糖心原创

School of Computer Science
 

Grazziela Figueredo

Associate Professor in Health Data Science, Faculty of Medicine & Health Sciences

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Teaching Summary

Previous Teaching

Module co-convenor for COMP4103/G54BIG: Big Data Learning and Technologies

Target students: Part II and III undergraduate students and MSc students in the School of Computer Science. This module is part of the AI, Modelling and Optimisation theme and the Operating systems and Networks theme in CS. Available to JYA/Erasmus students.

Summary of Content: "Big Data" involves data whose volume, diversity and complexity requires new technologies, algorithms and analyses to extract valuable knowledge, which go beyond the normal processing capabilities of a single computer. The field of Big Data has many different faces such as databases, security and privacy, visualisation, computational infrastructure or data analytics/mining.

This module provides the following concepts:

1. Introduction to Big data

3. Big Data frameworks and how to deal with big data

4. Machine learning library of Apache Spark (MLlib) to understand how some machine learning algorithms (e.g. Decision Trees, Random Forests, k-means) can be deployed at a scale.

Management and Professional Practice is an Aerospace Engineering

I am responsible for delivering the big data topic, where I introduce basic concepts of data science and machine learning applied to aerospace, focussing on the research case studies I work on in the area.

Research, knowledge transfer and training interests:

Big Data

Best practices in Data Science

Machine Learning

Active Learning

Meta-learning

Bio-inspired computation

MLOps

Research Summary

The focus of my research is the development and application of techniques for systems simulation and intelligent data analysis. In particular, I am interested in how environmental changes, trend… read more

Recent Publications

  • FIGUEREDO, GRAZZIELA P, TRIGUERO, ISAAC, MESGARPOUR, MOHAMMAD, GUERRA, ALEXANDRE M, GARIBALDI, JONATHAN M and JOHN, ROBERT I, 2017. IEEE Transactions on Emerging Topics in Computational Intelligence. 1(4), 248-258
  • SIEBERS, PEER-OLAF, FIGUEREDO, GRAZZIELA P, HIRONO, MIWA and SKATOVA, ANYA, 2017. Developing Agent-Based Simulation Models for Social Systems Engineering Studies Social Systems Engineering: The Design of Complexity. 133-156
  • TRIGUERO, ISAAC, FIGUEREDO, GRAZZIELA P, MESGARPOUR, MOHAMMAD, GARIBALDI, JONATHAN M and JOHN, ROBERT I, 2017. Vehicle incident hot spots identification: An approach for big data In: Trustcom/BigDataSE/ICESS, 2017 IEEE. 901-908
  • ALBANGHALI, MA, FIGUEREDO, GP, ALESKANDARANY, MA, GREEN, AR, RAKHA, EA, NOLAN, C, DIEZ-RODRIGUEZ, M, GARIBALDI, JM, ELLIS, IO and CHEUNG, KL, 2017. Biological subtyping and response to primary endocrine therapy in older women with early operable primary breast cancer-a study based on core needle biopsy In: FUTURE ONCOLOGY. 17-17

Current Research

The focus of my research is the development and application of techniques for systems simulation and intelligent data analysis. In particular, I am interested in how environmental changes, trend setters and temporal phenomena affect data and the outcome of AI inference in real-world scenarios. I am mainly interested in sensor and mobility big data problems, where aspects such as health diagnostics, anomalies, traffic, hot spots and behaviour identification can be assisted or interpreted by machine learning.

More recently, I have been working on machine learning, active learning and other computational intelligence methods for (bio) materials discovery. The objective of this research is to create close-loop systems that feed high throughput screening experimental data into intelligent systems. Data is analysed to understand further data needs, material properties and how those properties modulate a certain endpoint. The extracted information is subsequently used to automatically generate new improved designs. This research is conducted in collaboration of colleagues from the school of Pharmacy, the Biodiscovery Institute and the School of Engineering and is mostly funded by EPSRC.

