Short Summary
Pedro Furtado is Professor at University of Coimbra UC, Portugal, teaching Computer and Biomedical Engineering. He has more than 25 years experience in both teaching, doing research and supervising industry projects. He has a broad interest in computer science subjects, with the main focus being on data analysis, bigdata, pattern recognition and data management. Currently, Pedro focuses most of his research efforts in biomedical image analysis, pattern recognition and bigdata. Pedro has more than 200 papers published in international conferences and journals, books published and several research collaborations with both industry and academia. In the last years, Pedro has also spent time as visiting scholar in some of the most prestigious universities in the world, and collaborating with non-profit institutions. Pedro holds a PhD in Computer Engineering from U. Coimbra (UC) (2000) and an MBA from Universidade Catolica Portuguesa (UCP) (2004).
https://orcid.org/0000-0001-6054-637X
My Publications in Scopus
My Publications in dblp
My Publications in Google Scholar
Anouncements
I am proud to be chairing IWPR 2021, as I also did in recent years.I am also proud to be general chair of International Conference on Biomedical Engineering and Applications (ICBEA)
University of Coimbra
University of Coimbra is one of the most prestigeous universities in Portugal, founded in 1290 and the main university in Portugal for some centuries. It's courses and research are top quality by Portugal standards, in both Medicine, Sciences, Technology and Law.Research Summary
I do research and teach in data management and data analysis in general. Currently, my main research topic is analysis of medical images using deep learning and machine learning mechanisms. I also work on applying machine learning and time series algorithms to analysis of data, mostly in the health domain. I have also been doing research in many other issues related to data management and analysis for a long time. The main subjects where I worked were:- Bigdata, Realtime, Scalability, Performance, QoS of Software Systems, Databases and Data Warehouses
- Data processing in Parallel, Distributed and Cloud
- Internet-of-Things, Assistive technologies for healthcare, elderly and special needs
Recent research prototypes ...
The following are specific recent research prototypes. The puplications where the results are shown are listed after the list of prototypes:- SW for Object-based detection of Breast Cancer for mammarian tissue wholeslides (OBI) = individualizes tissues elements (objects) (e.g. cells, vacuoles), obtains statistical characteristics of each object and uses a classifier for breast cancer based on those statistics
- SW for Variability-based detection of breast cancer from mammarian tissue wholeslides
- Improved deep-learning segmentation of Eye Fundus Images:
- SW for Improved deep learning segmentation of abdominal organs from MRI and CT
- SW for SIR-based COVID time-series prediction and what-if analysis
- SmartGuia assistive technologies: prototype of system to guide blind people indoors: SmartGuia
...and some corresponding publications:
Teaching
I have taught several courses to Biomedical Engineering and Computer Engineering students since I started teaching in 1992. I am the Professor responsible for the courses I give together with colleagues or alone, depending on the course. I have taught at all levels, BSc, MSc and PhD. Bright students love my classes, less bright ones sometimes not that much... Here's a short list: Digital systems (1992-1995)Programming Languages (C, C++) (1992-1995)
Microprocessor Systems (1992-1995)
Database Systems (1996-2020)
Advanced Data Management Systems (2003-2020)
Computer Systems (Biomedical Engineering) (2006)
Large Scale Concurrent Systems (2008)
Databases and Data Analysis (Biomedical Engineering, Physics) (2008-2020)
Programming Languages and Algorithms (2008)
Advanced Topics in Data Processing and Analysis (2009-2015)
Object Oriented Programming (2012-2014)
Enterprise Systems Integration (JavaEE) (2020)
Recent Participation in Organization of Scientific Events
I have chaired some conferences, most recently IWPR, also some scientific tracks, e.g. in IEEE SCC. I have also been an active organizer as member of program commitee in the following conferences (only show recent ones...) DOLAP 2021, EDBT 2021, AIME 2021, DATA 2021, ICDIP 2021, ICBBT 2021 CloudCom 2020, DATA 2020, CSE 2020, IWPR 2020, ASPAI' 2020, ANT-2020, ICBBT 2020, SCC 2020, DOLAP 2020, Dawak 2020 ICMLT 2019, IWPR2019, ASPAI' 2019, CloudCom 2019, DOLAP 2019, Dawak 2019, IDEAS '19, DATA '19 IWPR2018, ANT-2018, ISPA 2018, DOLAP 2018, CloudCom 2018, IWPR2018, ICIOT 2018, SCC 2018, DATA '18, Dawak 2018 CloudCom 2017, ISPA 2017, MoBiD 2017, IDEAS '17, Dawak 2017, IWPR 2017, DOLAP 2017, SCC 2017, CloudCom 2017, ANT 2017 ANT 2016, IDEAS '16, CloudCom 2016, ICIOT 2016, MoBiD'16, SCC 2016, Dawak 2016, DATA 2016 IDEAS '15, Big Data 2015, ADBIS 2015, DOLAP 2015, Dawak 2015, SCC 2015, MoBiD 2105, SAC 2015. MoBiD 2014,DSS 2014, SERVICES 2014, Dawak 2014, MEDI 2014, BigData 2014, SCC 2014, NBIS 2014, IDEAS '14, ADBIS 2014;Courses, Slides and Tutorials
