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

Tazebew Dires Kassie | Engineering | Editorial Board Member

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Mr. Tazebew Dires Kassie | Engineering | Editorial Board Member

Debre Markos University | Ethiopia

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🌱 Early Academic Pursuits

Mr. Tazebew Dires Kassie's journey into the realm of mechanical engineering began at Debre Markos University, where he earned his Bachelor’s degree in Mechanical Engineering in 2016 with an impressive GPA of 3.8/4.0. Fueling his passion for sustainability and innovation, he pursued a Master’s in Sustainable Energy Engineering from Bahir Dar University, graduating in 2021 with a perfect CGPA of 4.0/4.0. His thirst for continuous learning has since led him to expand his expertise through multiple Nano Degrees in Artificial Intelligence, Data Science, Android Development, and Programming Fundamentals from Udacity Online, and a Master Class in Online Teaching from Arizona State University.

🧑‍🏫 Professional Endeavors

Mr. Tazebew has been a dedicated academic and engineering professional since 2016, serving as a Lecturer at Debre Markos University. His leadership skills were further recognized when he was appointed Head of the Mechanical Engineering Department in 2024, where he now oversees academic programs, faculty development, research innovation, and strategic planning. Beyond academia, his early industry experience as a Maintenance Technician at Dashen Brewery S.C. in 2015 provided a strong foundation in preventive maintenance, machinery troubleshooting, and operational efficiency.

🔬 Contributions and Research Focus

Mr. Tazebew’s research contributions lie at the intersection of renewable energy systems, thermoelectric modules, and sustainable mechanical solutions. His notable studies include optimizing stove waste heat recovery using evaporative cooling, investigating CuO-water nanofluids in thermal systems, and analyzing performance parameters of direct evaporative coolers. His publications are featured in top-tier journals such as Springer – Energy Systems, Elsevier – Journal of Thermofluids, and Case Studies in Thermal Engineering. He has published five research papers, many of which are in press, and led two funded projects as a Principal Investigator.

🏅 Accolades and Recognition

Throughout his academic and professional career, Mr. Tazebew has received multiple awards that reflect his innovation and community dedication. He earned the Best BSc Thesis Award from Debre Markos University and received formal recognition for designing and manufacturing 6 wheelchairs with integrated toilet and shower services, and a shoeshine boy’s working shade, improving both accessibility and dignity. His outreach and project work have also earned him six certificates for community engagement, especially in aiding people with disabilities.

🌍 Impact and Influence

Mr. Tazebew’s work goes beyond the confines of classrooms and labs. His community-oriented engineering solutions highlight the practical application of sustainable technologies to address local needs. As a speaker and presenter at forums such as the Ethiopian Society of Mechanical Engineering and national research conferences, he continues to inspire peers and students alike with innovations in energy-efficient systems and design thinking. His teaching integrates real-world challenges with engineering fundamentals, empowering future professionals with critical problem-solving skills.

🔮 Legacy and Future Contributions

Mr. Tazebew Dires Kassie stands as a beacon of innovation and community-driven engineering in Ethiopia. With his growing expertise in AI, data science, and digital technologies, he is poised to bridge traditional mechanical engineering with cutting-edge interdisciplinary approaches. As he continues to lead his department and expand his research portfolio, his legacy is one of sustainable impact, academic excellence, and inclusive design. The future holds promise for more transformative projects and leadership in green energy solutions, smart technologies, and engineering education reform.

Publications

📄  Design and Fabrication of a Multi-Terrain Triphibian Quadcopter for Airborne, Terrestrial, and Aquatic Mobility
Author: Tazebew Dires Kassie
Journal: Journal of Intelligent & Robotic Systems
Year: 2025

📄  Experimental Investigation of Air Velocity, Water Flow Rate and Staging of Cooling Pad on the Performance of Direct Evaporative Coolers
Authors: Tazebew Dires Kassie, Yaregal Eneyew Bizuneh
Journal: International Journal of Air Conditioning and Refrigeration
Year: 2025

📄  Numerical Studies on Thermo-Hydraulic Performance of Solar Air Heater with Quarter-Circle Roughness Ribs
Authors: Tazebew Dires Kassie, Yaregal Eneyew, Amare Merfo
Journal: Results in Engineering
Year: 2025