RESEARCH PROJECTS:

As Primary Investigator

  • (2021-2023) KTP104213 Innovate UK/Gendius (拢238,841.89) (PI - Project Lead)
  • (2019-2022) KTP011710: Innovate UK/ Gleeds (Innovate UK 拢240k) (PI - Academic Supervisor)
  • (2019) An Intelligent Tool to Optimise Early Stage Cancer Screening - A feasibility study. Research Priority Funding from the 糖心原创.( 拢28,330.28) (PI)

As Co-Investigator:

  • (2025-2027) TREvolution - DARE UK Grant Ref MC_PC_24038 (拢4,940,092.20)
  • (2023-2027) Designing Biomaterials for translation-ready medical devices EPSRC EP/X001156/1 (Co-I 300K for my WP)
  • (2022-2025) Maternal venous return from the placenta and the effect of placental and uterine contractions as potential markers of stillbirth risk (Funded by the Welcome Leap 拢4M) (Co-I 450K for my WP)
  • (2022) Untangling the mechanistic links between heart and brain health in older populations: An AI assisted toolkit for assessing dementia risk - MR/X005437/1 (拢130,462.03) (Co-I 拢37,700.92 for my WP)
  • (2022) - TRE4C: Creating a blueprint for a Trusted Research Environment For Cities (UoN internal funding)
  • (2021-2022) The association between drugs/vaccines commonly prescribed to older people and bullous pemphigoid: a UK population-based study. (拢192,113.46) - NIHR202781 (Co-I)
  • (2020-2021) Informing policy to mitigate risks of COV19 to the mental and physical health of 糖心原创 students - Behavioural Arm (拢207,817.24) - UKRI (Co-I)
  • (2020-2021) Using Artificial Intelligence to predict need for therapy in LAM (The LAM Foundation 79k) (Co-I)
  • (2020-2021) Coordinating COVID-19 asymptomatic testing programmes in university settings: providing insight on acquired immunity across the student population. (UKRI 312K) (Co-I)
  • (2020) - AECOM/Microlise Pavement Data Analysis (Services Rendered to Highways England/AECOM 拢60K) (Co-I)
  • (2019-2020) Confidence Associated with Metagenomic Detection of Threat Agents (Funded by DSTL 拢136k) (Co-I)
  • (2019) Nottingham Smart Cities - Open Transport Data (Funded by Nottingham City Council) (拢31k) (Co-I)
  • (2015) Creating an Artificial Hotspot Laboratory Prototype for Investigating HGV Hotspot Incidences - Funded internally by D3 RPA Discipline Bridging Fund + ADAC (拢11.022) (CO-I)

As Researcher/Data Scientist/Collaborator:

