Eric Nizeyimana | Computer Science | Best Researcher Award

Dr. Eric Nizeyimana | Computer Science | Best Researcher Award

Lecturer from University of Rwanda, Rwanda

Dr. Eric Nizeyimana is a Rwandan researcher and academic specializing in Internet of Things (IoT) and embedded systems. He has built a career grounded in advanced technological solutions for environmental and infrastructural challenges, particularly in air pollution monitoring and data-driven IoT applications. His recent work includes developing decentralized, predictive frameworks using blockchain, machine learning, and IoT technologies to track pollution spikes in real time. With extensive research and teaching experience across African and Asian academic institutions, including the University of Rwanda and Seoul National University, he brings a global perspective to technological development. Dr. Nizeyimana is known for integrating practical and scalable systems with academic rigor, earning recognition for his innovative and impactful work. His contributions have been published in several reputable journals, and he continues to influence the next generation of engineers and scientists through both classroom teaching and research mentorship. Fluent in English, French, Kinyarwanda, and Swahili, and having held leadership roles in academic committees and church communities, he blends technical excellence with interpersonal and organizational strengths. As a proactive researcher and educator, Dr. Nizeyimana continues to push the boundaries of IoT systems in addressing societal issues, especially in transportation, environmental sustainability, and smart infrastructure.

Professional Profile

Education

Dr. Eric Nizeyimana has pursued a progressive academic path centered on engineering, mathematical sciences, and emerging technologies. He earned his Ph.D. in Internet of Things (IoT) with a specialization in Embedded Systems from the University of Rwanda – College of Science and Technology (UR-CST), under the African Center of Excellence in Internet of Things (ACEIoT), in collaboration with Seoul National University (SNU), South Korea, from 2020 to 2024. His doctoral research focused on environmental monitoring systems using IoT and edge computing technologies, particularly addressing air pollution monitoring and predictive analytics. Prior to this, he completed a master’s program in Mathematical Sciences at the African Institute for Mathematical Sciences (AIMS-Cameroon) in 2015. His academic foundation was laid through a bachelor’s degree in Computer Engineering from the Kigali Institute of Science and Technology (KIST), which he completed in 2012. This strong foundation in both engineering and mathematics positioned him well for his advanced research in smart systems and applied technologies. His educational journey reflects a consistent focus on interdisciplinary innovation, bridging computational science, real-world data systems, and environmental sustainability. Through scholarships and competitive academic grants, Dr. Nizeyimana has demonstrated academic excellence and international competitiveness.

Professional Experience

Dr. Eric Nizeyimana has accumulated rich professional experience in academia and research-focused technical roles. As of October 2024, he serves as a Lecturer at the University of Rwanda – College of Science and Technology, where he also previously held the role of Assistant Lecturer between August 2015 and May 2017. In this capacity, he has taught diverse subjects, including Embedded Computer Systems, Artificial Intelligence, Java Programming, and Computer Programming. He has also supervised undergraduate and graduate research projects and contributed to proposal writing and curriculum development. From April to October 2023, Dr. Nizeyimana was a researcher at Seoul National University, where he developed IoT-based systems for environmental monitoring, optimized embedded systems, and analyzed complex data. Between 2019 and 2023, he worked as an IT Analyst and Training Officer at the African Institute for Mathematical Science (AIMS), coordinating IT infrastructure, providing technical training, and managing secure digital environments. Earlier, from 2017 to 2018, he held the role of IT Officer and System Administrator at AIMS in both Rwanda and Cameroon. These roles highlight his hybrid expertise in teaching, systems design, network security, and capacity building, establishing him as a technically proficient and educationally driven professional.