📄  Numerical Investigation on Heat Transfer of CuO-Water Nano-Fluid in a Circular Pipe with Twisted Tape Inserts
Authors: Tazebew Dires Kassie, Yaregal Eneyew Bizuneh, Endalkew Berhie Gebresilassie, Atalay Enyew Bizuneh
Journal: International Journal of Thermofluids
Year: 2025

📄 Enhancing a Thermoelectric Power Generation System’s Efficiency from a Stove’s Waste Heat by Optimizing the Heat Sink Temperature Junction Using a Direct Evaporative Cooler
Authors: Bimrew Admasu, Tazebew Dires Kassie, Getu Alemayehu Melas, Hailemariam Mulugeta, S. Nagarajan
Journal: Energy Systems
Year: 2025

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

Yeeshtdevisingh Hosanee | Computer Science | Women Research Award

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Ms. Yeeshtdevisingh Hosanee | Computer Science | Women Research Award 

JCI | Mauritius

Author Profile

Scopus

🎓 Early Academic Pursuits

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

💼 Professional Endeavors

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

🧠 Contributions and Research Focus

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

🏆 Accolades and Recognition

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

🌍 Impact and Influence

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

✨ Legacy and Future Contributions

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

Publications

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

  • Authors: Yeeshtdevisingh Hosanee, Shireen Panchoo

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

  • Publisher: IEEE

  • Publication Date: January 7, 2016

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

  • Authors: Yeeshtdevisingh Hosanee, Shireen Panchoo

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

  • Publisher: IEEE

  • Publication Date: November 10, 2016

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

  • Authors: Yeeshtdevisingh Hosanee, Shireen Panchoo

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

  • Publisher: IEEE

  • Publication Date: November 10, 2016

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

  • Authors: Yeeshtdevisingh Hosanee, Shireen Panchoo

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

  • Publisher: ELECOM

  • Publication Date: November 28–30, 2018

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

  • Author: Yeeshtdevisingh Hosanee

  • Publisher: GRIN Publishing

  • Publication Date: June 28, 2016

 

Shaik Salma Asiya Begum | Computer Science | Best Researcher Award

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Dr. Shaik Salma Asiya Begum | Computer Science | Best Researcher Award

LBRCE College | India

Author Profile

Scopus

🎓 Early Academic Pursuits

Dr. Shaik Salma Asiya Begum's journey in academia began with a strong foundation in science and mathematics. From excelling in her SSC with distinction to graduating with a B.Tech in Computer Science from Nimra Women’s College of Engineering, her passion for technology was evident early on. She pursued her M.Tech in Computer Science and Engineering at Nova College, earning first-class distinction, and recently completed her Ph.D. at VIT-AP University in 2024, further cementing her expertise in advanced computing.

👩‍💼 Professional Endeavors

Dr. Salma has amassed rich experience across prestigious institutions. She currently serves as an Associate Professor at LBRCE, Mylavaram. Previously, she was a Research Assistant at VIT-AP University and held academic roles at Amrita Sai Institute and Nova College. Her teaching portfolio spans undergraduate to postgraduate courses, including MCA and B.Pharmacy, and she has also delivered guest lectures to international students. She has skillfully balanced teaching with academic administration and NAAC coordination.

🔬 Contributions and Research Focus

Dr. Salma's research spans deep learning, plant disease detection, cloud-fog computing, vehicular networks, and optimization algorithms. Her work showcases technical depth and innovation, as seen in her SCIE and Scopus-indexed papers and conference presentations. She developed models like GSAtt-CMNetV3 and CNBLM and contributed significantly to agricultural and vehicular AI. Her research bridges AI applications with real-world problems, particularly in agriculture and smart environments.

🏆 Accolades and Recognition

Dr. Salma’s excellence has been recognized through several Best Research Paper Awards, notably at ICRTAC’23 and iDEAAS 2024. Her innovations have also led to a patented system for potato plant disease surveillance using AI. She has actively participated in and coordinated various faculty development programs and workshops, reflecting her commitment to continuous learning and knowledge dissemination.

🌍 Impact and Influence

With over a decade of teaching and research experience, Dr. Salma has made a profound impact on students, peers, and the academic community. Her mentorship of B.Tech and MCA projects, guest lectures, and departmental leadership roles highlight her influential presence in academia. Her contributions in leveraging AI for agriculture, environment, and smart systems are paving new directions in applied computing.

