Leema Nelson | Computer Science | Research Excellence Award

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Dr. Leema Nelson | Computer Science | Research Excellence Award

Chitkara University | India 

Dr. Leema Nelson is an accomplished researcher whose scholarly contributions span machine learning, clinical decision support systems, composite materials, signal processing, and intelligent diagnostic frameworks. With a total of 1206 citations, an h-index of 17, and 29 i10-index publications, her research demonstrates both depth and sustained impact across interdisciplinary domains. She has produced numerous high-quality peer-reviewed articles, many in leading Elsevier journals such as Applied Soft Computing and Materials & Design, focusing on neural network optimization, characterization of metal-matrix composites, wear modelling, and advanced computational methods. Her work in clinical data classification, including diabetes and PCOS diagnosis, highlights the integration of artificial intelligence into healthcare decision-making. In recent years, she expanded her research into video smoke detection, cyber-security–based email filtering, audio source separation, and welding parameter optimization using intelligent algorithms. Her studies in deepfake detection, text recognition, and clinical support systems reflect her continuing advancements in data-driven AI models. She has also contributed extensively to IEEE conferences, presenting innovations in masked face detection, ultrasound image analysis, mobile app frameworks, and disease prediction models. Overall, her scientific output reflects strong productivity, interdisciplinary expertise, and meaningful contributions to both computational intelligence and applied engineering research.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Jibinsingh, B. R., & Nelson, L. (2025). FL-WOSP: Federated learning with Walrus Optimization for sepsis prediction using MIMIC-III physiological and clinical data. Pattern Recognition. Advance online publication.

Batra, H., & Nelson, L. (2024). ESD: E-mail spam detection using cybersecurity-driven header analysis and machine learning-based content analysis. International Journal of Performability Engineering, 20(4).

Nelson, L. (2024). Data-driven clinical decision support system using neural network topology optimization for PCOS diagnosis. Journal of Soft Computing and Data Mining.

Batra, H., & Nelson, L. (2024). A three-stage deepfake detection framework using deep learning models with multimedia data. International Journal of Intelligent Systems and Applications.

Shanmuga Priya, M., Pavithra, A., & Leema, N. (2024). Character/word modelling: A two-step framework for text recognition in natural scene images. Computer Science.

Batra, H., & Nelson, L. (2023). DCADS: Data-driven computer aided diagnostic system using machine learning techniques for polycystic ovary syndrome. International Journal of Performability Engineering, 19(3).

Kumar, V. A., Rao, C. V. R., & Leema, N. (2023). Audio source separation by estimating the mixing matrix in underdetermined condition using successive projection and volume minimization. International Journal of Information Technology, 15(4), 1831–1844.

Ramesh, A., Sivapragash, M., Ajith Kumar, K. K., & Leema, N. (2023). Investigating the quality of TIG-welded aluminium alloy 5086 using the online acoustic emission and optimization of welding parameters using global best-based modified artificial bee colony algorithm. Transactions of the Indian Institute of Metals, 1–14.

Pranshu Kumar Soni, & Leema, N. (2023). PCP: Profit-driven churn prediction using machine learning techniques in banking sector. International Journal of Performability Engineering, 19(5), 303–311.

Vettum Perumal, S., Suyamburajan, V., Chidambaranathan, V. S., & Nelson, L. (2023). Characterization of microstructure and mechanical behaviour in activated tungsten inert gas welded dissimilar AA joint of AA 5083 and AA 6061 alloys. Journal of the Institution of Engineers (India): Series D, 1–9.

Patruni Rajshekhar Rao | Computer Science | Best Researcher Award

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Mr. Patruni Rajshekhar Rao | Computer Science | Best Researcher Award

FTD Infocom Pvt Ltd | India

Mr. Patruni Rajshekhar Rao is an avionics research professional whose work integrates test and verification engineering, data analysis, and safety-critical system evaluation across aerospace platforms. His contributions span functional RTL verification, aerospace data analysis, and reliability assessment of embedded systems. His early work involved functional verification of ARINC818 protocol IP cores, where he designed assertion-based test benches using VHDL and file-driven debugging to enhance precision in timing-sensitive validation. He later expanded into flight data analysis for advanced aircraft systems such as the SARAS platform, performing hardware–software integration testing, developing low-level test cases, and analyzing stall-warning system performance. His research also includes pioneering efforts in software health management, where he explored self-healing software systems using AI-driven methods to automate fault detection and recovery in avionics architectures. He has contributed to safety-critical processes aligned with DO-178B and DO-254 standards, including MCDC-level testing for auto-generated code in A-FADEC systems and performing dynamic and static analysis to identify and mitigate software defects. Across conferences and journals, he has published studies on verification methodologies, safety criteria, IP-core validation procedures, and AI-based static analysis, reinforcing his role in advancing dependable avionics engineering.