Research Interests

Dr. Eric Nizeyimana’s research interests lie at the intersection of the Internet of Things (IoT), embedded systems, edge computing, and environmental monitoring. He focuses on developing intelligent, decentralized systems to address real-world challenges such as air pollution, particularly in urban transportation networks. His work explores the integration of edge devices, machine learning algorithms, and blockchain technologies to design predictive and real-time monitoring solutions. Another key interest involves leveraging IoT infrastructures for smart city applications, including traffic management, public health monitoring, and resource optimization. Dr. Nizeyimana is particularly interested in how embedded systems can be adapted to constrained environments to achieve high accuracy with low power consumption and minimal latency. In addition to technical development, he investigates the ethical and infrastructural implications of deploying such technologies in developing countries. His research also includes data analytics for IoT devices, remote sensing systems, and system interoperability within distributed computing frameworks. Through his multidisciplinary approach, he seeks to expand the boundaries of scalable, secure, and sustainable technology for societal benefit. These interests reflect his commitment to using engineering innovation to improve public services, infrastructure management, and environmental stewardship in both local and global contexts.

Research Skills

Dr. Eric Nizeyimana possesses advanced research skills in embedded systems design, IoT application development, and edge computing architecture. He is proficient in integrating IoT sensors and communication protocols with real-time data processing systems to monitor and analyze environmental data, especially for detecting air pollution peaks. His work involves embedded system programming, circuit design, microcontroller deployment, and the use of platforms such as Arduino and Raspberry Pi. He also has experience in machine learning model development for predictive analytics, including supervised learning techniques applied to transportation and pollution datasets. Dr. Nizeyimana demonstrates expertise in decentralized systems using blockchain for data immutability and enhanced security. Additionally, he has strong skills in scientific writing, proposal development, and collaborative project implementation. His ability to design end-to-end solutions—from hardware development to software implementation and data interpretation—sets him apart in the IoT research space. Furthermore, he is skilled in academic dissemination, having presented at multiple international seminars and conferences. His competence in working across multicultural teams, both locally and internationally, further enhances his collaborative research capabilities. These skills are underpinned by a solid background in programming languages such as Python, Java, and C++, along with system administration and IT infrastructure management.

Awards and Honors

Dr. Eric Nizeyimana has been recognized for his academic excellence and research contributions through various prestigious awards. In 2023, he received the Mobility Research Grant from Rwanda’s National Council of Science and Technology (NCST), which enabled him to conduct critical experimental work at an international research institution. This grant, valued at approximately 8 million Rwandan francs, supported his living and research expenses during a two-month exchange, reflecting the national confidence in his research potential. In 2020, he was awarded a full four-year Ph.D. scholarship through the Partnership for skills in Applied Sciences, Engineering and Technology (PASET), a competitive regional initiative aimed at promoting advanced STEM education in Africa. His leadership and service have also been acknowledged through appointments such as PhD student representative and Master’s student representative, demonstrating trust in his leadership within academic communities. In addition, his consistent presence at international conferences and seminars, along with publications in respected peer-reviewed journals, underscores his active engagement in the global research community. These honors not only validate his academic achievements but also highlight his capability to drive impactful, solution-oriented research with both national and international relevance.

Conclusion

Dr. Eric Nizeyimana embodies the qualities of an outstanding researcher through his technical innovation, academic leadership, and commitment to solving real-world problems using emerging technologies. His focused research in IoT, embedded systems, and air pollution monitoring has generated valuable insights into how smart systems can be leveraged for environmental and urban challenges. His publication record in high-quality journals and active participation in global research exchanges reflect a strong orientation toward scholarly excellence and international collaboration. With a foundation in mathematics and engineering, his interdisciplinary approach allows him to bridge theory and application effectively. His work with institutions like Seoul National University and AIMS demonstrates adaptability, technical depth, and professional maturity. As an educator, he contributes to capacity building through teaching, mentorship, and curriculum development. Recognized with competitive grants and scholarships, he has proven his potential to lead transformative research in both academic and industrial contexts. While there remains room for broader global engagement and interdisciplinary outreach, Dr. Nizeyimana has established himself as a valuable contributor to the research community. His profile makes him a highly suitable candidate for recognition under a Best Researcher Award, affirming both his achievements and future promise.