✨ Legacy and Future Contributions

Dr. Salma Asiya Begum is not just an educator but a visionary research leader. As she continues to explore cutting-edge technologies, her future work is poised to influence AI-driven agriculture, sustainable computing, and smart infrastructure. Her academic legacy will be defined by her dedication to empowering students, fostering research excellence, and making technology work for the greater good.

Publications

 📄 Feature Selection Using Hybridized Genghis Khan Shark with Snow Ablation Optimization Technique for Multi-Disease Prognosis

Authors: Ruqsar Zaitoon, Shaik Salma Asiya Begum, Sachi Nandan Mohanty, Deepa Jose
Journal: Intelligence-Based Medicine
Year: 2025

 📄 Navigating the Future of Intelligent Transportation: Challenges and Solutions in 6G V2X and V2V Networks

Authors: Spandana Mande, Shaik Salma Asiya Begum, Nandhakumar Ramachandran
Journal: EAI Endorsed Transactions on Internet of Things
Year: 2025

Francisco Mena | Computer Science | Best Researcher Award

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Mr. Francisco Mena | Computer Science | Best Researcher Award

University of Kaiserslautern-Landau | Germany

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🎓 Early Academic Pursuits

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

💼 Professional Endeavors

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

🔬 Contributions and Research Focus

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

🏆 Accolades and Recognition

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

🌐 Impact and Influence

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

🧬 Legacy and Future Contributions

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

Publications

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

  • Authors: Francisco Mena, Diego Arenas, Andreas Dengel

  • Journal: Neurocomputing

  • Year: 2025

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

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

  • Journal: Remote Sensing of Environment

  • Year: 2025

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

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

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

  • Year: 2024

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

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

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

  • Year: 2024

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

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

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

  • Year: 2024

 

Bing Cai | Computer Science | Best Researcher Award

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Mr. Bing Cai | Computer Science | Best Researcher Award

Anhui Institute of Information Technology | China

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Early Academic Pursuits 🎓

Mr. Bing Cai embarked on his academic journey with a strong foundation in engineering. He earned his Bachelor of Engineering in Electronics and Information Engineering from Anhui University in 2014, where he developed a keen interest in computing and information systems. His thirst for advanced knowledge led him to pursue a Master of Engineering in Computer Technology at Anhui Polytechnic University, completing his degree in 2024 with a commendable GPA of 3.36. His rigorous academic training laid the groundwork for his expertise in software development and multi-view clustering techniques.

Professional Endeavors 🌟

Mr. Cai has accumulated extensive professional experience in both academia and industry. From 2014 to 2017, he worked as a Software Engineer at iFLYTEK Co., Ltd., where he contributed to the development of Android and iOS applications. His responsibilities included designing app frameworks, optimizing performance, and conducting comprehensive testing for speech synthesis systems. His tenure at iFLYTEK honed his skills in software architecture, application development, and embedded systems testing. Transitioning to academia in 2017, Mr. Cai served as a Corporate Teacher at Anhui Institute of Information Technology. Here, he played a pivotal role in teaching Web Front-End Development, guiding students in research and graduation projects, and mentoring them for competitions. His ability to bridge theoretical knowledge with practical applications made him a valuable asset in the field of computer and software engineering education.

Contributions and Research Focus 📚

Mr. Cai's research primarily focuses on multi-view clustering, tensor subspace clustering, and machine learning methodologies. His scholarly contributions include several high-impact publications in prestigious journals such as IEEE Transactions on Multimedia, Pattern Recognition, and Signal Processing. His research introduces innovative clustering techniques using tensorized and low-rank representations, significantly advancing the field of multi-view learning. Notably, his studies on high-order manifold regularization and tensorized bipartite graph clustering have provided new insights into handling large-scale and incomplete multi-view data. His work is instrumental in improving data representation and clustering efficiency in artificial intelligence applications.

Accolades and Recognition 🏆

Mr. Cai's dedication to excellence has been recognized with several prestigious awards. In 2023, he won the Bronze Prize in the Anhui Province "Internet+" College Student Innovation and Entrepreneurship Competition, highlighting his innovative approach to problem-solving. He also received the Outstanding Paper Award from the Anhui Association for Artificial Intelligence in 2022, further cementing his reputation as a leading researcher in his field. His academic excellence was also acknowledged through the National Scholarship for Postgraduate Students in 2022, a testament to his scholarly contributions.

