Angeliki Antoniou | AI | Best Researcher Award

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Assoc. Prof. Dr. Angeliki Antoniou | AI | Best Researcher Award

Assoc. Prof. Dr. Angeliki Antoniou | AI | Associate Professor at University of West Attica | Greece

Assoc. Prof. Dr. Angeliki Antoniou is a distinguished scholar in the field of Human-Computer Interaction (HCI), Educational Technologies, and Digital Cultural Heritage, currently serving at the University of West Attica, Department of Archival, Library and Information Studies, Greece. She earned her Doctor of Informatics (Ph.D.) from the University of Peloponnese, focusing on adaptive educational technologies for museums, and holds an MSc in Human-Computer Interaction with Ergonomics from University College London (UCL). Additionally, she possesses undergraduate degrees in Psychology from the University of Kent and Early Childhood Education from the National and Kapodistrian University of Athens, illustrating her interdisciplinary foundation that bridges education, psychology, and informatics. Professionally, Assoc. Prof. Dr. Angeliki Antoniou has accumulated extensive teaching and research experience across institutions such as the University of Peloponnese and the University of West Attica, where she has led courses in cognitive psychology, human-computer interaction, and digital learning environments. Her research interests include user-centered design, cognitive modeling, serious games, digital storytelling, and technology-enhanced museum learning. She has successfully contributed to and coordinated several international and national projects on cultural heritage technologies, and her work is well-cited in high-impact academic journals indexed in Scopus and IEEE. Assoc. Prof. Dr. Angeliki Antoniou’s research skills encompass experimental design, usability evaluation, qualitative and quantitative analysis, and the development of adaptive systems for education and culture. She has received academic recognition for her leadership in interdisciplinary research, along with honors for her contributions to digital culture and innovation in educational informatics. In conclusion, Assoc. Prof. Dr. Angeliki Antoniou exemplifies academic excellence, innovative vision, and global impact through her scholarly research, educational leadership, and enduring contributions to the advancement of digital cultural heritage and human-computer interaction.

Profile: Google Scholar

Featured Publications 

  1. Lykourentzou, I., Antoniou, A., Naudet, Y., & Dow, S. P. (2016). Personality matters: Balancing for personality types leads to better outcomes for crowd teams. Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing. Citations: 158

  2. Theodoropoulos, A., & Antoniou, A. (2022). VR games in cultural heritage: A systematic review of the emerging fields of virtual reality and culture games. Applied Sciences, 12(17), 8476. Citations: 108

  3. Antoniou, A., & Lepouras, G. (2010). Modeling visitors’ profiles: A study to investigate adaptation aspects for museum learning technologies. Journal on Computing and Cultural Heritage (JOCCH), 3(2), 1–19. Citations: 84

  4. Lykourentzou, I., Claude, X., Naudet, Y., Tobias, E., Antoniou, A., & Lepouras, G. (2013). Improving museum visitors’ quality of experience through intelligent recommendations: A visiting style-based approach. Workshop Proceedings of the 9th International Conference on Intelligent Environments. Citations: 76

  5. Antoniou, A., Lepouras, G., Bampatzia, S., & Almpanoudi, H. (2013). An approach for serious game development for cultural heritage: Case study for an archaeological site and museum. Journal on Computing and Cultural Heritage (JOCCH), 6(4), 1–19. Citations: 69

  6. Katifori, A., Perry, S., Vayanou, M., Antoniou, A., Ioannidis, I. P., & McKinney, S. (2020). “Let them talk!” Exploring guided group interaction in digital storytelling experiences. Journal on Computing and Cultural Heritage (JOCCH), 13(3), 1–30. Citations: 67

  7. Antoniou, A., Katifori, A., Roussou, M., Vayanou, M., Karvounis, M., & Kyriakidi, M. (2016). Capturing the visitor profile for a personalized mobile museum experience: An indirect approach. Proceedings of the Digital Heritage International Congress. Citations: 60

 

