Swathi Priyadarshini Tigulla | Computer Science | Best Researcher Award

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Dr. Swathi Priyadarshini Tigulla | Computer Science | Best Researcher Award

Osmania University | India

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Scopus

Early Academic Pursuits

Dr. Swathi Priyadarshini Tigulla laid the foundation of her academic journey with a degree in Information Technology, followed by a master’s program in Information Technology with a specialization in network security. Her pursuit of advanced knowledge culminated in a doctoral degree in Computer Science and Engineering from Osmania University. From the beginning, she demonstrated a strong inclination toward solving computational problems and a keen interest in the emerging domains of artificial intelligence, machine learning, and network security.

Professional Endeavors

Her professional career reflects an extensive teaching and mentoring journey across reputed institutions. She began her career as an Assistant Professor in engineering colleges where she taught computer science, network security, and software engineering, and guided student projects. Over the years, she progressed to significant academic roles, including serving as Head of the Department, coordinating extracurricular activities, and contributing to student training and placement. Presently, she continues her academic engagement as an Assistant Professor specializing in artificial intelligence and machine learning, while also actively mentoring projects and participating in innovative academic initiatives such as GEN-AI teams and project schools.

Contributions and Research Focus

Dr. Tigulla’s research is strongly anchored in artificial intelligence, machine learning, and soft computing, with a particular focus on healthcare applications such as heart stroke prediction models. Her publications have proposed innovative approaches that integrate clustering, classification, and deep learning techniques to enhance medical predictions, combining accuracy with practical applicability. Beyond healthcare, her work also explores security strategies in cloud computing and data-driven approaches to protect systems from vulnerabilities. This blend of healthcare informatics and cyber security positions her research at the intersection of technology and community impact.

Accolades and Recognition

Her expertise has been recognized through publications in reputed international journals such as Measurement: Sensors and Journal of Positive School Psychology, along with contributions to international conferences under IEEE. She has served as a reviewer for scholarly journals and academic book chapters, demonstrating her standing as a trusted evaluator in her field. Her involvement as an organizer of technical workshops, hackathons, and project expos reflects her commitment to academic innovation and student skill development, further reinforcing her recognition as a versatile academic leader.

Impact and Influence

The impact of Dr. Tigulla’s work is evident in both her research outcomes and her teaching contributions. Her models for heart stroke prediction contribute significantly to community health by combining artificial intelligence with real-world medical applications. As an educator, she has influenced generations of students by equipping them with knowledge in machine learning, artificial intelligence, and advanced computational concepts. Her leadership in academic events has fostered a culture of innovation, creativity, and hands-on learning among students, thereby extending her influence beyond traditional teaching.

Legacy and Future Contributions

Dr. Tigulla’s legacy is one of blending research excellence with community benefit. By focusing on both healthcare prediction models and system security, she has addressed two domains of immense social importance—public health and digital trust. Looking forward, her future contributions are expected to further deepen the integration of artificial intelligence into real-world applications, enhance her role as a reviewer and academic guide, and continue her efforts to shape students into innovative researchers and industry-ready professionals.

Publications

Article: Developing Heart Stroke Prediction Model using Deep Learning with Combination of Fixed Row Initial Centroid Method with Naïve Bayes, Decision Tree, and Artificial Neural Network
Authors: T. Swathi Priyadarshini, Vuppala Sukanya, Mohd Abdul Hameed
Journal: Measurement: Sensors
Year: 2024

Article: Collaboration of Clustering and Classification Techniques for Better Prediction of Severity of Heart Stroke using Deep Learning
Authors: T. Swathi Priyadarshini, Vuppala Sukanya, Mohd Abdul Hameed
Journal: Measurement: Sensors
Year: 2025

Article: Deep Learning Prediction Model for Predicting Heart Stroke using the Combination Sequential Row Method Integrated with Artificial Neural Network
Authors: T. Swathi Priyadarshini, Mohd Abdul Hameed, Balagadde Ssali Robert
Journal: Journal of Positive School Psychology
Year: 2022

Article: Methods of Hidden Pattern Usage in Cloud Computing Security Strategies with K-means Clustering
Authors: T. Swathi Priyadarshini, Dr. S. Ramachandram
Journal: AIJREAS
Year: 2021

Article: A Review on Security Issue Solving Methods in Public and Private Cloud Computing
Authors: T. Swathi Priyadarshini, S. Ramachandram
Journal: IJMTST
Year: 2020

Conclusion

Dr. Swathi Priyadarshini Tigulla embodies the qualities of an academician and researcher who successfully bridges the gap between theoretical advancements and community impact. Her journey, marked by academic rigor, extensive teaching experience, and impactful research, showcases her dedication to advancing artificial intelligence and machine learning for practical applications. Recognized as both a researcher and a mentor, she continues to inspire through her contributions in education, healthcare, and cyber security. In conclusion, her career highlights a sustained commitment to knowledge, innovation, and community-oriented research, establishing her as a distinguished academic voice in the field of computer science and engineering.

