Yeeshtdevisingh Hosanee | Computer Science | Women Research Award

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Ms. Yeeshtdevisingh Hosanee | Computer Science | Women Research Award 

JCI | Mauritius

Author Profile

Scopus

🎓 Early Academic Pursuits

Ms. Yeeshtdevisingh Hosanee's academic journey is a testament to her passion for continuous learning and excellence in diverse fields. She began with a BSc (Hons) in Computer Science in 2012, graduating with second class first division honors. Her dedication to technical mastery led her to earn an MSc in Software Engineering in 2016 with distinction, followed by an MBA in Banking in 2018, achieving a commendable B+ grade. Currently, she is pursuing a research, further advancing her academic endeavors and research potential.

💼 Professional Endeavors

Her professional career spans over a decade of impactful roles in Mauritius's tech and banking sectors. From her early days as a Junior Windows and Unix Administrator (2009), she grew steadily into technical leadership positions, such as Associate Software Engineer (2012–2016), Cards IT Specialist (2016–2020), and Testing and Automation Analyst (2020–2021). Currently, she is serving as a Project Specialist, applying her extensive knowledge across domains. Simultaneously, Ms. Hosanee has been a part-time lecturer since 2017, inspiring young minds in institutions like the University of Mauritius, Curtin University (Mauritius), and Open University of Mauritius, teaching subjects such as Java programming, database management, and algorithm design.

🧠 Contributions and Research Focus

Ms. Hosanee is known for her strong command over AI-powered automation testing, DevOps, and banking IT systems. Her technical expertise includes performance testing (using JMeter and SOAPUI), system administration, API development, and middleware technologies like SAP PI and IBM App Connect. She has made substantial contributions to card payment systems, with expertise in ATM/POS concepts and compliance standards like PCI DSS and HSM. Her academic research spans Object-Oriented Programming education, ubiquitous learning, and AI-based assessment tools, with publications in IEEE and other notable platforms. She has also developed and published over 18 books, many of which integrate storytelling and poetry with AI and programming education for children, an innovative approach bridging STEM with creativity.

🏆 Accolades and Recognition

Ms. Hosanee’s multifaceted brilliance has garnered her global recognition. In 2019, she won the MT180 “My Thesis in 180 seconds” competition by AUF Canada. She was a Top 30 finalist in the JCI Ten Outstanding Young Persons of the World (2022) and has earned accolades like the 2024 Global Recognition Award, ABLE Golden Book Awards (Australia), and the Sahitya Sparsh Award (India). Her publications have received international attention, especially in digital education and AI advocacy.

🌍 Impact and Influence

Beyond academia and industry, Ms. Hosanee has contributed socially impactful solutions during the COVID-19 pandemic. Her open-source project "Noutiket", a web-based e-ticketing system, was implemented in Mauritius and Algeria to manage public queues for services like blood donation and library usage. This project drew media attention and was featured in several regional news outlets, underlining her commitment to using technology for public good.

✨ Legacy and Future Contributions

Ms. Hosanee’s legacy lies in her transdisciplinary vision—blending AI, education, literature, and social impact. With her imaginative approach, she is redefining how programming and AI can be taught to children and communities through relatable stories and cultural contexts. As she continues her research and expands her reach in AI, IoT, and machine learning, her future promises even deeper influence in shaping inclusive digital literacy and AI education.

Publications

📄 "An Enhanced Software Tool to Aid Novices in Learning Object-Oriented Programming (OOP)"

  • Authors: Yeeshtdevisingh Hosanee, Shireen Panchoo

  • Journal/Conference: 2015 International Conference on Emerging Trends in Electrical, Electronics and Sustainable Energy Systems (ICETEESES)

  • Publisher: IEEE

  • Publication Date: January 7, 2016

📄"The Implementation of a 2 User-Proficiency Level Novice OOP Software Tool"

  • Authors: Yeeshtdevisingh Hosanee, Shireen Panchoo

  • Conference: 2016 IEEE International Conference on Emerging Technologies and Innovative Business Practices for the Transformation of Societies (EmergiTech)

  • Publisher: IEEE

  • Publication Date: November 10, 2016

📄 "Teaching English Literacy to Standard One Students: Requirements Determination for Remediation Through ICT"

  • Authors: Yeeshtdevisingh Hosanee, Shireen Panchoo

  • Conference: 2016 IEEE International Conference on Emerging Technologies and Innovative Business Practices for the Transformation of Societies (EmergiTech)

  • Publisher: IEEE

  • Publication Date: November 10, 2016

📄 "The Analysis and the Need of Ubiquitous Learning to Engage Children in Coding"

  • Authors: Yeeshtdevisingh Hosanee, Shireen Panchoo

  • Conference: 2018 International Conference on Electrical, Electronics, and Computer Engineering (ELECOM)