Impact and Influence 🌍

Mr. Cai's work has had a profound impact on both academia and industry. His contributions to multi-view clustering have influenced the development of more robust and efficient data analysis techniques in AI and machine learning. His research findings are widely cited, reflecting their significance in advancing computational intelligence. Furthermore, his role as an educator has shaped the next generation of computer scientists, inspiring students to engage in research and innovation.

Legacy and Future Contributions 🚀

With a strong foundation in research and industry, Mr. Cai is poised to make even greater contributions to the field of computer technology. His ongoing work in multi-view clustering and tensor-based machine learning will likely lead to more breakthroughs in AI-driven data processing. As he continues to explore innovative clustering methodologies, his research is expected to influence a wide range of applications, from big data analytics to artificial intelligence-driven decision-making systems. His commitment to excellence ensures that he will remain at the forefront of technological advancements in the years to come.

 

Publications

  • 📄 Multi-view subspace clustering with a consensus tensorized scaled simplex representation
    Author(s): Hao He, Bing Cai, Xinyu Wang
    Journal: Information Sciences
    Year: 2025-03

  • 📄 Tensorized Scaled Simplex Representation for Multi-View Clustering
    Author(s): Bing Cai, Gui-Fu Lu, Hua Li, Weihong Song
    Journal: IEEE Transactions on Multimedia
    Year: 2024

  • 📄 Aligned multi-view clustering for unmapped data via weighted tensor nuclear norm and adaptive graph learning
    Author(s): Bing Cai, Gui-Fu Lu, Liang Yao, Jiashan Wan
    Journal: Neurocomputing
    Year: 2024

  • 📄 Complete multi-view subspace clustering via auto-weighted combination of visible and latent views
    Author(s): Bing Cai, Gui-Fu Lu, Guangyan Ji, Weihong Song
    Journal: Information Sciences
    Year: 2024

  • 📄 Auto-weighted multi-view clustering with the use of an augmented view
    Author(s): Bing Cai, Gui-Fu Lu, Jiashan Wan, Yangfan Du
    Journal: Signal Processing
    Year: 2024

 

Aman Bin Jantan | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Aman Bin Jantan | Computer Science | Best Researcher Award

Universiti Sains Malaysia | Malaysia

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Early Academic Pursuits 🎓

Assoc. Prof. Dr. Aman Bin Jantan's academic journey is rooted in a strong foundation in computer science. He earned his Bachelor’s degree (1993) and Master’s in Computer Science (AI) (1996) from Universiti Sains Malaysia (USM), where he laid the groundwork for his expertise in artificial intelligence and software engineering. His research on FrameLog Compiler Construction during his MSc reflected an early inclination toward programming languages and AI-driven system development. His PhD in Software Engineering (2002) from USM further solidified his prowess, focusing on the redefinition of expert system development languages—a groundbreaking contribution to the field.

Professional Endeavors 🏢

Dr. Aman has had an extensive career in both academia and industry. His professional journey began as a Research Officer at USM’s AI Lab in 1993, followed by roles as a Graduate Assistant and Lecturer. His passion for education saw him taking up lecturing positions at Stamford College, UiTM Shah Alam, and USM. Apart from academia, he ventured into the tech industry by establishing his own ICT business, offering software solutions, IT services, and computer training. Since 2002, he has been an integral part of USM’s School of Computer Sciences, where he now serves as an Associate Professor.

Contributions and Research Focus 🔬

Dr. Aman’s research spans across multiple domains, including:
Information Security – Intrusion Detection, Cyberwarfare, Encryption, Steganography, and Electronic Forensics.
Software Engineering – Fault Tolerance, Component-Based System Development, and Software Quality Assurance.
Artificial Intelligence – Machine Learning, Neuro-Fuzzy Systems, and Expert Systems.

His work on network security, intrusion detection, and machine learning-driven cybersecurity solutions has significantly impacted the field. His innovative Honeybee Intelligent Model for Network Zero-Day Attack Detection is a notable contribution that has been widely recognized.

Accolades and Recognition 🏆

Dr. Aman’s excellence in teaching and research has earned him multiple Excellent Service Awards (2007, 2011, 2020). His publications in high-impact journals, including those on financial crime prevention, AI-driven profiling, and cybersecurity measures, have established him as a thought leader in his domain.

