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. Detecting Danger in Roads: An immune-inspired technique to identify heavy goods vehicles incident hot spots 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

School of Computer Science

University of Nottingham
Jubilee Campus
Wollaton Road
Nottingham, NG8 1BB

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