Ms. Kumi Rani – Machine Learning – Best Researcher Award

Published on by Academic Achievements

Ms. Kumi Rani - Machine Learning - Best Researcher Award

Indian Institute of Technology BHU, Varanasi - India

Professional Profiles

Early Academic Pursuits:

Kumi Rani's academic journey began with a passion for Computer Science and Engineering at the prestigious Indian Institute of Technology (IIT) BHU, Varanasi. During her early academic pursuits, she immersed herself in a challenging curriculum, laying the foundation for a robust understanding of computational sciences. The rigorous coursework at IIT BHU introduced her to a diverse range of subjects, including Artificial Intelligence, Neural Networks, Computer Graphics, and Mathematical Modeling.

Professional Endeavors:

Post her academic journey, Kumi Rani transitioned into the realm of academia. She served as an Assistant Professor at Sharda University, Greater Noida, where she contributed to the Computer Science and Engineering department. Subsequently, she expanded her academic footprint to include the Mathematics department at Shree DKV Science and Arts College, Jamnagar. This versatility showcased her ability to navigate and contribute to different facets of academia.

Contributions and Research Focus:

Kumi Rani's contributions in academia extend to her technical skills and her research focus. Proficient in operating systems such as Windows Vista/XP/Linux and mathematical software like Matlab R2009a, she demonstrated a command over tools crucial for computational research. Her programming expertise in C, Python, C++, and Matlab reflected her commitment to staying at the forefront of technological advancements. At the heart of her research focus lies an intersection of Machine Learning, Deep Learning, and Applied Mathematics. Her Ph.D. thesis, "Handcrafted and Deep Learning Techniques for Classification of Medical and Hyperspectral Images," underscores her commitment to addressing critical challenges in medical image analysis. By amalgamating traditional handcrafted methods with cutting-edge deep learning architectures, she aimed to elevate the precision and efficiency of medical image diagnostics. Her M.Tech thesis, "A Study of Clustering Algorithms in Fuzzy Scenario," delves into the realms of unsupervised learning and statistical data analysis. The introduction of the Kernel Intuitionistic Fuzzy c-Means algorithm reflects her innovative approach to clustering, emphasizing improved performance and robustness.

Accolades and Recognition:

Kumi Rani's academic prowess has earned her notable accolades and recognition. She secured an impressive All India Rank of 199 in the National Eligibility Test (NET) for Lectureship, a joint initiative by the Council of Scientific and Industrial Research (CSIR) and University Grants Commission (UGC). Additionally, she secured an All India Rank of 83 in the Graduate Aptitude Test in Engineering (GATE), a testament to her excellence in the field. Her pursuit of continuous learning is evident through her completion of professional development programs and courses on platforms like Coursera and Oracle Academy. This commitment to staying abreast of industry-relevant skills showcases her dedication to both personal and professional growth.

Impact and Influence:

In her professional roles, Kumi Rani has not only shared her knowledge through teaching but has also left an impact on real-world projects. Her involvement in projects at ATC Labs, including the design of a real-time broadcast communicator on the Android platform, reflects her ability to apply computational skills to practical scenarios. Her guidance on B.Tech projects further extends her influence to shaping the next generation of computational professionals.

Legacy and Future Contributions:

As Kumi Rani continues her journey, her legacy at the Indian Institute of Technology BHU, Varanasi, is marked by her early academic pursuits, versatile contributions in academia, and impactful research focus. Her commitment to education, demonstrated through the diverse courses she has taught, and her ongoing research pursuits are likely to define her future contributions. In the interdisciplinary field of computational sciences and mathematics, Kumi Rani's legacy is shaped by a dedication to excellence and a vision for the continual advancement of knowledge and application.

Notable Publications:

Classification of wireless capsule endoscopy images for bleeding using deep features fusion 2022-11-16

Cyclic learning rate based HybridSN model for hyperspectral image classification 2022-09

Automated bleeding detection in wireless capsule endoscopy images based on sparse coding 2021-08