Profile : Scopus

Featured Publications

Nanda, M., & Rao, P. R. (2018, May 17). Implementation and verification of an asynchronous FIFO under boundary conditions (Paper ID: NCESC18-181). National Conference on Electronics, Signals and Communication (NCESC-2018), GSSS Institute of Engineering & Technology for Women, Mysore.

Nanda, M., Jayanthi, J., & Rao, P. R. (2018, May 18–19). Aerospace compliant test bench to verify critical aerospace functionalities (Paper ID: CRP18-1007). 3rd International Conference on Recent Trends in Electronics, Information and Communication Technology (RTEICT-2018), Department of Electronics and Communication Engineering, SVCE, Bangalore.

Nanda, M., & Rao, P. R. (2018). An approach for generating self-checking test bench. International Journal for Research in Applied Science and Engineering Technology, 6(6). (Paper ID: IJRASET17914).

Nanda, M., & Rao, P. R. (2018). Aerospace data bus safety criteria as per DO-254. International Journal of Research and Innovation in Applied Science, 3(6).

Nanda, M., & Rao, P. R. (2018). A procedure to verify and validate an FPGA level testing as per DO-254. International Journal of Research and Innovation in Applied Science, 3(6).

Nanda, M., & Rao, P. R. (2018). Verification cases and procedure for IP-core development. International Journal of Engineering Research and Advanced Technology. (ISSN 2454-6135).

Simy Baby | Engineering | Best Researcher Award

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Mrs. Simy Baby | Engineering | Best Researcher Award

National Institute of Technology | India

Mrs. Simy Baby is an emerging researcher whose scholarly contributions center on semantic communications, machine learning, and computer vision, with a strong emphasis on communication-efficient feature extraction for edge inference tasks. She has authored 2 documents, received 2 citations, and holds an h-index of 1, reflecting the growing impact of her research in advanced communication technologies. Her publications in SCI-indexed journals, including Elsevier’s Computers & Electrical Engineering and IEEE Transactions on Cognitive Communications and Networking, demonstrate her commitment to innovation and excellence. Her study, “Complex Chromatic Imaging for Enhanced Radar Face Recognition”, introduced a novel complex-valued representation preserving amplitude and phase information of mmWave radar signals, achieving 99.7% recognition accuracy. Another major contribution, “Complex-Valued Linear Discriminant Analysis on mmWave Radar Face Signatures for Task-Oriented Semantic Communication”, proposed a CLDA-based encoding framework that improved feature interpretability and robustness under varying channel conditions. Her ongoing projects explore Data Fusion Discriminant Analysis (DFDA) for multi-view activity recognition and Semantic Gaussian Process Regression (GPR) for vehicular pose estimation, advancing the integration of semantic communication and computer vision. Mrs. Simy Baby’s research represents a vital step toward the development of intelligent, efficient, and adaptive communication systems for next-generation technologies.

Profiles : Scopus | Orcid | Google Scholar

Featured Publications

Baby, S. M., & Gopi, E. S. (2025). Complex valued linear discriminant analysis on mmWave radar face signatures for task-oriented semantic communication. IEEE Transactions on Cognitive Communications and Networking.

Baby, S. M., & Gopi, E. S. (2025, April). Complex chromatic imaging for enhanced radar face recognition. Computers and Electrical Engineering.

Victor R.L. Shen | Computer Science | Best Researcher Award

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Prof. Dr. Victor R.L. Shen | Computer Science | Best Researcher Award

National Taipei University | Taiwan

Prof. Dr. Victor R. L. Shen is a highly accomplished scholar and Professor Emeritus in the Department of Computer Science and Information Engineering at National Taipei University, Taiwan. With an extensive academic background, including a Ph.D. in Computer Science from National Taiwan University, he has dedicated decades to advancing research and education in artificial intelligence, Petri net theory, fuzzy logic, cryptography, e-learning systems, IoT, and intelligent computing. Over his distinguished career, he has published 78 documents that collectively received 840 citations across 696 sources, earning him an h-index of 15, reflecting both the depth and impact of his contributions. Beyond his prolific research, Prof. Shen has held prominent academic leadership positions, including Dean, Chairman, and CEO roles at National Taipei University and Ming Chi University of Technology, shaping academic programs and fostering innovation. His global recognition includes visiting professorships, membership in leading professional organizations such as IEEE, ACM, and IET, and numerous prestigious awards for teaching, research, and innovation. With sustained contributions in smart systems, advanced computing, and AI-driven education, Prof. Shen continues to influence the global academic community, leaving a legacy of excellence in both research and pedagogy.