 

Vaggelis Lamprou | Computer Science | Best Researcher Award

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Mr. Vaggelis Lamprou | Computer Science | Best Researcher Award

National Technical University of Athens | Greece

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Google Scholar 

Early Academic Pursuits

Mr. Vaggelis Lamprou began his academic journey with a strong foundation in mathematics, earning his Bachelor’s degree from the National and Kapodistrian University of Athens, where he developed a deep interest in calculus, probability theory, and statistics. His passion for analytical reasoning and theoretical problem-solving led him to pursue a Master’s degree in Mathematics at the University of Bonn, Germany, where he focused on probability theory and its applications, culminating in a thesis on large deviations in mean field theory. This early academic phase not only honed his mathematical rigor but also laid the groundwork for his transition into the emerging domains of artificial intelligence and machine learning.

Professional Endeavors

Building upon his academic background, Mr. Lamprou advanced into roles that blended research with real-world applications. As a Data Analyst at Harbor Lab, he utilized statistical and computational tools to optimize platform usability and collaborated in developing innovative cost estimation tools for the maritime industry. His transition into machine learning engineering at Infili Technologies SA and later at the DSS Lab, EPU-NTUA, marked a shift toward high-impact AI-driven research and development, particularly within European-funded projects focusing on federated learning, generative AI, anomaly detection, and privacy-preserving technologies.

Contributions and Research Focus

Mr. Lamprou’s research is rooted in the intersection of mathematics, computer science, and artificial intelligence, with a strong emphasis on interpretable AI, deep learning, and probabilistic modeling. His work spans applications in medical imaging, cybersecurity, and large-scale distributed learning systems. In his Master’s thesis in Artificial Intelligence, he explored the evaluation of interpretability methods for deep learning models in medical imaging, underlining his dedication to developing transparent and trustworthy AI solutions. His contributions also extend to federated learning frameworks, enhancing data security and performance in next-generation communication networks.

Publications and Scholarly Engagement

His scholarly output reflects a commitment to both theoretical innovation and practical problem-solving. Notable works include a study on interpretability in deep learning for medical images published in Computer Methods and Programs in Biomedicine, and a comprehensive survey on federated learning for cybersecurity and trustworthiness in 5G and 6G networks in the IEEE Open Journal of the Communications Society. He actively participates in academic discourse, presenting at international conferences such as the International Conference on Information Intelligence Systems and Applications, further contributing to the global exchange of ideas in AI research.

Accolades and Recognition

Mr. Lamprou’s academic excellence is evident in his high academic distinctions throughout his studies, including top GPAs in his advanced degrees. His recognition extends beyond academic grades, with his selection to contribute to high-profile European R&D initiatives—a testament to his expertise and reliability in cutting-edge technological research. His invited participation in prestigious conferences and collaborations with leading research institutions reflects the respect he commands within the AI and machine learning community.

Impact and Influence

Through his research and professional activities, Mr. Lamprou has contributed to advancing AI methodologies in fields of societal importance, such as healthcare and cybersecurity. His work in interpretable AI has the potential to bridge the gap between complex machine learning models and human understanding, fostering trust in AI-assisted decision-making. In the realm of federated learning, his contributions support data sovereignty and privacy, addressing critical challenges in the deployment of AI at scale across sensitive domains.

Legacy and Future Contributions

As a PhD candidate at the National Technical University of Athens, Mr. Lamprou is poised to further deepen his contributions to the AI research landscape. His ongoing work aims to push the boundaries of interpretable and probabilistic AI models, with a vision to create transparent, reliable, and secure machine learning systems. His trajectory suggests a lasting influence on both the academic and industrial sectors, with the potential to inspire future researchers to prioritize ethical and explainable AI solutions.

Publications

Article: Federated Learning for Enhanced Cybersecurity and Trustworthiness in 5G and 6G Networks: A Comprehensive Survey
Authors: Afroditi Blika, Stefanos Palmos, George Doukas, Vangelis Lamprou, Sotiris Pelekis, Michael Kontoulis, Christos Ntanos, Dimitris Askounis
Journal: IEEE Open Journal of the Communications Society
Year: 2025

Article: On the trustworthiness of federated learning models for 5G network intrusion detection under heterogeneous data
Authors: Vangelis Lamprou, George Doukas, Christos Ntanos, Dimitris Askounis
Journal: Computer Networks
Year: 2025

Article: Data analytics for research on complex brain disorders
Authors: Michail Kontoulis, George Doukas, Theodosios Pountridis, Loukas Ilias, George Ladikos, Vaggelis Lamrpou, Kostantinos Alexakis, Dimitris Askounis, Christos Ntanos
Journal: Open Research Europe
Year: 2024