  • Publisher: ELECOM

  • Publication Date: November 28–30, 2018

📄"The Need to Teach Object-Oriented Programming in Undergraduate Courses"

  • Author: Yeeshtdevisingh Hosanee

  • Publisher: GRIN Publishing

  • Publication Date: June 28, 2016

 

Francisco Mena | Computer Science | Best Researcher Award

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Mr. Francisco Mena | Computer Science | Best Researcher Award

University of Kaiserslautern-Landau | Germany

Author Profile

Scopus

Orcid

Google Scholar

🎓 Early Academic Pursuits

Mr. Francisco Mena began his academic journey in Santiago, Chile, where he demonstrated early excellence by ranking in the top 10% of his class at the prestigious Federico Santa María Technical University (UTFSM). He earned multiple degrees there, including a Bachelor’s and Master's equivalent in Computer Engineering. His master’s thesis focused on mixture models for learning in crowdsourcing scenarios, an early indicator of his passion for combining probabilistic modeling with real-world data complexities.  Currently, he is pursuing a PhD in Computer Science at RPTU Kaiserslautern-Landau, Germany, where his research delves into data fusion in multi-view learning for Earth observation applications—focusing on handling missing views in complex datasets.

💼 Professional Endeavors

Francisco’s career bridges academia, research, and practical industry contributions. He has held key positions as a student research assistant at DFKI, a visiting PhD researcher at Inria France, and has taught courses in machine learning, computational statistics, and neural networks in Chile and Germany. His practical experience includes work as a front-end and back-end developer and a research assistant for the Chilean Virtual Observatory, handling astroinformatics data from observatories like ALMA and ESO.

🔬 Contributions and Research Focus

Francisco's research sits at the intersection of machine learning, multi-modal data fusion, and unsupervised learning. He has advanced the understanding of deep learning models, particularly variational autoencoders, multi-view learning, and deep clustering. His work tackles computational complexity and seeks to design models that function effectively without heavy human intervention or domain specificity. He has applied his research to areas such as earth observation, vegetation analysis, neural information retrieval, and astroinformatics, making his work both versatile and impactful.

🏆 Accolades and Recognition

Francisco has received numerous scholarships and awards, including the PhD Scholarship from RPTU and the Scientific Initiation Award from UTFSM. His academic excellence and innovative research have also earned him roles as a lecturer, conference presenter, and session chair at international venues. 🏅

🌐 Impact and Influence

With multiple peer-reviewed journal articles and conference papers, Francisco’s contributions are shaping best practices in remote sensing, data fusion, and representation learning. His co-authored works in IEEE JSTARS, Remote Sensing of Environment, and other notable platforms highlight his influence in computational earth sciences and machine learning theory.

🧬 Legacy and Future Contributions

Francisco Mena is building a legacy of scientific rigor, interdisciplinary collaboration, and educational leadership. His focus on reducing dependency on domain-specific data and human labeling aligns with the future of scalable, autonomous machine learning. With a global academic presence and a strong foundation in both theoretical and applied research, Francisco is poised to contribute significantly to the fields of AI, data science, and earth analytics in the years to come.

Publications

📄Missing Data as Augmentation in the Earth Observation Domain: A Multi-View Learning Approach

  • Authors: Francisco Mena, Diego Arenas, Andreas Dengel

  • Journal: Neurocomputing

  • Year: 2025

📄Adaptive Fusion of Multi-Modal Remote Sensing Data for Optimal Sub-Field Crop Yield Prediction

  • Authors: Francisco Mena, Deepak Pathak, Hiba Najjar, Cristhian Sanchez, Patrick Helber, Benjamin Bischke, Peter Habelitz, Miro Miranda, Jayanth Siddamsetty, Marlon Nuske, et al.

  • Journal: Remote Sensing of Environment

  • Year: 2025

📄Common Practices and Taxonomy in Deep Multiview Fusion for Remote Sensing Applications

  • Authors: Francisco Mena, Diego Arenas, Marlon Nuske, Andreas Dengel

  • Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS)

  • Year: 2024

📄Impact Assessment of Missing Data in Model Predictions for Earth Observation Applications

  • Authors: Francisco Mena, Diego Arenas, Marcela Charfuelan, Marlon Nuske, Andreas Dengel

  • Conference Proceedings: IGARSS 2024 – IEEE International Geoscience and Remote Sensing Symposium

  • Year: 2024

📄Assessment of Sentinel-2 Spatial and Temporal Coverage Based on the Scene Classification Layer

  • Authors: Cristhian Sanchez, Francisco Mena, Marcela Charfuelan, Marlon Nuske, Andreas Dengel

  • Conference Proceedings: IGARSS 2024 – IEEE International Geoscience and Remote Sensing Symposium

  • Year: 2024

 

Dimitrios Karapiperis | Computer Science | Best Research Award

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Dr. Dimitrios Karapiperis | Computer Science | Best Research Award

International Hellenic University | Greece

Author Profile

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Orcid

Google Scholar

🎓 Early Academic Pursuits

Dr. Dimitrios Karapiperis embarked on his academic journey with a BSc degree in Information Technology from the Technological Educational Institute of Thessaloniki, Greece, where he developed a strong foundation in applied technology. His passion for computer science led him to pursue an MSc degree in Software Engineering at the University of York, UK, funded by the State Scholarships Foundation of Greece (ΙΚΥ). During this time, he honed his skills in software engineering and expanded his knowledge in computer science.