Publications Top Notes

  1. Prototype of monitoring transportation pollution spikes through the internet of things edge networks

    • Authors: E. Nizeyimana, D. Hanyurwimfura, J. Hwang, J. Nsenga, D. Regassa

    • Year: 2023

    • Citations: 7

    • Journal: Sensors, 23(21), 8941

  1. Integration of Vision IoT, AI-based OCR and Blockchain Ledger for Immutable Tracking of Vehicle’s Departure and Arrival Times

    • Authors: M. Sichinga, J. Nsenga, E. Nizeyimana

    • Year: 2023

    • Citations: Not listed

    • Conference: 2023 8th Int. Conf. on Machine Learning Technologies

  1. Miniaturized Ultrawideband Microstrip Antenna for IoT‐Based Wireless Body Area Network Applications

    • Authors: U. Pandey, P. Singh, R. Singh, N.P. Gupta, S.K. Arora, E. Nizeyimana

    • Year: 2023

    • Citations: 15

    • Journal: Wireless Communications and Mobile Computing, 2023(1), 3950769

  1. IOT‐Based Medical Informatics Farming System with Predictive Data Analytics Using Supervised Machine Learning Algorithms

    • Authors: A. Rokade, M. Singh, S.K. Arora, E. Nizeyimana

    • Year: 2022

    • Citations: 20

    • Journal: Computational and Mathematical Methods in Medicine, 2022(1), 8434966

  1. Design of smart IoT device for monitoring short-term exposure to air pollution peaks

    • Authors: E. Nizeyimana, J. Nsenga, R. Shibasaki, D. Hanyurwimfura, J.S. Hwang

    • Year: 2022

    • Citations: 7

    • Journal: International Journal of Advanced Computer Science and Applications (IJACSA)

  1. Design of a decentralized and predictive real-time framework for air pollution spikes monitoring

    • Authors: E. Nizeyimana, D. Hanyurwimfura, R. Shibasaki, J. Nsenga

    • Year: 2021

    • Citations: 9

    • Conference: 2021 IEEE 6th Int. Conf. on Cloud Computing and Big Data Analysis

  1. Effect of Window Size on PAPR Reduction in 4G LTE Network Using Peak Windowing Algorithm in Presence of Non-linear HPA

    • Authors: M. Fidele, H. Damien, N. Eric

    • Year: 2020

    • Citations: 10

    • Conference: 2020 IEEE 5th Int. Conf. on Signal and Image Processing (ICSIP)

  1. Monitoring system to strive against fall armyworm in crops: case study on maize in Rwanda

    • Authors: D. Hanyurwimfura, E. Nizeyimana, F. Ndikumana, D. Mukanyiligira, …

    • Year: 2018

    • Citations: 7

    • Conference: 2018 IEEE SmartWorld/Ubiquitous Intelligence & Computing

  1. Comparative study on performance of High Performance Computing under OpenMP and MPI on Image Segmentation

    • Authors: E. Hitimana, E. Nizeyimana, G. Bajpai

    • Year: 2016

    • Citations: 1

    • Conference: Third International Conference on Advances in Computing, Communication and Informatics

  1. Development of an encrypted patient database including a doctor user interface

  • Author: E. Nizeyimana

  • Year: 2015

  • Citations: Not listed

  • Institution: African Institute for Mathematical Sciences Tanzania

Qichuan Tian | Computer Science | Best Researcher Award

Prof. Dr. Qichuan Tian | Computer Science | Best Researcher Award

Prof. Dr. at  Beijing University of Civil Engineering and Architecture, China

Qichuan Tian, born in 1971, is a distinguished professor and technical expert specializing in artificial intelligence, pattern recognition, and computer vision. He holds a Ph.D. in Engineering from Northwestern Polytechnical University (2006) and currently serves as a professor and master’s supervisor at Beijing University of Civil Engineering and Architecture (BUCEA). As the Director of the Department of Artificial Intelligence at the School of Intelligent Science and Technology, he leads research in biometrics, human-computer interaction, and deep learning. He is a member of multiple prestigious organizations, including the National Information Technology Standardization Technical Committee and the Chinese Society of Biomedical Engineering. His career spans academia and industry, with significant contributions in developing national standards, publishing books, and mentoring graduate students. Tian has also played a key role in over 20 research projects funded by national and provincial foundations, solidifying his reputation as a thought leader in AI and computational sciences.