Article: On the evaluation of deep learning interpretability methods for medical images under the scope of faithfulness
Authors: Vangelis Lamprou, Athanasios Kallipolitis, Ilias Maglogiannis
Journal: Computer Methods and Programs in Biomedicine
Year: 2024

Article: Grad-CAM vs HiResCAM: A comparative study via quantitative evaluation metrics
Author: Vaggelis Lamprou
Institution: University of Piraeus
Year: 2023

Conclusion

With his blend of theoretical insight, technical skill, and a forward-looking research vision, Mr. Lamprou stands out as a promising researcher whose work is set to have a significant impact on the development of transparent and reliable AI technologies. His career embodies the bridge between rigorous academic inquiry and impactful, real-world AI solutions.

Ziang Liu | Engineering | Best Researcher Award

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Mr. Ziang Liu | Engineering | Best Researcher Award

Nanjing University | China

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Early Academic Pursuits

Mr. Ziang Liu began his academic journey with distinction at Tianjin University, where he earned his Bachelor of Science in Electronic Engineering. His strong foundation in engineering and mathematics laid the groundwork for advanced research and innovation. Continuing his academic trajectory, he pursued a Master of Science in Electronic Engineering at the prestigious Nanjing University, where he was recognized as an Outstanding Student and awarded the First-class Academic Scholarship.

Professional Endeavors

Ziang has accumulated valuable industry experience through impactful internships. At Meituan Shanghai, he served as an LLMs Evaluation Algorithm Intern, where he designed evaluation schemes and analyzed instruction-following capabilities across large language models such as Qwen, Doubao, ChatGPT 3.5/4, and Llama2-70B.  In another significant role at Alibaba DingTalk in Hangzhou, he worked on the back-end development of Chatmemo, an enterprise AI assistant. There, he implemented knowledge graph subgraph displays and integrated Retrieval-Augmented Generation (RAG), significantly boosting response speed and system performance.

Contributions and Research Focus

Mr. Liu’s core interests revolve around LLMs (Large Language Models), RAG (Retrieval-Augmented Generation), and knowledge graph technologies. He has contributed to the design and optimization of backend systems for intelligent applications in healthcare and enterprise settings. His work on deploying frameworks like Graph RAG and utilizing tools like Redis, MySQL, and Spring Boot has shown practical outcomes in real-world systems, particularly in performance optimization, load balancing, and cache management. His participation in the Nanjing University Intelligent Hospital Project resulted in a custom online medication purchasing system, complete with AI-powered Q&A capabilities and scalable backend infrastructure.

Accolades and Recognition

Ziang Liu’s academic excellence is evident through a remarkable series of accolades earned during both his undergraduate and postgraduate studies. He was honored as the Outstanding Student of Nanjing University in 2023 and received the First-class Academic Scholarship in 2022, recognizing his superior academic performance. His analytical and technical skills were demonstrated through competition achievements, including the Third Prize in the 19th Chinese Graduate Mathematical Modeling Competition (2022) and the Second Prize in the 18th Chinese Electronic Design Competition (2023). Earlier in his academic journey, he was named a Meritorious Winner in the Mathematical Contest in Modeling (MCM) in 2021 and was recognized as an Outstanding Graduate of Tianjin University in 2022. These accomplishments reflect his consistent dedication, innovation, and leadership in engineering and applied mathematics.

Impact and Influence

Ziang Liu’s work has made a tangible impact in both academia and industry. His efforts in improving instruction-following performance in LLMs and optimizing backend systems for enterprise AI applications have proven valuable for real-world implementation. His innovations in intelligent hospital systems demonstrate a commitment to applying advanced AI technologies to enhance societal well-being and operational efficiency.

Legacy and Future Contributions

Poised at the intersection of AI, backend engineering, and applied innovation, Mr. Ziang Liu is emerging as a key contributor to the next generation of AI infrastructure. His hands-on experience with cutting-edge technologies like gRPC, GraphRAG, JWT, and multi-threaded optimization positions him to drive future advancements in AI systems, enterprise platforms, and digital healthcare. With a strong academic record and robust technical expertise, he is well on his way to becoming a leading voice in intelligent systems development.

