Department of Computer Science
University of Cyprus

caip logoThe 19th International Conference on Computer Analysis of Images and Patterns (CAIP) will be held between 27 September – 01 October 2021.

Due to the COVID-19 global pandemic, CAIP 2021 will be held as a virtual conference. The Organizing Committee would like to thank you for your commitment and support and reassure you that they are dedicated to offering the best possible online experience to attendees.

Extended Paper Submission Deadline - 05 May 2021


Important Dates:

Special Sessions proposal submission
05 May 2021

Special Sessions acceptance notification
10 May 2021

Paper Submission
05 May 2021


Author notification
15 June 2021

Camera-ready paper due
01 July 2021


Early bird registration
31 July 2021


For more information about CAIP 2021, please click here.

IEEE EBMS Grand Challenges Forum

Data science is an emerging discipline that will be instrumental in accelerating healthcare innovation and transforming the healthcare industry to improve the quality and cost of services provided to patients. Data science, broadly defined, includes the tools, techniques, and theoretical underpinnings for enabling machine learning and artificial intelligence (AI) to be applied to large, diverse, complex, longitudinal, and distributed data sets in order to extract useful information and knowledge. Machine learning and AI have already led to significant successes in many health-related fields including medical image classification, segmentation, prediction, and decision making. The field of data science promises to accelerate the applications and successes, specifically by enabling the scaling to “big” and heterogeneous data.
To address the research and translational advances and challenges in healthcare-focused data science, the IEEE EMBS Grand Challenge Forum on Data Science and Engineering in Healthcare will be held on Feb 10-13, 2021. The forum aims to highlight and discuss the challenges and opportunities of Data Science innovations in healthcare, medicine and biology, and how these innovations can be translated into cutting-edge healthcare and biomedical engineering curriculums.
The forum will have the following four symposiums:
  1. Grand Challenges in Data Science and Engineering in Healthcare: Medical Imaging
  2. Grand Challenges in Data Science and Engineering in Healthcare: Precision Medicine
  3. Grand Challenges in Data Science and Engineering in Healthcare: Digital Healthcare
  4. Grand Challenges in Data Science and Engineering in Healthcare: Brain and Neural Systems

You can find the full Symposium's program here.

We believe that the IEEE EMBS Forum will provide a unique platform for scientists, engineers, and students to focus on translational data science and engineering research and healthcare innovations, as well as the need for a paradigm shift in engineering and science education and their impact on healthcare and economic growth.
Due to the long-term impact of the COVID-19 pandemic, the organizing committee has decided to offer the Forum in a virtual format only to ensure a safe environment and to make participation possible for more people. We hope you would join us. 
Please note registration is free and required to attend the IEEE EMBS Grand Challenges Forum on Data Science:


13th Cyprus Workshop on Signal Processing and Informatics (CWSPI)
September 21st, 2020, 18:45-22:00 hrs

via Google Meet at the following link:

The final program of the 13th Cyprus Workhshop on Signal Processing and Informatics - can be downloaded from here.

Technical Program








Andreas Spanias

Arizona State University, USA


SESSION 1: IoT and Sensing

Andreas Spanias

Arizona State University, USA


Energy Efcient Reuse of Mobile Nodes for Congestion Control in Wireless Sensor Networks

Natalie Temene, Charalampos Sergiou, chryssis Georgiou, Vasos Vasiliou

Department of Computer Science, University of Cyprus, Nicosia, Cyprus


Sensor Synchronization for Android Spatial Applications

Andreas Spanias1

1Maria Christofi, 2,3George Plastiras, 2,3Rafaella Elia, 2Vaggelis Tsiourtis, 2,3Theocharis Theocharides, 1Miltiadis Katsaros

