Mrs. Sabatina Criscuolo | Signal Processing Awards | Young Scientist Award

Mrs. Sabatina Criscuolo | Signal Processing Awards | Young Scientist Award 

Mrs. Sabatina Criscuolo, University of Naples Federico II, Italy

Sabatina Criscuolo is an Italian biomedical engineer currently pursuing a Ph.D. in Information and Communication Technology for Health at the University of Naples Federico II, where she is affiliated with the National Research Council’s Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA). Her research focuses on the development of advanced artificial intelligence techniques to support precision medicine, with specific applications in neurodegenerative diseases, type 1 diabetes, and colorectal surgery. Sabatina has also collaborated internationally, including a visiting PhD position at the Applied Intelligence Research Centre in Dublin, where she worked on EEG artifact removal using variational autoencoders. With a strong academic background, she holds a Master’s degree in Biomedical Engineering, specializing in Bionic and Biorobotics, and has been involved in various research projects and initiatives aimed at enhancing health monitoring and rehabilitation technologies. In addition to her research activities, Sabatina contributes to the scientific community as a reviewer for multiple journals and has organized significant conferences in her field.

Professional Profile:

ORCID

Research for Young Scientist Award Evaluation for Sabatina Criscuolo

Sabatina Criscuolo is a promising candidate for the Research for Young Scientist Award, given her strong academic background, ongoing research initiatives, and contributions to the field of biomedical engineering and artificial intelligence. Here are several key points that highlight her suitability for this award.

Academic Experience

Sabatina is currently engaged in research at the National Research Council – STIIMA in Lecco, Italy, focusing on advanced artificial intelligence techniques to support precision medicine. Her work involves developing AI algorithms for applications in electroencephalographic (EEG) analysis related to neurodegenerative diseases, type 1 diabetes, and colorectal surgery.

PhD Studies: Since January 2022, she has been pursuing her PhD, with her thesis submission planned for December 2024 and expected graduation in March 2025. She has also been a visiting PhD student at the Applied Intelligence Research Centre in Dublin, Ireland, where she worked on EEG artifact removal using variational autoencoders and explainable AI.

Education

Sabatina holds a Master’s degree in Biomedical Engineering with a focus on Bionic & Biorobotics, where she developed a wearable Brain-Computer Interface system for robot-assisted rehabilitation in children with ADHD. She also completed a Bachelor’s degree in Biomedical Engineering, focusing on innovative enzyme immobilization methods.

Research Collaborations

Her collaborative research spans several institutions, including the University of Salento, Temple University, and the Interdepartmental Research Centre on Management and Innovation in Healthcare at her home university.

Scientific Impact

As of July 2024, Sabatina has an H-index of 5 on Scopus, reflecting her contributions to topics such as EEG signal analysis and diabetes management.

Publication Top Notes

Interpreting the latent space of a Convolutional Variational Autoencoder for semi-automated eye blink artefact detection in EEG signals

Improving Multiscale Fuzzy Entropy Robustness in EEG-Based Alzheimer’s Disease Detection via Amplitude Transformation

Exploring Nutritional Influence on Blood Glucose Forecasting for Type 1 Diabetes Using Explainable AI

A Novel Metric for Alzheimer’s Disease Detection Based on Brain Complexity Analysis via Multiscale Fuzzy Entropy

EEG complexity-based algorithm using Multiscale Fuzzy Entropy: Towards a detection of Alzheimer’s disease

Dr. Zhengjia Xu | Signal Analysis Award | Best Researcher Award

Dr. Zhengjia Xu | Signal Analysis Award | Best Researcher Award

Dr. Zhengjia Xu, Cranfield University, United Kingdom

Dr. Zhengjia Xu is an accomplished Electronic and Embedded Software Engineer with a rich blend of academic and industrial experience. He holds a Ph.D. in Aerospace from Cranfield University, where his research focused on cognitive communication and intelligent DSP for drone applications. Dr. Xu has a strong track record of over 25 peer-reviewed publications, including influential journal articles and conference papers in fields such as intelligent signal processing and aerospace engineering. Currently, he serves as a Research Fellow at Cranfield University, specializing in position, navigation, and timing systems, and has led several high-profile projects funded by ESA and EPSRC. His prior roles include Senior RF Engineer at Drone Defense Services Ltd, where he made significant advancements in passive RF radar and SDR-based receivers, and Electronic and Embedded Software Engineer at ASH Wireless (Captec LTD), where he developed advanced NB-IoT products and embedded firmware.

Professional Profile:

Summary of Suitability for the Best Researcher Award

Zhengjia Xu has a comprehensive technical and research background, demonstrating expertise in both industrial and academic settings. His experience spans a range of areas including embedded software development, digital system design, RF analysis, and intelligent signal processing.

Education

Ph.D. in Aerospace Engineering
Cranfield University, Cranfield, UK
September 2017 – March 2021

  • Research Area: Cognitive communication, intelligent DSP, drone communication
  • Thesis: “Cognitive Communication for UAV Applications”
  • Proposed a DSP algorithm enabled by deep learning for RF fingerprint identification, simulated air-to-ground communication performance, and proposed system architectures for UAV communications.

M.Sc. in Vehicle Operation Design
Nanjing University of Aeronautics and Astronautics, Nanjing, China
September 2014 – June 2017

  • Research Area: Aircraft modeling and control, fault-tolerant control
  • Simulated aircraft aerodynamic models, developed aircraft control algorithms, and analyzed real flight data. Involved in PCB layout design and the development of flight simulators.

Bachelor in Electrical and Electronics Engineering
Nanjing University of Aeronautics and Astronautics, Nanjing, China
September 2010 – June 2014

  • Thesis: “Research on Stability and Control of Quadratic Aircraft Based on STM32F407”
  • Designed PID-based flight control software on a self-designed PCB board with STM32 MCU.

Work Experience

Research Fellow in Position, Navigation, and Timing
Cranfield University, Bedford, UK
March 2023 – Present

  • Managed projects with stakeholders including Telespazio – Thales UK, European Space Agency, and others.
  • Co-supervised over 10 MSc and PhD student projects.
  • Main researcher for two ESA-funded projects and one EPSRC-funded 6G project.
  • Delivered lectures and developed course materials for 13 hours across four modules.

Senior RF Engineer
Drone Defense Services Ltd, Retford, UK
March 2022 – March 2023

  • Developed passive RF radar products, including software refactoring and hardware integration.
  • Improved radar detection range significantly and led the design of an SDR-based OFDM receiver.
  • Proficient in SDR developments and GPU platform optimization.

Electronic and Embedded Software Engineer
ASH Wireless (Captec LTD), Southampton, UK
March 2021 – March 2022

  • Developed an NB-IoT product for air-to-ground communication.
  • Customized IoT protocol suite and performed schematic design and RF validation.
  • Experienced in STM ARM Cortex-based embedded application developments.

Volunteer, IET Aerospace TN Committee
Institution of Engineering and Technology (IET)
September 2022 – Present

  • Participated in strategic planning and board meetings for the aerospace technical network.

Publication top Notes:

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