 

 

Publications

Channel-Dependent Multilayer EEG Time-Frequency Representations Combined with Transfer Learning-Based Deep CNN Framework for Few-Channel MI EEG Classification

Authors: Ziang Liu, Kang Fan, Qin Gu, Yaduan Ruan
Journal: Bioengineering
Year: 2025

Studying Multi-Frequency Multilayer Brain Network via Deep Learning for EEG-Based Epilepsy Detection

Authors: Weidong Dang, Dongmei Lv, Linge Rui, Ziang Liu, Guanrong Chen, Zhongke Gao
Journal: IEEE Sensors Journal
Year: 2021

Rishabh Kumar | Computer Science | Best Researcher Award

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Mr. Rishabh Kumar | Computer Science | Best Researcher Award

IIT Bombay | India

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🌱 Early Academic Pursuits

Mr. Rishabh Kumar’s journey in the field of Computer Science and Engineering began with academic brilliance and passion for innovation. He completed his Bachelor of Technology at IIT (ISM) Dhanbad in 2016, where he laid the foundation for his interest in language technologies under the mentorship of Prof. Sukomal Pal. His intellectual trajectory reached new heights when he joined IIT Bombay as a PhD scholar in 2019. There, under the guidance of Prof. Ganesh Ramakrishnan and Prof. Preethi Jyothi, he began pioneering work in Automatic Speech Recognition (ASR) for low-resource Indian languages, including Sanskrit and Hindi — an effort that merges linguistics with machine learning in service of cultural preservation and accessibility.

👨‍💼 Professional Endeavors

With roles spanning startups to tech giants, Mr. Kumar has applied his research to real-world systems. At Samsung R&D, Bangalore, during his 2023–2024 internship, he developed advanced ASR models for Hindi and spearheaded cross-lingual proper noun recognition using Large Language Models (LLMs). His early stints as Technical Head at Gartley618 Technologies and Lead Developer at Pocketin demonstrate his versatility across full-stack development, iOS applications, and blockchain-based platforms. Additionally, his research internship at Wrig Nanosystems involved Android-based biomedical device integration, showcasing his interdisciplinary reach.

🧠 Contributions and Research Focus

Mr. Kumar’s work is particularly focused on ASR for underrepresented languages, speech-text alignment, and LLM-based improvements in speech technologies. His innovations include:

🔹 Developing Vāgyojaka, a Sanskrit ASR annotation and post-editing tool
🔹 Creating a SpeechQC Agent, a natural language–driven framework for speech dataset validation
🔹 Building ASR pipelines for Indian Parliament (SansadTV)
🔹 Advancing BharatGen Hindi ASR systems

His contributions are documented across top-tier conferences and journals, including ACL, EMNLP, INTERSPEECH, and CSL, with several first-author papers that blend linguistic knowledge and computational innovation.

🏆 Accolades and Recognition

Mr. Kumar’s excellence has been widely recognized. He received the Microsoft Research India Travel Grant to attend INTERSPEECH 2022 and has won prestigious competitions like the State Android App Contest by Jharkhand Government and the National Multilingual Theater Competition. His early achievements include multiple Math Olympiad prizes, an NTSE Level II qualification, and distinctions in Macmillan Olympiads by the University of New South Wales. These accolades reflect his lifelong dedication to problem-solving, innovation, and excellence.

🌍 Impact and Influence

Rishabh Kumar’s research has directly impacted India’s speech technology ecosystem, contributing essential tools and models for building inclusive, vernacular AI systems. His work supports broader national initiatives such as Bhashini and aligns with global goals of linguistic equity in AI. By building publicly usable ASR tools, datasets, and systems for resource-poor languages, he is democratizing access to technology for millions of Indian users.

🔭 Legacy and Future Contributions

As Mr. Kumar approaches the culmination of his PhD, his trajectory signals an exciting future. His legacy lies in fusing computational prowess with cultural sensitivity — bringing Indian linguistic diversity to the forefront of AI innovation. Whether in academia, industry, or open-source collaborations, he is poised to continue shaping the next generation of multilingual ASR systems, LLM-based speech understanding, and resource-efficient AI tools. His work will inspire young researchers to explore the intersection of language, society, and technology.

Publications

📝 Linguistically Informed Automatic Speech Recognition in Sanskrit
 Author: Rishabh Kumar (assumed from your context)
 Journal: Computer Speech & Language (CSL)
 Year: 2025

📝 Beyond Common Words: Enhancing ASR Cross-Lingual Proper Noun Recognition Using LLMs
 Author: Rishabh Kumar (assumed)
 Conference: EMNLP (Findings of the 2024 Conference on Empirical Methods in Natural Language Processing)
 Year: 2024

📝 Linguistically Informed Post-processing for ASR Error Correction in Sanskrit
 Author: Rishabh Kumar
 Conference: INTERSPEECH
 Year: 2022

📝 Vāgyojaka: An Annotating and A Post-Editing Tool for Automatic Speech Recognition
 Author: Rishabh Kumar
 Conference: INTERSPEECH (Show and Tell)
 Year: 2022

📝 Automatic Speech Recognition in Sanskrit: A New Speech Corpus and Modelling Insights
 Author: Rishabh Kumar
 Conference: ACL (Findings of the Association for Computational Linguistics)
 Year: 2021

Hongcheng Xue | Computer Science | Best Academic Researcher Award

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Dr. Hongcheng Xue | Computer Science | Best Academic Researcher Award

