year fully-funded scholarship on data analytics (particularly deep learning) for water sensing. See here. Deadline 23 Jan 2019.
We're recruiting a PhD student on a 3-year fully-funded scholarship on data analytics from IoT devices for modelling flood risks. See here. Deadline 23 Jan 2019.
Once the start date and funding for my PhD was confirmed, I started searching the internet for what makes a successful PhD student in Computer Science. ...
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David Benoit from Chemistry and Nina Dethlefs gave a talk at the British Science Festival on "Let the AI In".
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Following up on our talk at the British Science Festival, we published an article in The Conversation --- AI: there’s a reason it’s so bad at conversation.
Alex Turner got his EPSRC grant on 'Using Epigenetically-Inspired Connectionist Models to Provide Transparency In The Modelling of Human Visceral Leismaniasis'.
See details.
Today we had "big data" cake to welcome 3 new team members who will be working on deep learning and computational biology.
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After having my paper accepted for the 2018 WISDOM workshop at KDD, I felt both nervous but excited. ...
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Robert Blackburn Building 3rd floor University of Hull Cottingham Road HU6 7RX, Hull, UK