Professional Profile

Education

Qichuan Tian has an extensive academic background in engineering. He obtained his Bachelor of Engineering (1993) and Master of Engineering (1996) from Taiyuan University of Science and Technology. In 2006, he completed his Doctor of Engineering at Northwestern Polytechnical University, specializing in artificial intelligence and computer vision. His academic training laid a strong foundation for his later contributions to AI, biometrics, and deep learning. His studies focused on integrating computational intelligence into practical applications, a theme that continues to define his research and professional endeavors.

Professional Experience

Tian has a diverse career in academia and research. Since 2012, he has served as the Head of the Department of Artificial Intelligence at BUCEA, where he spearheads innovative AI programs. From 2009 to 2010, he was a Visiting Scholar at Auburn University, USA, gaining international exposure in computer science. Between 2006 and 2008, he conducted postdoctoral research at Tianjin University. Previously, he held various roles at Taiyuan University of Science and Technology (1993–2012), where he advanced from Assistant Professor to Associate Professor and later became the Chief Leader of Circuits and Systems. His leadership has been instrumental in shaping AI research and education in China.

Research Interests

Tian’s research interests focus on artificial intelligence, pattern recognition, image processing, and deep learning. He specializes in biometric recognition, computer vision, and human-computer natural interaction. His work extends to security authentication, big data analysis, and IoT-based embedded systems. Tian has published over 100 journal and conference papers, authored six books, and contributed significantly to national standards in AI applications. His interdisciplinary research bridges theoretical advancements with practical AI implementations, making substantial contributions to the field.

Research Skills

With expertise in artificial intelligence and computer vision, Tian possesses strong research skills in deep learning algorithms, biometric recognition systems, and real-time image processing. He has successfully led projects in autonomous driving, green building AI integration, and complex object detection. His experience includes handling large-scale datasets, implementing machine learning frameworks, and designing AI-driven applications. Additionally, he has obtained over 50 invention patents and software copyrights, showcasing his ability to translate theoretical research into impactful technological innovations.

Awards and Honors

Tian’s contributions to academia and AI research have earned him multiple accolades. In 2024, he was recognized among CNKI’s Highly Cited Scholars (Top 5). He received the First Prize for Teaching Achievements at BUCEA in 2021 and was honored for developing a National First-Class Blended Online and Offline Course in 2020. Additionally, he was awarded the Outstanding Master’s Thesis Advisor Award in 2012. His accolades highlight his commitment to education, research, and AI-driven innovations, reinforcing his influence in the field of intelligent science and technology.

Conclusion

Qichuan Tian is a prominent scholar and AI expert dedicated to advancing artificial intelligence and biometric research. His leadership in academia, combined with his extensive research portfolio, underscores his impact on technological advancements in pattern recognition, computer vision, and human-computer interaction. With a career spanning over two decades, Tian has played a pivotal role in shaping AI education, national standards, and industry collaborations. His legacy continues to influence emerging AI technologies and inspire the next generation of researchers in intelligent computing.

Publications Top Notes

  • Title: An improved framework for breast ultrasound image segmentation with multiple branches depth perception and layer compression residual module

    • Authors: K. Cui, Qichuan Tian, Haoji Wang, Chuan Ma
    • Year: 2025
  • Title: Mobile Robot Path Planning Algorithm Based on NSGA-II

    • Authors: Sitong Liu, Qichuan Tian, Chaolin Tang
    • Year: 2024
    • Citations: 1
  • Title: OcularSeg: Accurate and Efficient Multi-Modal Ocular Segmentation in Non-Constrained Scenarios

    • Authors: Yixin Zhang, Caiyong Wang, Haiqing Li, Qichuan Tian, Guangzhe Zhao
    • Year: 2024
  • Title: Convolutional Neural Network–Bidirectional Gated Recurrent Unit Facial Expression Recognition Method Fused with Attention Mechanism

    • Authors: Chaolin Tang, Dong Zhang, Qichuan Tian
    • Year: 2023
    • Citations: 4

 

 

 

Yongzhi Wang | Information Security | Best Scholar Award

Dr. Yongzhi Wang | Information Security | Best Scholar Award

Assistant Professor of Texas A&M University-Corpus Christi, United States .