College of Information and Electrical Engineering, China Agricultural University | China

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🎓 Early Academic Pursuits

Dr. Hongcheng Xue began his academic journey with a Bachelor's degree in Information and Computational Science from Hunan University of Science and Technology (2014–2018), where he demonstrated leadership as class monitor and held key student roles in the Cultural and Security Departments. His studies emphasized mathematical rigor with courses in analysis, algebra, geometry, and numerical methods. He advanced his education with a Master’s degree in Software Engineering from Inner Mongolia University of Technology (2018–2021), specializing in Data Science Applications. His focus areas included Deep Learning and Computer Vision. During his studies, he actively led his class, served as Vice Chair of the Student Union, and won multiple academic and innovation awards, including:

  • 🥈 Second-class and third-class academic scholarships

  • 🏆 First prize in the university-level Internet+ Innovation and Entrepreneurship Competitions (2018 & 2019)

💼 Professional Endeavors

Dr. Xue served as an Algorithm Engineer at Inner Mongolia Smart Animal Husbandry Co. Ltd. (March–November 2019), where he played a critical role in the development of a sheep delivery early warning detection system using deep learning. His contributions involved:

  •   ➤ Collecting and augmenting training datasets

  •   ➤ Building and fine-tuning neural network models for real-time birthing scene recognition

  •   ➤ Collaborating with frontend and backend teams to deploy the system successfully

  •   ➤ Monitoring system performance and continuously optimizing model behavior

This role showcased his ability to blend theoretical knowledge with real-world applications, especially in agricultural tech solutions.

🧠 Contributions and Research Focus

Dr. Xue’s core research interests lie in deep learning, object detection, and computer vision. His key contributions include:

📄 Published Paper:
“Sheep Delivery Scene Detection Based on Faster-RCNN” – presented at IVPAI 2019

📝 Submitted Research:
“Small Target Modified Car Parts Detection Based On Improved Faster-RCNN” – (Under review)

🔬 Patented Innovation:
Granted a utility model patent for an intelligent trough capable of collecting sheep identification data – Patent No. 202020674737.2

💻 Software Copyright:
Developed and registered a HOG-based Video Pedestrian Detection System V1.0 – Registration No. 2019SR0757039

🏅 Accolades and Recognition

Dr. Xue’s academic journey is marked with consistent excellence and recognition:

  •   ➤ Multiple scholarships during postgraduate studies

  •   ➤ Repeated champion in innovation competitions at university level

  •   ➤ Leadership roles acknowledged both academically and administratively

  •   ➤ Recognized contributor to interdisciplinary applications of AI in agriculture

🌍 Impact and Influence

Dr. Xue’s work reflects a rare synergy between technological innovation and agricultural transformation, especially in remote and rural contexts. His efforts in intelligent livestock management have the potential to significantly enhance productivity, monitoring, and sustainability in smart farming.

He serves as a model for researchers applying AI and deep learning in niche but impactful sectors, bridging gaps between modern tech and traditional industries.

🌟 Legacy and Future Contributions

As a young and dynamic researcher, Dr. Xue’s career is on a promising trajectory. His unique blend of academic rigor, applied research, and patented innovations positions him well for future leadership in AI-driven agricultural systems, smart sensing technologies, and computer vision applications.

He is expected to continue making contributions that transform rural technology landscapes, influence policy through innovation, and inspire future researchers in emerging interdisciplinary fields.

Publications

📄HCTD: A CNN-transformer hybrid for precise object detection in UAV aerial imagery

Authors: Hongcheng Xue, Zhan Tang, Yuantian Xia, Longhe Wang, Lin Li
Journal: Computer Vision and Image Understanding
Year: 2025 (September)

📄 Aggressive behavior recognition and welfare monitoring in yellow-feathered broilers using FCTR and wearable identity tags

Authors: Hongcheng Xue, Jie Ma, Yakun Yang, Hao Qu, Longhe Wang, Lin Li
Journal: Computers and Electronics in Agriculture
Year: 2025

📄 Enhanced YOLOv8 for Small Object Detection in UAV Aerial Photography: YOLO-UAV

Authors: Hongcheng Xue, Xia Wang, Yuantian Xia, Lin Li, Longhe Wang, Zhan Tang
Conference: Proceedings of the International Joint Conference on Neural Networks (IJCNN)
Year: 2024

📄 Open Set Sheep Face Recognition Based on Euclidean Space Metric

Authors: Hongcheng Xue, Junping Qin, Chao Quan, Wei Ren, Tong Gao, Jingjing Zhao, Pier Luigi Mazzeo
Journal: Mathematical Problems in Engineering
Year: 2021

Seunghyun Oh | Computer Science | Best Researcher Award

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Mr. Seunghyun Oh | Computer Science | Best Researcher Award

Yonsei University | South Korea

Author Profile

Google Scholar

🎓 Early Academic Pursuits

Mr. Seunghyun Oh began his academic journey at the Global School of Media, Soongsil University, where he earned his Bachelor of Science degree in February 2025. Throughout his undergraduate studies, he demonstrated a strong aptitude for advanced technical subjects, securing A+ grades in key courses such as Image Processing, Computer Vision, and Machine Learning. His early academic record reflects a solid foundation in both theoretical concepts and applied computing.