Impact and Influence 🌍

As an academic and researcher, Dr. Aman has shaped the next generation of cybersecurity experts and software engineers. His workshops, mentorship, and leadership in the field of information security have influenced policy-making and corporate cybersecurity strategies. His Security and Forensic Research Group Laboratory at USM is a hub for cutting-edge research in cyber defense technologies.

Legacy and Future Contributions 🚀

Dr. Aman’s contributions to artificial intelligence, cybersecurity, and software engineering will continue to shape the landscape of digital security and computing. His commitment to advancing cybersecurity education and research ensures that future professionals will be well-equipped to tackle emerging threats in an increasingly digital world. With a strong portfolio of research, industry collaborations, and mentorship, Dr. Aman remains a driving force in the evolution of AI-driven security solutions. His future work is expected to redefine the intersection of AI and cybersecurity, making digital systems safer and more resilient.

Publications

  • 📄 Enhancing Neighborhood-Based Co-Clustering Contrastive Learning for Multi-Entity Recommendation

    • Authors: J. Liao, Juan; A.B. Jantan, Aman Bin; Z. Liu, Zhe

    • Journal: Engineering Applications of Artificial Intelligence

    • Year: 2025

  • 📄 Digital Forensic Investigation on Social Media Platforms: A Survey on Emerging Machine Learning Approaches

    • Authors: A.A. Kazaure, Abdullahi Aminu; A.B. Jantan, Aman Bin; M.N. Yusoff, Mohd Najwadi

    • Journal: Journal of Information Science Theory and Practice

    • Year: 2024

  • 📄 Digital Forensics Investigation Approaches in Mitigating Cybercrimes: A Review

    • Authors: A.A. Kazaure, Abdullahi Aminu; A.B. Jantan, Aman Bin; M.N. Yusoff, Mohd Najwadi

    • Journal: Journal of Information Science Theory and Practice

    • Year: 2023

  • 📄 A Machine Learning Classification Approach to Detect TLS-Based Malware Using Entropy-Based Flow Set Features (Open Access)

    • Authors: K. Keshkeh, Kinan; A.B. Jantan, Aman Bin; K. Alieyan, Kamal

    • Journal: Journal of Information and Communication Technology

    • Year: 2022

  • 📄 Multi-Behavior RFM Model Based on Improved SOM Neural Network Algorithm for Customer Segmentation (Open Access)

    • Authors: J. Liao, Juan; A.B. Jantan, Aman Bin; Y. Ruan, Yunfei; C. Zhou, Changmin

    • Journal: IEEE Access

    • Year: 2022

 

Hongzhen Cui | Computer Science | Best Researcher Award

Published on by Book of Award

Dr. Hongzhen Cui | Computer Science | Best Researcher Award

University of Science and Technology Beijing | China

Author Profile

Orcid

🚀 Early Academic Pursuits

Dr. Hongzhen Cui embarked on his academic journey in computer science with a Bachelor's degree from Zaozhuang University, where he built a solid foundation in computational principles. His passion for technology and problem-solving led him to pursue a Master's degree at Harbin Engineering University, refining his expertise in advanced computing methodologies. Currently, he is a Ph.D. candidate at the University of Science and Technology Beijing, where he specializes in cutting-edge fields such as Natural Language Processing (NLP), Knowledge Graphs, and Deep Learning, with a strong focus on cardiovascular disease research.

💼 Professional Endeavors

Dr. Cui's career has been marked by a blend of research and practical experience. As a System R&D Engineer at Meituan, he contributed to large-scale distributed systems, optimizing performance and collaborating with cross-functional teams to drive technological advancements. His passion for academia led him to a teaching position at Zaozhuang University, where he inspired students in subjects such as Data Structures, Algorithm Design, and Software Engineering. Through these roles, he has seamlessly combined industry expertise with academic mentorship.

🔬 Contributions and Research Focus

Dr. Cui’s research delves deep into the intersection of artificial intelligence and healthcare. His work in Natural Language Processing and Knowledge Graphs plays a pivotal role in extracting meaningful insights from medical data. With a keen interest in cardiovascular disease feature mining, he develops AI-driven models for disease prediction and analysis, aiding in early diagnosis and medical decision-making. His interdisciplinary approach bridges the gap between engineering and medicine, contributing to the evolution of intelligent healthcare solutions.