Dr. Yongzhi Wang is an accomplished computer scientist and educator with a robust background in cloud computing, cybersecurity, and blockchain technologies. He currently serves as an Assistant Professor at Texas A&M University at Corpus Christi, where he conducts cutting-edge research, teaches computer science courses, and mentors students in academic and research pursuits. Dr. Wang’s academic journey includes significant roles at Park University and Xidian University, where he contributed to research initiatives and academic programs. He holds a Ph.D. and M.S. in Computer Science from Florida International University, with a focus on secure outsourced computing frameworks in cloud environments. Throughout his career, Dr. Wang has received prestigious awards, including the Distinguished Faculty Scholar Award and Best Paper Award, recognizing his exceptional scholarship and research contributions. His research interests encompass cloud computing security, blockchain applications, cybersecurity, and virtualized lab environments for computer education. Dr. Wang’s passion for advancing secure computing technologies and nurturing future computer scientists underscores his leadership and impact in the field of computer science.

Professional Profiles:

Education

Dr. Yongzhi Wang has pursued an extensive academic journey, culminating in advanced degrees in computer science from prestigious institutions. He earned his Doctor of Philosophy (Ph.D.) and Master of Science (M.S.) degrees in Computer Science from Florida International University in Miami, Florida, U.S.A., with a focus on secure outsourced computing frameworks in cloud environments. Dr. Wang also holds a Master of Engineering (M.Eng.) in Computer Science from Xidian University in China and a Bachelor of Engineering (B.Eng.) in Computer Science from the same institution. Throughout his academic career, Dr. Wang demonstrated exceptional academic prowess, reflected in his high academic achievements with a GPA of 3.91 for both his Ph.D. and M.S. degrees. His educational background underscores his expertise in computer science, particularly in areas related to cloud computing, cybersecurity, and advanced technologies. Dr. Wang’s academic foundation has positioned him as a leading researcher and educator in the field of computer science.

Professional Experience

Dr. Yongzhi Wang has amassed a wealth of professional experience across academia, research, and industry, reflecting his deep expertise in computer science and related disciplines. He currently serves as an Assistant Professor at Texas A&M University at Corpus Christi, where he conducts cutting-edge research, teaches computer science courses, and mentors students in academic and research endeavors. Prior to this role, Dr. Wang held positions as an Associate Professor and Assistant Professor at Park University, contributing significantly to research initiatives and academic programs. Before his academic appointments, Dr. Wang served as an Assistant Professor at Xidian University in China, where he conducted research, taught courses, and supervised graduate students. His professional journey also includes roles as a Research Assistant and Teaching Assistant at Florida International University and as a Staff Software Engineer at IBM, where he applied his technical expertise in software development and project management. Dr. Wang’s diverse professional background underscores his leadership, dedication, and impact in advancing computer science education, research, and innovation.

Research Interest

Dr. Yongzhi Wang’s research interests span several critical areas in computer science and related disciplines. His primary focus includes cloud computing and security, where he explores secure computing frameworks and protocols to address data privacy and integrity challenges in cloud environments. Dr. Wang is also engaged in research on blockchain technologies, investigating their applications in enhancing security and transparency across various industries. Another significant aspect of Dr. Wang’s research is cybersecurity, encompassing threat detection, risk management, and intrusion detection systems to safeguard critical infrastructures from cyber threats. He also delves into big data and data privacy, developing techniques for preserving data privacy and ensuring the integrity of sensitive information in large-scale data environments. Moreover, Dr. Wang’s interest extends to virtualized lab environments for computer education, aiming to enhance practical learning experiences and accessibility to computing resources. Through his research, Dr. Wang contributes to advancing secure and efficient computing technologies, addressing contemporary challenges in the digital age.