💼 Professional Endeavors

Mr. Oh’s professional growth was marked by a series of impactful roles and experiences. In 2023, he joined the Reality Lab at Soongsil University, where he later served as Lab Leader and contributed as an undergraduate researcher until April 2025. His commitment extended beyond academia—he spearheaded a web development training initiative for a Cambodian team to build a school website, showcasing leadership and global engagement. Currently, he is working as a research intern at MAI-LAB, Yonsei University, where he continues to push the boundaries of machine intelligence.

🧠 Contributions and Research Focus

Mr. Oh’s research is centered on computer vision and medical artificial intelligence, with a particular focus on optimization and domain generalization. His notable project, Baseball Player Pose Corrector (BPPC), introduces a refined framework for enhancing 2D pose estimation using 3D motion priors. This work, accepted by ICT-Express (SCIE, IF: 4.1), highlights his innovative approach to human pose estimation in dynamic environments. Additionally, he is actively exploring feature-level domain generalization and disentanglement techniques to improve performance in ultrasound image segmentation, addressing efficiency concerns in medical imaging.

🏅 Accolades and Recognition

Mr. Oh’s dedication to research has already gained peer recognition. In 2024, he delivered an oral presentation at the Annual Symposium of KIPS (ASK 2024), showcasing his work on motion-guided pose correction. His accepted publication in a reputed journal further cements his status as a promising researcher in the field of AI-driven vision systems.

🌍 Impact and Influence

Beyond his technical contributions, Mr. Oh has had a tangible social and educational impact. His web training leadership for Cambodian school developers reflects a blend of technological expertise and social responsibility. Within research communities, he is known for his collaborative spirit and his ability to translate complex models into practical, optimized solutions—particularly in environments where precision and efficiency are critical, such as medical AI.

🔭 Legacy and Future Contributions

As he continues his journey in AI research, Mr. Seunghyun Oh is poised to make significant contributions to medical imaging, optimization algorithms, and domain generalization. His forward-thinking mindset, coupled with technical depth and leadership experience, positions him to be a transformative force in both academic and applied artificial intelligence research. With a strong publication record already underway and promising collaborations in progress, the future holds immense potential for this rising star in computer vision and medical AI.

Publications

📝 Accurate Baseball Player Pose Refinement Using Motion Prior Guidance

Authors: Seunghyun Oh, Heewon Kim
Journal: ICT Express
Year: 2025

📝 Motion Prior-Guided Refinement for Accurate Baseball Player Pose Estimation

Authors: Seunghyun Oh, Heewon Kim
Conference: Annual Conference of KIPS
Year: 2024

Lubin Wang | Computer Science | Best Researcher Award

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Mr. Lubin Wang | Computer Science | Best Researcher Award

Guilin Institute of Information Technology | China

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🎓 Early Academic Pursuits

Mr. Lubin Wang began his academic journey with a Bachelor's degree in Computer Science and Technology at Shanxi Datong University. His early years were marked by active engagement in software development projects, where he not only served as a core developer but also honed critical skills in modular design, teamwork, and leadership. His proactive involvement in both academic and extracurricular technology initiatives laid a strong foundation for his future research career. Notably, he contributed to an open-source database management tool on GitHub that garnered over 2.4k stars, reflecting early promise and innovation.

💼 Professional Endeavors

Following his undergraduate studies, Mr. Wang advanced his expertise by enrolling in a Master's program at Guilin University of Technology, in collaboration with the National Space Science Center of the Chinese Academy of Sciences. Throughout this period, he managed several interdisciplinary projects in high-tech domains including IoT, aerospace data systems, and smart manufacturing. As a project lead and software manager, Mr. Wang took charge of planning, coordinating, and executing complex software systems, displaying not only technical aptitude but also remarkable project governance.

🧠 Contributions and Research Focus

Mr. Wang’s research spans a diverse set of domains unified by a core theme—intelligent systems and automation. He spearheaded the design and implementation of a cloud-based smart printing factory platform that combined neural networks with physical control systems, achieving near-perfect detection accuracy. In the realm of smart cities, he developed a novel traffic-responsive lighting control algorithm and integrated it into a robust management platform supported by SpringBoot and MQTT protocols. His contributions to wind turbine diagnostics involved developing MATLAB-based reliability models, while his work on smart oil testing platforms showcased expertise in OCR, blockchain, and predictive analytics.