Keynote in IWPR 2018
Keynote speech presentation where I explain most interesting research issues on Medical Imaging that I have been dealing with, including food recognition, breast cancer detection, benchmarking classification and segmentation in medical imaging, segmentation of eye fundus images and classification of diabetic retinopathy.Keynote in IWPR 2018
Medical Imaging 2019:Objects Characterization to Detect Degree of Malignancy in Breast Cancer Histopathology
This is a work in which I have created an approach bassed on automatically acquiring characteristics of different tissue elements (cells, vacuoles, interstice, etc) to detect changes that denote cancerous tissue. I then use this to improve the quality of detection of cancer degree. The prototype software that was developed to do this is still evolving today and we will apply it to that and other detection issues in medical imaging in the future.Medical Imaging 2019
Related publication:
| [1] | Pedro Furtado. Objects characterization-based approach to enhance detection of degree of malignancy in breast cancer histopathology. In Elsa D. Angelini and Bennett A. Landman, editors, Medical Imaging 2019: Image Processing, San Diego, California, United States, 16-21 February 2019, volume 10949 of SPIE Proceedings, page 109491R. SPIE, 2019. [ bib | DOI | http ] |
ICBBT 2020:Testing Deep Segmentation of Computer Tomography scans
This was my presentation at ICBBT2020 on segmentation of CT scans of the liver, it won prize for best presentation...ICBBT2020 CT of Liver: best presentation
Related publication:
| [4] | Pedro Furtado. Testing deep segmentation of computer tomography scans. In Proceedings of the 2020 12th International Conference on Bioinformatics and Biomedical Technology, pages 106--111, 2020. [ bib ] |
ICDIP 2020:Magnetic Resonance Sequences: Experimental Assessment of Achievements and Limitations
This was my presentation at ICDIP 2020 on MRI of abdominal organs... it grabbed best presentation and the paper is accepted for publication in Journal of Advances in Information Technology (http://www.jait.us/)ICDIP2020 MRI of Abdominal Organs... best presentation
Medical Imaging 2020:Deep semantic segmentation of diabetic retinopathy lesions: what metrics really tell us
My presentation at MI2020. It calls attention to the problem that segmentation of lesions in DR are most frequently not well evaluated because the metrics used and the comparison approach is not the best one.MI2020 on segmentation of DR lesions
Related publications:
| [1] | Pedro Furtado. Deep semantic segmentation of diabetic retinopathy lesions: what metrics really tell us. In Andrzej Król and Barjor S. Gimi, editors, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, Houston, TX, USA, February 15-20, 2020, volume 11317 of SPIE Proceedings, page 113170O. SPIE, 2020. [ bib | DOI | http ] |
| [2] | Pedro Furtado. Segmentation of diabetic retinopathy lesions by deep learning: Achievements and limitations. In Filipe Soares, Ana L. N. Fred, and Hugo Gamboa, editors, Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 2: BIOIMAGING, Valletta, Malta, February 24-26, 2020, pages 95--101. SCITEPRESS, 2020. [ bib | DOI | http ] |
| [3] | Pedro Furtado. Segmentation of Diabetic Retinopathy Lesions: The Common Fallacy and Evaluation of Real Segmenters In Open Journal of Medical Imaging, accepted fopr publication in 2020. [ http, to appear in... ] |
keynote speech in e-Biss 2016 = keynote tutorial on Big Data Warehouses and Analytics: About Scalability and Realtime
This was my keynote presentation on e-Biss 2016, where I presented the major issues related to processing big qauntities of data, as well as all our previous research on the subject. It is also a useful tutorial on BigData tools.Keynote presentation at e-Biss 2016
More to be added later...
Research Graphically
1. Deep Learning Segmentation and Classification Networks ...
2. Segmentation of abdominal organs ...
3. Segmentationos of diabetic retinopathy eye lesions ...
4. Seizures ...
5. Medical applications ...
6. Automated CHC in Self-Management of Diabetes + Convolution Neural Nets...
7. Segmentation for Accurate Classification/Detection
Research WordCloud
Assistive Technology: SmartGuia
SmartGuia, Assistive Technologies
We propose a system for indoor assisted shopping and navigation for blind people. The proposed system helps the user navigate and find desired or available services and products in buildings. It aims to increase the autonomy of blind people in day-to-day indoor activities. A blind person does not have access to the common visual information. The proposed system consists of a smartphone application which offers guided navigation inside public buildings, answering questions, and providing objective information about places, products and services that are available.
Books