Furthering his academic aspirations, Dr. Karapiperis earned a PhD in Computer Science from the Hellenic Open University, Greece. His research during this period focused on the field of Entity Resolution (Record Linkage), where he developed similarity algorithms, data structures, approximation schemes, and scalable distributed solutions. This phase of his education laid the groundwork for his future contributions to the field of computer science.

💼 Professional Endeavors

Dr. Karapiperis' professional career is marked by his dedication to both teaching and research. He has held various academic positions, including his current role as a lecturer at the Hellenic Open University, where he teaches courses on Data Mining and Machine Learning techniques. He also serves as an adjunct lecturer at the International Hellenic University, Greece, where he imparts knowledge on subjects such as Knowledge Management in the Web, Big Data and Cloud Computing, and Exploratory Data Analysis and Visualization. His previous roles include an adjunct lecturer position at the University of Western Macedonia, Greece, where he taught courses in Data Technologies and Database Management. Additionally, Dr. Karapiperis has experience as a research intern at the University of York, UK, and as a research assistant at the University of Macedonia, Greece, where he developed web and database applications.

🔬 Contributions and Research Focus

Dr. Karapiperis has made significant contributions to the field of computer science, particularly in the area of privacy-preserving record linkage. His research work includes the design of similarity algorithms, data structures, and approximation schemes that enable large-scale systems to perform record linkage while preserving privacy. His innovative use of randomization schemes, such as Locality-Sensitive Hashing (LSH) and count-min sketches, has advanced the field and provided practical solutions for handling voluminous data. In addition to his research, Dr. Karapiperis has supervised over 30 post-graduate theses at the International Hellenic University and Hellenic Open University, guiding students in topics related to Big Data management and the design of efficient algorithms.

🏆 Accolades and Recognition

Throughout his career, Dr. Karapiperis has earned recognition for his contributions to academia and research. His dedication to teaching, research, and the development of innovative algorithms has positioned him as a respected figure in the field of computer science. His expertise and commitment to advancing knowledge have garnered him the respect of his peers and students alike.

🌍 Impact and Influence

Dr. Karapiperis' work has had a profound impact on the field of computer science, particularly in the areas of data management and privacy-preserving technologies. His research on scalable and distributed solutions for Entity Resolution has influenced the development of more secure and efficient systems for handling large datasets. Moreover, his role as an educator has enabled him to shape the minds of future computer scientists, ensuring that his influence extends beyond his own research.

🚀 Legacy and Future Contributions

As Dr. Karapiperis continues his academic and research endeavors, his legacy is one of innovation, dedication, and impact. His ongoing work in developing cutting-edge algorithms and scalable solutions positions him as a leader in the field. With a strong foundation in both education and research, Dr. Karapiperis is poised to make even greater contributions to computer science in the years to come.

 

Publications

  • 📝Predicting Football Match Results Using a Poisson Regression Model
    Authors: Konstantinos Loukas, Dimitrios Karapiperis, Georgios Feretzakis, Vassilios S. Verykios
    Journal: Applied Sciences
    Year: 2024
  • 📝A Suite of Efficient Randomized Algorithms for Streaming Record Linkage
    Authors: Dimitrios Karapiperis, Christos Tjortjis, Vassilios S. Verykios
    Journal: IEEE Transactions on Knowledge and Data Engineering
    Year: 2024
  • 📝Machine Learning in Medical Triage: A Predictive Model for Emergency Department Disposition
    Authors: Georgios Feretzakis, Aikaterini Sakagianni, Athanasios Anastasiou, Ioanna Kapogianni, Rozita Tsoni, Christina Koufopoulou, Dimitrios Karapiperis, Vasileios Kaldis, Dimitris Kalles, Vassilios S. Verykios
    Journal: Applied Sciences
    Year: 2024
  • 📝Tracing Student Activity Patterns in E-Learning Environments: Insights into Academic Performance
    Authors: Evgenia Paxinou, Georgios Feretzakis, Rozita Tsoni, Dimitrios Karapiperis, Dimitrios Kalles, Vassilios S. Verykios
    Journal: Future Internet
    Year: 2024