1National Technical University of Athens, Athens, Greece

2University of Cyprus, Nicosia, Cyprus

3KIOS Research and Innovation Centre of Excellence, Nicosia, Cyprus


The Navarchos Fleet Management Platform

I.Constantinou1, C. Constantinou1, P. Gouvas2, T. Bouras2

1Istognosis Ltd Cyprus, 2UBITECH Limited Cyprus


SESSION 2: Machine Learning and Signal Processing

Chair: Marios Neofytou

3AeHealth LTD


Machine Learning based MEMS Sensor Calibration

Gowtham Muniraju, Andreas Spanias,

SenSIP Center, ECEE, ASU


Unsupervised Audio Source Separation using Generative Priors

Vivek Narayanaswamy1, Jayaraman, Thiagarajan2, Rushil Anirudh2, Andreas Spanias1

1SenSIP Center, ASU, 2Lawrence Livermore National Labs


Graph Representation Learning using Deep Neural Networks

Uday Shankar1, Jayaraman Thiagarajan2, Andreas Spanias1

1SenSIP Center, ASU, 2Lawrence Livermore National Labs


SESSION 3: Computer Vision

Chair: Andreas Panayides

University of Cyprus


Cognitive Swarm of UAVs for Search and Rescue

Guillaume Voirin, Loizos Michael

Open University of Cyprus & Research Center on Interactive Media, Smart Systems, and Emerging Technologies


Detecting Obstacles for Pedestrians’ Safety

Marios Thoma1, Zenonas Theodosiou1, Harris Partaourides1, Charalambos Tylliros1, Demetris Antoniades1, Andreas Lanitis1,2

1RISE, Nicosia, Cyprus, 2Cyprus University of Technology, Limassol, Cyprus


Machine Learning Methods for PV Array Soilage Detection on the Cyprus Solar Dataset

Kristen Jaskie1 and Joshua Martin1, Yiannis Tofis2 Andreas Spanias1

1SenSIP Center, ECEE, ASU, 2KIOS Center, University of Cyprus


Cloud Segmentation and Movement Prediction

Sameeksha Katoch, Pavan Turaga, Cihan Tepedelenlioglu, Andreas Spanias

SenSIP Center, ECEE, ASU


SESSION 4: Medical Imaging

Chair: Efthyvoulos Kyriacou

Frederick University


Detection of Breast Cancer with Mammography: Use of temporal subtraction of sequential mammograms

Kosmia Loizidou, Galateia Skouroumouni, Christos Nikolaou and Costas Pitris

KIOS, University of Cyprus


Machine Learning Techniques Comparison for Classification of Barret’s and Dysplasia from In Vivo Esophagus Optical Coherence Tomography Images

Christos Photiou1, George Plastiras1, Guillermo Tearney2, Costas Pitris1

1KIOS Center of Excellence for Intelligent System and Networks, Dept. of Electrical and Computer Engineering, University of Cyprus,

2Massachusetts General Hospital and Harvard medical school 55 Fruit Street, Boston, USA


SESSION 5: PhD Presentations – 5 min. (2 to 3 slides)

Costas Pitris

University of Cyprus


Extracting Explainable Assessments of Alzheimer’s disease via Machine Learning on brain MRI imaging data

Kleo Achilleos, Nicoletta Prentza, Antonis C. Kakas, Constantinos S. Pattichis

Department of Computer Science, University of Cyprus, Nicosia, Cyprus


Argumentation-based framework for Explainable Machine Learning (ARGEML)

Nicoletta Prentzas, Antonis Kakas, Constantinos S. Pattichis

Department of Computer Science, University of Cyprus


A Review of Brain MRI Multiple Sclerosis Disease Image Analysis Studies

Andria Nicolaou, Department of Computer Science, University of Cyprus, Nicosia, Cyprus


Intelligent Virtual Reality Systems for pain management in cancer patients

Melpo Pittara

Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligent, University of Groningen, Department of Computer Science, University of Cyprus


SESSION 6: Elevator Speech Presentations – 2 min (1 to 2 slides)