🏅 Accolades and Recognition

Mr. Wang has earned numerous accolades that reflect his academic excellence and technical mastery. He secured the First Prize at the National College Student English Vocabulary Challenge in both 2022 and 2023 and was recognized in various programming and language competitions. His academic performance also earned him prestigious scholarships and awards throughout his graduate studies. Beyond these formal recognitions, his influence extends to the online education community, where his Bilibili content channel has amassed thousands of views, demonstrating his ability to communicate complex ideas to broader audiences.

🌍 Impact and Influence

The practical impact of Mr. Wang’s work is far-reaching. His innovations in smart factory and city infrastructure have been piloted at major institutions, contributing to automation, safety, and efficiency. His software and hardware solutions have influenced how industrial faults are detected and managed, while his academic guidance has helped numerous graduate students succeed in their entrance examinations. Mr. Wang’s ability to bridge theory with real-world applications underscores his role as both a thinker and a doer in the field of intelligent systems.

🔮 Legacy and Future Contributions

Looking ahead, Mr. Wang is positioned to continue making transformative contributions to the fields of artificial intelligence, urban computing, and autonomous control systems. His trajectory suggests not only sustained innovation but also leadership in shaping the future of intelligent infrastructure and research-led development. As a mentor, researcher, and technology developer, Mr. Wang is building a legacy defined by curiosity, excellence, and a profound commitment to technological advancement.

Publications

📘 HYFF-CB: Hybrid Feature Fusion Visual Model for Cargo Boxes

Authors: Juedong Li, Kaifan Yang, Cheng Qiu, Lubin Wang, Yujia Cai, Hailan Wei, Qiang Yu, Peng Huang
Journal: Sensors
Year: 2025

📗 BSMD-YOLOv8: Enhancing YOLOv8 for Book Signature Marks Detection

Authors: Long Guo, Lubin Wang (陆斌 王), Qiang Yu, Xiaolan Xie
Journal: Applied Sciences
Year: 2024

📙 DYNet: A Printed Book Detection Model Using Dual Kernel Neural Networks

Authors: Lubin Wang (陆斌 王), Xiaolan Xie, Peng Huang, Qiang Yu
Journal: Sensors
Year: 2023

Fabio Matiussi | Radiology | Innovative Research Award

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Dr. Fabio Matiussi | Radiology | Innovative Research Award

Imaging Institute of Southern Switzerland | Switzerland

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🎓 Early Academic Pursuits

Dr. Fabio Mattiussi’s journey began with a firm commitment to healthcare and imaging sciences. He earned his degree in Medical Radiologic Technology from the University of Insubria in 2016, which laid the foundation for his clinical expertise. Eager to expand his horizons, he pursued advanced studies in healthcare system administration and health management, followed by a strategic academic leap into the realm of computer engineering. These steps reflect his unique vision to combine traditional radiology with emerging digital technologies.

🏥 Professional Endeavors

Dr. Mattiussi has served across a range of reputable healthcare institutions throughout Italy and Switzerland, building a versatile portfolio in diagnostic imaging. From private clinics in the Varese province to key positions at ASST Sette Laghi and now at the Ente Ospedaliero Cantonale in Lugano, he has mastered the art and science of radiology. His proficiency spans traditional radiography, computed tomography (CT), and magnetic resonance imaging (MRI), making him a trusted expert in patient diagnostics.

🤖 Contributions and Research Focus

Blending clinical know-how with advanced data science, Dr. Mattiussi has ventured into uncharted territory—merging machine learning with diagnostic radiology. With certifications from top institutions like Meta, IBM, Google, and DataMasters, he has cultivated deep expertise in neural networks, Python programming, and AI applications in medical imaging. His current focus lies in developing intelligent systems that can revolutionize image interpretation, automate detection, and significantly enhance diagnostic accuracy.

🏅 Accolades and Recognition

While his formal recognitions are still on the rise, Dr. Mattiussi’s consistent pursuit of innovation has earned him recognition within both the medical and tech education spheres. His completion of numerous elite certifications and active engagement in online scientific communities marks him as a forward-thinking professional committed to lifelong learning and impactful research.

🌍 Impact and Influence

Dr. Mattiussi’s influence spans both clinical and technological domains. His ability to work seamlessly across languages and disciplines empowers him to contribute to international healthcare dialogues. By staying at the cutting edge of both patient care and digital innovation, he serves as a bridge between traditional radiology departments and the fast-evolving world of AI-driven diagnostics.

🔮 Legacy and Future Contributions

Dr. Fabio Mattiussi is poised to leave a legacy as a pioneer in the integration of artificial intelligence into medical imaging. His academic rigor, technical acumen, and compassionate healthcare experience equip him to lead future innovations in radiology. As machine learning continues to redefine medical practices, Dr. Mattiussi is set to be at the forefront—developing tools, systems, and protocols that will shape the future of global healthcare.