  • (2018-2020) EPSRC Next Generation Biomaterials Discovery Programme Grant (EP/N006615/1 - 拢5M) (Senior Data Scientist)
  • (2017-2018) EU OPTMISED (H2020-FoF-2015 grant 680515) - (RA)
  • (2016-present) INNOVATIVE (Aerospace Engineering - Marie Curie ITN) (Academic partner - PhD supervisor)
  • (2016) ADAM - Anthropomorphic Design through Advanced Manufacturing (EPSRC) (RA)
  • (2016) Biological subtyping and response to primary endocrine therapy in older women with early operable primary breast cancer-a study based on core needle biopsy (Data Analyst)
  • (2015-2016) Value Enhancement for Data from Assets & Transactions (Innovate UK 拢 拢359,000) (RA)
  • FIGUEREDO, GRAZZIELA P, TRIGUERO, ISAAC, MESGARPOUR, MOHAMMAD, GUERRA, ALEXANDRE M, GARIBALDI, JONATHAN M and JOHN, ROBERT I, 2017. IEEE Transactions on Emerging Topics in Computational Intelligence. 1(4), 248-258
  • SIEBERS, PEER-OLAF, FIGUEREDO, GRAZZIELA P, HIRONO, MIWA and SKATOVA, ANYA, 2017. Developing Agent-Based Simulation Models for Social Systems Engineering Studies Social Systems Engineering: The Design of Complexity. 133-156
  • TRIGUERO, ISAAC, FIGUEREDO, GRAZZIELA P, MESGARPOUR, MOHAMMAD, GARIBALDI, JONATHAN M and JOHN, ROBERT I, 2017. Vehicle incident hot spots identification: An approach for big data In: Trustcom/BigDataSE/ICESS, 2017 IEEE. 901-908
  • ALBANGHALI, MA, FIGUEREDO, GP, ALESKANDARANY, MA, GREEN, AR, RAKHA, EA, NOLAN, C, DIEZ-RODRIGUEZ, M, GARIBALDI, JM, ELLIS, IO and CHEUNG, KL, 2017. Biological subtyping and response to primary endocrine therapy in older women with early operable primary breast cancer-a study based on core needle biopsy In: FUTURE ONCOLOGY. 17-17
  • TODD, IAN, NEGM, OLA H, REPS, JENNA, RADFORD, PAUL, FIGUEREDO, GRAZZIELA, MCDERMOTT, ELIZABETH M, DREWE, ELIZABETH, POWELL, RICHARD J, BAINBRIDGE, SUSAN, HAMED, MOHAMED and OTHERS, 2017. Pharmacological research. 125, 188-200
  • SIEBERS, PEER-OLAF, SUSANTY, MEREDITA and FIGUEREDO, GRAZZIELA, 2016. A (More) Formal Approach for Developing Agent-Based Social Simulation Models of Energy Users In: Conference on Social Science Research in Energy. 04
  • FIGUEREDO, G.P., SIEBERS, P.O. and AICKELIN, U., 2015. Juxtaposition of System Dynamics and Agent-Based Simulation for a Case 糖心原创 in Immunosenescence PLoS ONE. (In Press.)
  • FIGUEREDO, GRAZZIELA P., WAGNER, CHRISTIAN, GARIBALDI, JONATHAN M. and AICKELIN, UWE, 2015.
  • FIGUEREDO, GRAZZIELA P, QUINLAN, PHILIP R, MESGARPOUR, MOHAMMAD, GARIBALDI, JONATHAN M and JOHN, ROBERT I, 2015. In: 2015 IEEE 18th International Conference on Intelligent Transportation Systems. 2001-2006
  • MARTI, E, WANG, X, JAMBARI, NN, RHYNER, C, OLZHAUSEN, J, P脡REZ-BAREA, JJ, FIGUEREDO, GP and ALCOCER, MJC, 2015. Veterinary immunology and immunopathology. 167(3), 171-177
  • FIGUEREDO, GRAZZIELA P, SIEBERS, PEER-OLAF, OWEN, MARKUS R, REPS, JENNA and AICKELIN, UWE, 2014. PloS ONE. 9(4), e95150
  • FIGUEREDO, GRAZZIELA P., JOSHI, TANVI V., OSBORNE, JAMES M., BYRNE, HELEN M. and OWEN, MARKUS R., 2013. INTERFACE FOCUS. 3(2),
  • GRAZZIELA P. FIGUEREDO, PEER-OLAF SIEBERS, DOUGLAS A. AUGUSTO AND HELIO J. C. BARBOSA and UWE AICKELIN, 2013. In: The 12th European Conference on Artificial Life (ECAL 2013). 854-855
  • FIGUEREDO, GRAZZIELA PATROCINIO, BERNARDINO, HEDER SOARES and BARBOSA, HELIO JOS脡 CORR^EA, 2013. Introdu莽茫o aos sistemos imunol贸gicos artificiais Meta-heur铆sticas em pesquisa operacional. 113-128
  • PASSINI, MARIA LUIZA C, EST脡BANEZ, KATIUSCA B, FIGUEREDO, GRAZZIELA P and EBECKEN, NELSON FF, 2013. A strategy for training set selection in text classification problems International Journal of Advanced Computer Science & Applications. 4(6),