Profiles : Scopus | Orcid

Featured Publications

Yang, C.-Y., Lin, Y.-N., Shen, V. R. L., Shen, F. H. C., & Lin, Y.-C. (2025). Petri net modeling and analysis of an IoT-enabled system for real-time monitoring of eggplants. Systems Engineering.

Yang, C.-Y., Lin, Y.-N., Shen, V. R. L., Shen, F. H. C., & Jheng, W.-S. (2025). A novel IoT-enabled system for real-time monitoring home appliances using Petri nets. IEEE Canadian Journal of Electrical and Computer Engineering.

Chang, J.-C., Chen, S.-A., & Shen, V. R. L. (2024). Smart bird identification system based on a hybrid approach: Petri nets, convolutional neural and deep residual networks. Multimedia Tools and Applications, 83(12), 34795–34823.

Yang, C.-Y., Lin, Y.-N., Shen, V. R. L., Tung, Y.-C., & Lin, J.-F. (2024). A novel IoT-enabled system for real-time face mask recognition based on Petri nets. IEEE Internet of Things Journal, 11(4), 6992–7001.

Yang, C.-Y., Lin, Y.-N., Wang, S.-K., Shen, V. R. L., & Lin, Y.-C. (2024). An edge computing system for fast image recognition based on convolutional neural network and Petri net model. Multimedia Tools and Applications, 83(5), 12849–12873.

Yang, C.-Y., Hwang, M.-S., Tseng, Y.-W., Yang, C.-C., & Shen, V. R. L. (2024). Advancing financial forecasts: Stock price prediction based on time series and machine learning techniques. Applied Artificial Intelligence, 38(1), 1–24.

Lin, Y.-N., Wang, S.-K., Chiou, G.-J., Yang, C.-Y., Shen, V. R. L., & Su, Z. Y. (2023). Development and verification of an IoT-enabled air quality monitoring system based on Petri nets. Wireless Personal Communications, 131(1), 63–87.*

 

Ziang Liu | Engineering | Best Researcher Award

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Mr. Ziang Liu | Engineering | Best Researcher Award

Nanjing University | China

Author Profile

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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

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

Hongfei Yang | Engineering | Best Researcher Award

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Assoc Prof Dr. Hongfei Yang | Engineering | Best Researcher Award

Shihezi University | China

Author Profile

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🌱 Early Academic Pursuits

Dr. Hongfei Yang’s academic journey is marked by an impressive foundation in engineering and scientific disciplines. He earned his Bachelor's degree in Mechanical Design, Manufacturing, and Automation from Dalian University in 2016. Following this, he pursued his Master’s in Mechanical Design and Theory at Jilin University, complemented by a joint training program at Cambridge University. These early years laid a solid groundwork in mechanical design, equipping him with a unique blend of theoretical knowledge and practical skills.

💼 Professional Endeavors

Currently an Associate Professor in Electronic Information Engineering at Shihezi University, Dr. Yang has dedicated his career to advancing precision engineering and measurement technology. His experience includes a rigorous doctoral program in Testing and Measurement Technology at Jilin University, where he focused on developing innovative solutions in instrument technology. Dr. Yang's professional path reflects his commitment to impactful research and teaching in electronic and mechanical engineering fields.

📚 Contributions and Research Focus

Dr. Yang’s research is distinguished by its focus on magnetic sensing and machine vision, especially in applications for unstructured environments and deep-earth observations. As the first author of 11 academic papers with a cumulative impact factor of 59.4, he has made substantial contributions to journals like IEEE Transactions on Geoscience and Remote Sensing and IEEE Sensors Journal. His work addresses pressing challenges in instrument measurement, such as developing methods for identifying rail defects and creating robust magnetic sensing systems. His expertise extends to multiple patents, demonstrating practical solutions for applications ranging from long-term monitoring in extreme environments to automated mushroom collection devices.

🏆 Accolades and Recognition

Dr. Yang’s contributions have been recognized with numerous honors. Among them are the prestigious National Scholarship for Doctoral Students in China, awarded by the Ministry of Education, and Jilin University's First-Class Doctoral Excellence Scholarship. His scholarly achievements and dedication have earned him the title of "Outstanding Graduate" and the Geological Instrument Scholarship from Jilin University. These accolades reflect his exceptional research performance and his ongoing impact in his field.