Constantinos S. Pattichis

University of Cyprus


AI for Power Converters

Mohit Malu, Andreas Spanias and Gautam Dasarathy



RET Project: Solar Fault Detection and Classification using Machine Learning

Milton Johnson

Bioscience High School, Phoenix

Advisors: Kristen Jaskie and Andreas Spanias,  ECEE, SenSIP, ASU


Fault Classification in PV Arrays using Pruned Neural Networks

Sunil Rao, Cihan Tepedelenlioglu and Andreas Spanias



Using Machine Learning and Audio Spectral Features For COVID-19 Testing

Michael Esposito

Advisors: Sunil Rao, Vivek Narayanaswami and Andreas Spanias



Semi-Supervised Classification via Graph Filtering

Jie Fan, Cihan Tepedelenlioglu and Andreas Spanias

SenSIP Center, ECEE, ASU


Space-Based Computational Imaging Systems

Drika Iqbal, Suren Jayasuriya, Andreas Spanias




frontiers vector logoThe COVID-19 pandemic marks one of the greatest global challenges experienced this century. It has led to more than 20 million reported infections and caused more than 800 000 deaths world-wide. Despite attempts at lifting restrictions for lock-downs and seeking ways “back” to a “new normal”, we are far from a stable transition to a new normal life.

Digital Health solutions have already been used in many ways from tracking and tracing apps to deep learning for analysis of computerized tomography images or audio-based diagnosis and early symptom recognition. However, there are many technologies and innovations that remain unexploited with vast potential in improving the reliability, trustability, usability, and explainability of healthcare services: including the speed and quality of diagnosis, healthcare process and results. In addition, novel technology solutions and innovations to adapt processes and technologies are desperately needed. Further, there is a need for new regulatory pathways and processes for rapid testing, approval and integration of these new technologies into practice.

More information can be found in:

CWSPINicosia, Cyprus, September 21st, 2020

Venue: University of Cyprus (New Campus),

THEE001 ROOM 148 (Building of the Department of Computer Science)

September 21st, 2020, 14:00-19:00 hrs

Organized and Sponsored by:
University of Cyprus, Cyprus

Research Centre on Interactive Media, Smart Systems and Interactive Technologies (RISE), Cyprus
Cyprus University of Technology, Cyprus
Frederick University, Cyprus
Arizona State University, USA
University of New Mexico, USA


Technically Co-Sponsored by:
IEEE Cyprus Section
IEEE CIS Cyprus Chapter
IEEE EMBS Cyprus Chapter
IET Cyprus Local Network

Dear Colleagues and Friends,
Following the successful one-day workshop we had in the last 12 years, we would  like to cordially invite you to participate in the upcoming 13th Cyprus Workshop on Signal Processing and Informatics (CWSPI 2020). The  overall objective of CWSPI 2020 is to disseminate new research results in several areas and help establish industry, university, and multi-university collaborations.  The workshop is mainly targeted to our graduate and intern students to present their most recent findings.

You can submit an abstract in one of the following themes:

- Digital signal and image processing
- Interactive Media, Virtual Reality and Augmented Reality Systems and Applications
- Speech, and audio, processing
- Intelligent and Cognitive systems
- Sensor networks and signal analysis
- Biomedical signal, image, and video analysis
- Wireless communications and signal processing
- FPGAS in signal, image and video processing.


Abstract submission guidelines:

This year we will have extended one page abstracts with IEEE guidelines.

A template is given at the following link:

Submit abstract to: Constantinos S. Pattichis
emails: This email address is being protected from spambots. You need JavaScript enabled to view it., with subject: CWSPI 2020 Abstract Submission.


Important Dates:
Abstract Submission Deadline: Monday, September 14th, 2020For more CWSPI 2020 details and updates, visit:

We are looking forward in seeing you all in September.

Andreas Panayides, Marios Neophytou

Constantinos S. Pattichis, Andreas Spanias,
for the Organising Committee

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