  • GRAZZIELA P. FIGUEREDO, TANVI V. JOSHI, JAMES M. OSBORNE, HELEN M. BYRNE and MARKUS R. OWEN, 2013. On-Lattice Agent-based Simulation of Populations of Cells within the Open-Source Chaste Framework Interface Focus.
  • GRAZZIELA P. FIGUEREDO, NELSON F. F. EBECKEN, DOUGLAS A. AUGUSTO and HELIO J. C. BARBOSA, 2012. An Immune-inspired Instance Selection Mechanism for Supervised Classification Memetic Computing.
  • GRAZZIELA P. FIGUEREDO, PEER-OLAF SIEBERS and UWE AICKELIN, 2012. Investigating Mathematical Models of Immuno-Interactions with Early-Stage Cancer under an Agent-Based Modelling Perspective BMC Bioinformatics. (In Press.)
  • GRAZZIELA P. FIGUEREDO, HEDER S. BERNARDINO and HELIO J. C. BARBOSA, 2012. Introducao aos Sistemas Imunologicos Artificiais. In: Metaheuristicas em Pesquisa Operacional (In Press.)
  • GRAZZIELA P. FIGUEREDO, PEER-OLAF SIEBERS, UWE AICKELIN and STEPHANIE FOAN, 2012. A Beginners Guide to Systems Simulation in Immunology. In: Proceedings of the 11th Int. Conf. on Artificial Immune Systems 57-71
  • FIGUEREDO, GRAZZIELA P, 2012. Translating simulation approaches for immunology
  • GRAZZIELA P. FIGUEREDO, UWE AICKELIN and PEER-OLAF SIEBERS, 2011. Systems Dynamics or Agent-Based Modelling for Immune Simulation? In: Proceedings of the International Conference on Artificial Immune Systems. 81-94
  • GRAZZIELA P. FIGUEREDO and UWE AICKELIN, 2011. Comparing System Dynamics and Agent-Based Simulation for Tumour Growth and its Interactions with Effector Cells In: Proceedings of the International Summer Computer Simulation Conference 2011. 15-22
  • GRAZZIELA P. FIGUEREDO and UWE AICKELIN, 2010. Investigating Immune System Aging: System Dynamics and Agent-Based Modelling In: Proceedings of the Summer Computer Simulation Conference 2010. 174-181
  • GRAZZIELA P. FIGUEREDO and UWE AICKELIN, 2010. Defining a Simulation Strategy for Cancer Immunocompetence In: Proceedings of the 9th International Conference on Artificial Immune Systems (ICARIS 2010). 4-17
  • GRAZZIELA P. FIGUEREDO, UWE AICKELIN and AMANDA WHITBROOK, 2009. System Dynamics Modelling of the Processes Involving the Maintenance of the Naive T Cell Repertoire In: Proceedings of the 9th workshop on computational intelligence (UKCI), Nottingham, UK',.
  • GRAZZIELA P. FIGUEREDO, NELSON F. F. EBECKEN and HELIO J. C. BARBOSA, 2009. An immune-inspired sampling technique for data selection In: The XXX CILAMCE.
  • GRAZZIELA P. FIGUEREDO, LUIS A. VIDAL DE CARVALHO, HELIO J. C. BARBOSA and NELSON F. F. EBECKEN, 2008. Evolutionary Intelligence I.
  • GRAZZIELA P. FIGUEREDO, NELSON F. F. EBECKEN and HELIO J. C. BARBOSA, 2007. The SUPRAIC Algorithm: A Suppression Immune Based Mechanism to Find a Representative Training Set in Data Classification Tasks In: ICARIS. 59-70
  • GRAZZIELA P. FIGUEREDO, LUIS A. V. DE CARVALHO and NELSON F. F. EBECKEN, 2006. Using Genetic Algorithms to 糖心原创 the Evolution of Paratopes and Antibodies in Artificial Immune Systems In: XXVII Iberian Latin American Congress on Computational Methods in Engineering, Belem - PA.
  • GRAZZIELA P. FIGUEREDO, LUIS A. V. DE CARVALHO and HELIO J. C. BARBOSA, 2005. Coevolutionary Genetic Algorithms to Simulate the Immune System's Gene Libraries Evolution In: Advances in Natural Computation: First International Conference, Lecture Notes in Computer Science, Changsha - China. 941-944

School of Computer Science

糖心原创
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