🌍 Impact and Influence

Dr. Yang’s influence extends beyond academia, as he actively participates in shaping engineering knowledge as a reviewer for top journals like IEEE Transactions on Instrumentation and Measurement. His work on projects, such as the National Natural Science Foundation of China project on environmental recognition for engineering vehicles, has pushed the boundaries of how advanced data processing can improve machine vision in complex environments. His contributions to deep borehole observation technology are advancing our understanding of deep-earth environments, with applications in various scientific and industrial domains.

🏅 Legacy and Future Contributions

Dr. Yang’s career represents a blend of innovation, interdisciplinary expertise, and real-world applications. His research in precision engineering, machine vision, and magnetic sensing continues to inspire advancements in technology and scientific exploration. His legacy lies in both his published works and his commitment to teaching, mentoring, and advancing engineering research. Looking forward, Dr. Yang is set to further enrich the field of electronic information engineering, leaving an enduring impact on the next generation of scientists and engineers.

 

Publications

📝 SwinLabNet: Jujube Orchard Drivable Area Segmentation Based on Lightweight CNN-Transformer Architecture

Authors: Mingxia Liang, Longpeng Ding, Jiangchun Chen, Liming Xu, Xinjie Wang, Jingbin Li, Hongfei Yang
Journal: Agriculture
Year: 2024

📝 Neural Network-Based 3D Point Cloud Detection of Targets in Unstructured Environments

Authors: D. Wang, H. Yang, Z. Yao, Z. Chang, Y. Wang
Journal: Advances in Mechanical Engineering
Year: 2024

📝 MI-FPD: Magnetic Information of Free Precession Signal Data Measurement Method for Bell-Bloom Magnetometer

Authors: D. Bai, L. Cheng, Y. Sun, H. Yang, Y. Wang
Journal: IEEE Transactions on Geoscience and Remote Sensing
Year: 2024

📝 Efficient Measurement of Free Precession Frequency in Bell-Bloom Atomic Magnetometers

Authors: D. Bai, Y. Zhou, Y. Sun, H. Yang, Y. Wang
Journal: IEEE Transactions on Instrumentation and Measurement
Year: 2024

📝 EHA-YOLOv5: An Efficient and Highly Accurate Improved YOLOv5 Model for Workshop Bearing Rail Defect Detection Application

Authors: J. Hu, H. Yang, J. He, D. Bai, H. Chen
Journal: IEEE Access
Year: 2024

 

Ousmane Thiare | Computer Science | Best Scholar Award

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Prof Dr. Ousmane Thiare | Computer Science | Best Scholar Award

Université Gaston Berger | Senegal

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Early Academic Pursuits 🎓

Professor Ousmane Thiare's academic journey began at Gaston Berger University (UGB), Senegal, a prestigious institution where he would later spend much of his career. He joined UGB in 1994 and demonstrated academic excellence, earning a Diploma of Advanced Studies (DEA) in Applied Mathematics in 2000. Eager to expand his knowledge, he continued his studies abroad at the Polytechnic School of the François Rabelais University of Tours (Polytech'Tours), obtaining a second DEA in Computer Science in 2002. His academic pursuits culminated in 2007 when he earned a Doctorate in Computer Science from CY Cergy Paris University in France.

Professional Endeavors 👨‍🏫

After completing his studies, Professor Thiare embarked on a teaching career that began right at the institution where he was trained, UGB. In 2002, he started as a Full Assistant in Computer Science. His dedication and expertise quickly saw him rise through the ranks, becoming an Assistant Professor in 2008 and later a Lecturer with Accreditation (HDR) from 2010 to 2015. Beyond Senegal, his teaching experience extended to Nigeria, where he served as an Associate Professor at the African University of Science and Technology (AUST) in Abuja from 2014. In 2015, Professor Thiare was promoted to Full Professor at UGB, a position of immense respect. By April 2021, he was further recognized as a Full Professor of Exceptional Class of Universities, underscoring his contributions to academia.

