Grazia Ragone | Human-Computer Interaction | Best Researcher Award

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Dr. Grazia Ragone | Human-Computer Interaction | Best Researcher Award

šŸ”¬ Grazia Ragone is a researcher in Human-Computer Interaction (HCI) with a focus on autism and interactive systems. šŸ« She earned her PhD from the University of Sussex, UK, where she investigated social motor synchrony in autistic children through motion capture and sonification. šŸŽ¼ With a background in psychology, developmental science, and music therapy, she integrates interdisciplinary methods into assistive technology. šŸ’» She has extensive teaching experience in research methods, cognitive science, and HCI at the University of Sussex. šŸ† Her research has been recognized with multiple international awards, including Microsoft Researchā€™s Best Student Research Competition. šŸŒ She actively contributes as a reviewer and associate chair for HCI conferences and journals. šŸ“– Her work bridges psychology, technology, and education, aiming to enhance accessibility and interaction for neurodiverse individuals.

Profile

Education šŸŽ“

She completed her PhD in 2023 at the University of Sussex, UK, where her research focused on autism, motion capture, and social motor synchrony. Prior to this, she earned an MSc in Psychological Methods from the University of Sussex in 2018, with a focus on autism and interactional features. She also holds an MPhil in Developmental Psychology from London Metropolitan University (2015), specializing in child development and interaction. In 2014, she completed her BSc in Developmental Psychology at London Metropolitan University, studying early cognitive and social development. She further enriched her expertise with a Masterā€™s in Music & Art Therapy from Tor Vergata University in Rome (2006), where she focused on therapeutic interventions for individuals with special needs. Her academic journey began with a BA in Humanities from the University of Pavia, Italy (2004), where she studied philosophy, linguistics, and cultural studies.

Experience šŸ‘Øā€šŸ«

From 2019 to 2023, she worked as a Teaching Assistant at the University of Sussex, UK, where she taught Human-Computer Interaction (HCI), research methods, and professional skills. Prior to this, she served as a Research Assistant at the University of Sussex (2016-2018), focusing on technology designed for neurodiverse children. From 2014 to 2016, she conducted research on autism and interactive environments at London Metropolitan University. Earlier in her career, she was a Research Assistant at CNR-ISTI Pisa, Italy (2008-2014), where she contributed to the development of assistive software for autistic children. Her experience also includes working as a Music Therapist for the Rome City Council (2005-2010), providing therapeutic interventions for autistic children. Additionally, from 2010 to 2019, she worked as a Trainer and Consultant, conducting workshops and training programs for professionals in the field of autism.

Research Interests šŸ”¬

Her research focuses on Human-Computer Interaction (HCI) and autism, developing interactive systems to support neurodiverse individuals. She explores the role of music and sonification in enhancing motor and social skills through auditory feedback. Her work also includes investigating social motor synchrony using motion capture technology. She designs AI-powered assistive technology to support autistic children and applies user-centered design principles to create accessible interfaces for individuals with special needs.

Awards & Recognitions šŸ…

She has received several prestigious awards and honors for her contributions to autism research and assistive technology. In 2021, she was awarded the Best Student Research Award by Microsoft Research at the ASSETS Conference. Her work was also recognized with the Best Work in Progress Award at the IDC Conference on autism research in 2020. In 2013, she received the Horizon Research Award from London Metropolitan University for outstanding research. Her contributions to autism research earned her a Massachusetts Senate Citation in 2012, and in 2011, she was honored with the Rotary Club Research Award from CNR Pisa for excellence in autism studies.

Publications šŸ“š

  • Ā Supporting and understanding autistic childrenā€™s non-verbal interactions through OSMoSIS, a motion-based sonic system
    International Journal of Child-Computer Interaction
    2025-02 |Ā Journal article
    DOI:Ā 10.1016/j.ijcci.2025.100726
    CONTRIBUTORS:Ā Grazia Ragone;Ā Judith Good;Ā Kate Howland

  • Child-Centered AI for Empowering Creative and Inclusive Learning Experiences

    Proceedings of ACM Interaction Design and Children Conference: Inclusive Happiness, IDC 2024
    2024 |Ā Conference paper
    DOI:Ā 10.1145/3628516.3661157

    EID:

    2-s2.0-85197894406

    Part ofISBN:Ā 9798400704420
    CONTRIBUTORS:Ā Ragone, G.;Ā Ali, S.A.;Ā Esposito, A.;Ā Good, J.;Ā Howland, K.;Ā Presicce, C.

  • Designing Safe and Engaging AI Experiences for Children: Towards the Definition of Best Practices in UI/UX Design

    arXiv
    2024 |Ā Other
    DOI:Ā 10.48550/arXiv.2404.14218

    EID:

    2-s2.0-85192517180

    Part ofĀ ISSN:Ā 23318422
    CONTRIBUTORS: Ragone, G.; Buono, P.; Lanzilotti,

Raveendra Pilli | Image Processing | Best Researcher Award

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Mr. Raveendra Pilli | Image Processing | Best Researcher Award

He mentored B.Tech. projects focused on the early detection of Alzheimerā€™s Disease. One project involved utilizing multi-modality neuroimaging techniques, where MRI and PET images were collected from the OASIS database, preprocessed, and robust features were extracted for classification. MATLAB and the SPM-12 toolbox were used for this task. Another project focused on the early detection of Alzheimerā€™s Disease using deep learning networks, where an MRI dataset from the ADNI database was collected, preprocessed, and the performance was compared with baseline algorithms. For this project, he used MATLAB and Python.

NIT-Silchar, India

Profile

Education

A dedicated research scholar with a Ph.D. in Electronics and Communication Engineering from the National Institute of Technology Silchar (Thesis Submitted, CGPA 9.0), specializing in brain age prediction and early detection of neurological disorders using neuroimaging modalities. With extensive teaching experience, a strong passion for research, and a proven ability to develop engaging curricula, deliver effective lectures, and guide students toward academic success, I am committed to contributing to the field through research, publications, and presentations. My academic journey includes an M.Tech. from JNTU Kakinada (76.00%, 2011) and a B.Tech. from JNTU Hyderabad (65.00%, 2007), along with a strong foundational background in science, having completed 10+2 (MPC) with 89.00% in 2003 and SSC with 78.00% in 2001.

Work experience

He worked as a Junior Research Fellow at the National Institute of Technology, Silchar, Assam, from July 2021 to June 2023, where he assisted professors with course delivery for Basic Electronics, conducted laboratory sessions, graded assignments, and provided office hours for student support. From July 2023 to December 2024, he served as a Senior Research Fellow at the same institute, taking on additional responsibilities, including mentoring B.Tech. projects and assisting with Digital Signal Processing laboratory duties. Prior to his research roles, he was an Assistant Professor at SRK College of Engineering and Technology, Vijayawada, Andhra Pradesh, where he taught courses such as Networks Theory, Digital Signal Processing, RVSP, SS, and LICA. He utilized innovative teaching methods, including active learning techniques, to enhance student engagement and learning outcomes. He also mentored undergraduate research projects in image processing and received positive student evaluations for his teaching effectiveness.

Publication