Publications

📄  Use of Open-Source Large Language Models for Automatic Synthesis of the Entire Imaging Medical Records of Patients: A Feasibility Study

Authors: Fabio Mattiussi, Francesco Magoga, Simone Schiaffino, Vittorio Ferrari, Ermidio Rezzonico, Filippo Del Grande, Stefania Rizzo

Journal: Tomography

Year: 2025

Jianghong Zhao | Engineering | Best Researcher Award

Published on by Book of Award

Prof. Jianghong Zhao | Engineering | Best Researcher Award

Beijing University of Civil Engineering and Architecture | China

Author Profile

Scopus

🌱 Early Academic Pursuits

Prof. Jianghong Zhao's academic journey began with a deep curiosity about maps and spatial data. She earned her Bachelor’s degree in Cartography from Wuhan Technical University of Surveying and Mapping in 1998, followed by a Master’s in Cartography and Geographic Information Engineering from Wuhan University in 2001. Her academic pursuits culminated in a Ph.D. in Photogrammetry and Remote Sensing from the same university in 2012. Her passion for international collaboration led her to the University of Massachusetts Boston as a visiting scholar, where she expanded her horizons in geospatial technology.

🧭 Professional Endeavors

Starting her academic career at Beijing University of Civil Engineering and Architecture in 2001, Prof. Zhao steadily rose from Lecturer to Full Professor. Since 2015, she has served as the Vice Dean of the School of Surveying and Mapping. Her responsibilities extend beyond teaching and research—she actively contributes to national academic committees, helps design curriculum reforms, and mentors both students and junior faculty with great enthusiasm.

🔬 Contributions and Research Focus

Prof. Zhao’s research has been at the forefront of geographic information science. Her expertise lies in 3D point cloud data processing, indoor and outdoor spatial modeling, and deep learning-driven geospatial analysis. She has led and participated in over 30 major research projects funded by the National Natural Science Foundation of China, government agencies, and academic institutions. Her innovations in semantic segmentation and intelligent modeling have provided powerful tools for urban planning, heritage preservation, and emergency response mapping.

🏆 Accolades and Recognition

A decorated academic, Prof. Zhao has earned numerous prestigious awards. These include multiple first and second prizes from the China Geographic Information Science and Technology Progress Awards, as well as the Beijing Science and Technology Progress Award. She has been recognized as an Excellent Teacher, Young Academic Star, and Outstanding Mentor in national competitions. Her books, patents, and teaching excellence have set benchmarks in the academic community.

🌍 Impact and Influence

Prof. Zhao’s impact is both wide and deep. Her scholarly work has been published in top-tier international journals, presented at global conferences, and adopted in practical applications across industries. Through her roles in international organizations such as the ICA and ISDE, she has contributed to shaping global standards and research directions in geoinformatics. Her mentorship has empowered a new generation of geospatial scientists, many of whom have won national honors under her guidance.

🌟 Legacy and Future Contributions

With a career defined by innovation, leadership, and compassion, Prof. Jianghong Zhao is not only a trailblazer in geographic information science but also a visionary educator. She continues to inspire through her work on integrating emerging technologies like AI and remote sensing into geospatial research. As she looks to the future, her legacy is clear—empowering students, advancing science, and transforming how we understand and interact with the world around us.

Publications

📄A Cross-Modal Attention-Driven Multi-Sensor Fusion Method for Semantic Segmentation of Point Clouds

Authors: Huisheng Shi, Xin Wang, Jianghong Zhao, Xinnan Hua
Journal: Sensors
Year: 2025

📄Overview and Prospects of Visibility Analysis Approaches

Authors: Jianghong Zhao, Ailin Xu, Xueqing Zhang, Yunhui Zhang, Yihong Zhang, Mengtian Cao, 黄明 (Huang Ming)
Journal: Proceedings
Year: 2024

📄MSFA-Net: A Multiscale Feature Aggregation Network for Semantic Segmentation of Historical Building Point Clouds

Authors: Ruiju Zhang, Yaqian Xue, Jian Wang, Daixue Song, Jianghong Zhao, Lei Pang
Journal: Buildings
Year: 2024

📄Advances in Spatiotemporal Graph Neural Network Prediction Research

Authors: Jianghong Zhao, Yi Wang, Xintong Dou, Xin Wang, Ming Guo, Ruiju Zhang, Haimeng Li
Journal: International Journal of Digital Earth
Year: 2023

📄An Automated Multi-Constraint Joint Registration Method for Mobile LiDAR Point Cloud in Repeated Areas

Authors: Chutian Gao, Ming Guo, Jianghong Zhao, Peng Cheng, Yuquan Zhou, Tengfei Zhou, Kecai Guo
Journal: Measurement
Year: 2023

 

Yeeshtdevisingh Hosanee | Computer Science | Women Research Award

Published on by Book of Award

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