Contributions and Research Focus 🔬

Professor Thiare's contributions extend beyond teaching. His research spans critical areas such as Computer Science, Information and Communication Technologies (ICT), and Mathematics. As Head of the Computer Science Department at UGB's UFR of Applied Sciences and Technology between 2007 and 2009, he influenced the direction of academic programs. He was instrumental in coordinating the Third Cycle in Computer Science in 2011 and later served as Director of the Ousmane Seck Computing Center from 2013. From 2017 to 2020, Professor Thiare led the African Center of Excellence for Mathematics, Computer Science, and ICT (CEA-MITIC), a World Bank-funded project aimed at providing world-class education in STEM fields. His leadership in this $8 million initiative was crucial in developing skilled professionals in ICT, Computer Science, and Mathematics across Africa.

Accolades and Recognition 🏅

Professor Thiare’s accomplishments have garnered numerous accolades. In 2021, he was elected as a Full Member of the National Academy of Sciences and Technology of Senegal (ANSTS), in the Fundamental, Applied, and Innovation Sciences (SFAI) section, recognizing his significant contributions to science and technology. As an Expert Evaluator for the National Authority for Quality Assurance of Higher Education (ANAQ-Sup) since 2014, he has contributed to maintaining high educational standards across Senegal. He also serves on the Scientific and Pedagogical Council of the Doctoral School of Science and Technology at UGB, reflecting his influence in shaping future academic research and educational programs.

Impact and Influence 🌍

From May 2018 to March 2023, Professor Thiare served as Rector of Gaston Berger University, leading one of Senegal's foremost institutions. As Rector, he played a pivotal role in guiding the university’s academic programs, fostering partnerships with international institutions, and ensuring the adoption of cutting-edge technologies to make UGB globally competitive. His role as Principal Authorizing Officer of UGB’s budget allowed him to influence not only academic policy but also the strategic use of financial resources to promote education and research. Under his leadership, UGB also spearheaded major projects such as the Mastercard Foundation Scholars Program, which secured nearly $38 million in funding to train 1,000 scholars, 70% of whom are women, in digital technology, health, agriculture, and engineering by 2031. This initiative has empowered young African talents to make meaningful contributions to their communities.

Legacy and Future Contributions 🌟

Professor Thiare's legacy as a trailblazer in African higher education is well-established. Through his work at CEA-MITIC, UGB, and various national and international platforms, he has helped shape the landscape of STEM education in Africa. His dedication to improving the quality of higher education, combined with his strategic leadership in academic programs and technological innovation, has left an indelible mark.

 

Publications

📄 Hardware Development and Evaluation of Multihop Cluster-Based Agricultural IoT Based on Bluetooth Low-Energy and LoRa Communication Technologies
Authors: Effah, E., Ghartey, G., Aidoo, J.K., Thiare, O.
Journal: Sensors
Year: 2024

📄 Data collection in IoT networks: Architecture, solutions, protocols and challenges
Authors: Abba Ari, A.A., Aziz, H.A., Njoya, A.N., Thiare, O., Mohamadou, A.
Journal: IET Wireless Sensor Systems
Year: 2024

📄 A comparative study of Machine Learning and Deep Learning methods for flood forecasting in the Far-North region, Cameroon
Authors: Dtissibe, F.Y., Ari, A.A.A., Abboubakar, H., Mohamadou, A., Thiare, O.
Journal: Scientific African
Year: 2024

📄 Enabling privacy and security in Cloud of Things: Architecture, applications, security & privacy challenges
Authors: Abba Ari, A.A., Ngangmo, O.K., Titouna, C., Mohamadou, A., Gueroui, A.M.
Journal: Applied Computing and Informatics
Year: 2024

📄 A collaborative WSN-IoT-Animal for large-scale data collection
Authors: Abdoul Aziz, H., Abba Ari, A.A., Ndam Njoya, A., Mohamadou, A., Thiare, O.
Journal: IET Smart Cities
Year: 2024

 

Nam-Phuong Tran | Computer Science | Best Researcher Award

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Mr. Nam-Phuong Tran | Computer Science | Best Researcher Award

Chung-Ang University | South Korea

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Early Academic Pursuits

Mr. Nam-Phuong Tran began his academic journey at Hanoi University of Science and Technology, Vietnam, where he pursued a Bachelor of Engineering in Computer Science, completing it from August 2015 to June 2020. His thesis, "Spatio-Temporal Dynamics of the Labor Market," showcased his early dedication to research. Subsequently, he pursued an MSc of Science in Computer Science at Chung-Ang University, Seoul, Korea, focusing on QoE Management for Video Streaming Systems over IRS-aided RSMA Networks under the guidance of Professor Sungrae Cho.