Award and Honors

Dr. Yongzhi Wang’s exemplary contributions to computer science have been recognized through prestigious awards and honors throughout his career. Notably, his research article was acknowledged as a Trending Article in IEEE Transactions on Computers, reflecting the relevance and impact of his work in the field. He was also honored with the Distinguished Faculty Scholar Award at Park University, recognizing his outstanding scholarship and academic contributions. In addition, Dr. Wang received the Best Paper Award at the 2017 International Conference on Networking and Network Applications for his significant research achievements. His excellence in teaching was acknowledged with a second-place finish in the Faculty Teaching Competition at Xidian University. Furthermore, he was awarded the Dissertation Year Fellowship at Florida International University in recognition of his exceptional doctoral research. These accolades highlight Dr. Wang’s dedication to advancing computer science through innovative research, teaching excellence, and scholarly pursuits, solidifying his reputation as a leader in the field.

Research Skills

Dr. Yongzhi Wang’s distinguished career in computer science has been marked by several prestigious awards and honors that underscore his outstanding contributions to the field. Notably, his research article was recognized as a Trending Article in IEEE Transactions on Computers, demonstrating the impact and relevance of his work within the academic community. Additionally, Dr. Wang received the esteemed Distinguished Faculty Scholar Award at Park University, acknowledging his exceptional scholarship and academic leadership. Further highlighting his research excellence, Dr. Wang was honored with the Best Paper Award at the 2017 International Conference on Networking and Network Applications for his significant contributions to the field. His dedication to teaching was also celebrated with a second-place finish in the Faculty Teaching Competition at Xidian University. Moreover, his exceptional doctoral research was recognized with the Dissertation Year Fellowship at Florida International University. These accolades reflect Dr. Wang’s commitment to advancing computer science through innovative research, teaching excellence, and scholarly achievements, positioning him as a distinguished leader in the field.

Publications

  1. Microthings: A generic IoT architecture for flexible data aggregation and scalable service cooperation
    Authors: Y. Shen, T. Zhang, Y. Wang, H. Wang, X. Jiang
    Year: 2017
    Citations: 76
  2. Viaf: Verification-based integrity assurance framework for MapReduce
    Authors: Y. Wang, J. Wei
    Year: 2011
    Citations: 76
  3. Secure -NN Query on Encrypted Cloud Data with Multiple Keys
    Authors: K. Cheng, L. Wang, Y. Shen, H. Wang, Y. Wang, X. Jiang, H. Zhong
    Year: 2017
    Citations: 71
  4. Special issue on security and privacy in network computing
    Authors: H. Wang, Y. Wang, T. Taleb, X. Jiang
    Year: 2020
    Citations: 69
  5. MTMR: Ensuring MapReduce computation integrity with Merkle tree-based verifications
    Authors: Y. Wang, Y. Shen, H. Wang, J. Cao, X. Jiang
    Year: 2016
    Citations: 46
  6. Result integrity check for MapReduce computation on hybrid clouds
    Authors: Y. Wang, J. Wei, M. Srivatsa
    Year: 2013
    Citations: 30
  7. IntegrityMR: Integrity assurance framework for big data analytics and management applications
    Authors: Y. Wang, J. Wei, M. Srivatsa, Y. Duan, W. Du
    Year: 2013
    Citations: 28
  8. CryptSQLite: SQLite with high data security
    Authors: Y. Wang, Y. Shen, C. Su, J. Ma, L. Liu, X. Dong
    Year: 2019
    Citations: 19
  9. Strongly secure and efficient range queries in cloud databases under multiple keys
    Authors: K. Cheng, Y. Shen, Y. Wang, L. Wang, J. Ma, X. Jiang, C. Su
    Year: 2019
    Citations: 18
  10. Trustworthy service composition with secure data transmission in sensor networks
    Authors: T. Zhang, L. Zheng, Y. Wang, Y. Shen, N. Xi, J. Ma, J. Yong
    Year: 2018
    Citations: 15