Professional Endeavors

Tran has diversified professional experience, ranging from software engineering to research roles. He worked as a Software Engineer at Viettel Digital Service and as a Graduate Research Assistant at the Ultra-Intelligent Computing/Communication Lab, Chung-Ang University. Additionally, he has served as a Software Developer, Data Scientist Intern, and Undergraduate Research Assistant, gaining exposure to various facets of computer science and engineering.

Contributions and Research Focus

Tran's research primarily revolves around improving Quality of Experience (QoE) in communication networks, focusing on topics such as wireless resource allocation, bitrate adaptation, and low-latency protocols. His expertise spans intelligent reflecting surfaces, rate-splitting multiple access, IoT, deep learning, reinforcement learning, federated learning, and multimedia over wireless networks. He has also delved into big data analytics, including data crawling, mining, visualization, and predictive analytics.

Accolades and Recognition

Tran's dedication to academia has been acknowledged through numerous awards and scholarships, including the Chung-Ang University Young Scientist Scholarship, Brain Korea 21 Graduate School Research Scholarship, Daewoong AI Big Data Scholarship, and the Shinhan Bank Scholarship. He has also received recognition for his programming skills and outstanding thesis presentation.

Impact and Influence

Tran's research contributions, particularly in the realm of improving QoE in communication systems, have the potential to influence the development of more efficient and user-centric network protocols. His work in wireless resource allocation, bitrate adaptation, and low-latency protocols could lead to significant advancements in multimedia streaming, IoT, and metaverse applications, shaping the future of communication technologies.

Legacy and Future Contributions

Tran's legacy may lie in his interdisciplinary approach to addressing challenges in communication networks and big data analytics. His research outputs and professional endeavors are poised to contribute to advancements in wireless communication, machine learning applications, and data-driven decision-making. With his demonstrated commitment to excellence and innovation, he is likely to continue making notable contributions to the field of computer science and engineering, both in academia and industry.

Notable Publications

Joint wireless resource allocation and bitrate adaptation for QoE improvement in IRS-aided RSMA-enabled IoMT streaming systems 2024

Privacy-Preserving Traffic Flow Prediction: A Split Learning Approach 2023

Delay-constrained quality maximization in RSMA-based video streaming networks 2022

A Survey on Intelligent Reflecting Surface-aided Non-Orthogonal Multiple Access Networks 2022

A Survey on Passive Beamforming using Statistical State Information in Intelligent Reflecting Surface Assisted Networks 2022

 

 

Sushovan Khatua | Computer Science | Best Researcher Award

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Mr. Sushovan Khatua | Computer Science | Best Researcher Award

Maulana Abul Kalam Azad University of Technology | India

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Early Academic Pursuits

Mr. Sushovan Khatua embarked on his academic journey with a zeal for excellence, evident from his stellar academic record. Graduating with distinction from various institutions, including  KU, and VU, he laid a robust foundation in computer science, paving the way for his future endeavors.

Professional Endeavors

With a blend of academic prowess and practical experience, Mr. Khatua delved into diverse professional undertakings. From internships at renowned organizations to roles in software testing and quality assurance at AVALGATE SOFTWARE LLP, he honed his skills across different domains.

Contributions and Research Focus

Mr. Khatua's contributions extend to both academia and industry, with a focus on cutting-edge research in areas such as Internet of Vehicular Things (IoVT), cloud computing, combinatorial optimization, and machine learning. His publications and collaborative projects demonstrate his dedication to addressing real-world challenges through innovative solutions.

Accolades and Recognition

Mr. Khatua's achievements speak volumes about his academic and research excellence. Notable accolades include qualifing GATE (Computer Science) and receiving the Best Paper Award at the 5th Regional Science and Technology Congress, Govt. of West Bengal. His scholarly contributions have been recognized in esteemed journals and conferences.

Impact and Influence

Mr. Khatua's research endeavors have made a significant impact, particularly in the realms of vehicular communications, sustainable logistics, and optimization problems. His collaborative efforts with renowned institutions and industry partners underscore his commitment to driving positive change through interdisciplinary collaboration.

Legacy and Future Contributions

As Mr. Khatua continues his pursuit of knowledge and innovation, his legacy is poised to inspire future generations of researchers and practitioners in the fields of computer science and engineering. With a focus on sustainability, resilience, and technological advancement, he aims to contribute meaningfully to society and academia, leaving an indelible mark on the landscape of research and innovation.

Notable Publications

SoVEC: Social Vehicular Edge Computing-based Optimum Route Selection 2024

Leveraging Machine Learning of Indian Railways Public Procurement Data for Managerial Insights 2023

Dew Computing-Based Sustainable Internet of Vehicular Things 2023