🏆 Accolades and Recognition

Dr. Cui’s dedication to research and academia has earned him recognition in both scientific and professional communities. His contributions to NLP and deep learning applications in healthcare have been acknowledged through publications, conference presentations, and collaborative projects. His role as a mentor and lecturer has also been praised for shaping future generations of computer scientists.

🌍 Impact and Influence

Through his research, Dr. Cui has made significant strides in the application of AI to medical diagnostics. His work on disease information extraction and prediction not only enhances medical research but also paves the way for AI-assisted healthcare innovations. As an educator, he has influenced countless students, guiding them towards research excellence and industry preparedness.

🔮 Legacy and Future Contributions

Dr. Cui's future aspirations involve furthering AI’s role in medical advancements, refining predictive models for cardiovascular diseases, and expanding the capabilities of knowledge graphs in healthcare applications. His interdisciplinary research continues to break barriers, promising a future where AI-driven solutions revolutionize disease prevention and treatment.

 

Publications

📄ECG Signal Classification Using Interpretable KAN: Towards Predictive Diagnosis of Arrhythmias
Author(s): Hongzhen Cui, Shenhui Ning, Shichao Wang, Wei Zhang, Yunfeng Peng
Journal: Algorithms
Year: 2025

 

Caiming Zhang | Decision Sciences | Best Researcher Award

Published on by Book of Award

Prof. Caiming Zhang | Decision Sciences | Best Researcher Award

China University of Labor Relations | China

Author profile

Scopus

Orcid

🌱 Early Academic Pursuits

Prof. Caiming Zhang's educational journey showcases his steadfast dedication to Industrial Economics and Management. He began with a Bachelor of Engineering from Nanchang University in 1998, followed by a Master of Management from Beijing University of Technology in 2001. His academic ambition culminated in a Ph.D. in Industrial Economics from Beijing Jiaotong University in 2008. These formative years laid the foundation for his future contributions to academia and industry.

🏛️ Professional Endeavors

Prof. Zhang's career trajectory reflects a seamless integration of academic leadership and industry innovation. As the Dean of the School of Labor Relations and Human Resources at China University of Labor Relations, he continues to guide the next generation of thinkers. His prior roles as Vice Dean and Director within the same institution underscore his impactful leadership. Beyond academia, Prof. Zhang is the Founder and President of Beijing Dimensional Insight Inc., a hub for cutting-edge research in big data and business intelligence, showcasing his entrepreneurial spirit and technical expertise.

🔬 Contributions and Research Focus

Prof. Zhang’s research encompasses pivotal areas such as big data, artificial intelligence, and Industry 4.0. His work has been recognized globally through publications in esteemed journals like Journal of Industrial Information Integration and Information Systems Frontiers. His patents, including innovative methods for big data analysis, highlight his contributions to technological advancement. Furthermore, his hosting of national research projects and development of big data systems for institutions like Beijing Metro Commission and Hebei Hospitals reflect his commitment to practical applications of research.

🏅 Accolades and Recognition

Prof. Zhang’s contributions have earned numerous accolades. Among them are awards for groundbreaking research in artificial intelligence and educational excellence. His paper on AI prospects won the Third Award at the 16th Scientific Research Achievements in China University of Labor Relations. He has also been recognized for innovative curriculum design, securing prestigious teaching awards. As a Senior Member of IEEE and the Chinese Society of Technology Economics, his influence extends across academic and professional spheres.

🌍 Impact and Influence

As a visiting scholar at Old Dominion University and a sought-after speaker at international conferences, Prof. Zhang has brought Chinese academic insights to the global stage. His research on topics like the economic impact of AI and blockchain technology not only advances knowledge but also addresses contemporary industry challenges. Through his mentorship of graduate students and leadership in research, he has shaped the academic and professional paths of countless individuals.

🌟 Legacy and Future Contributions

Prof. Zhang's enduring legacy lies in his ability to bridge the gap between theory and practice. His work in advancing big data applications, combined with his passion for education and innovation, promises a future where technology continues to drive societal progress. As he leads projects on intelligent education and big data decision-making, Prof. Zhang remains a beacon of inspiration, paving the way for breakthroughs in both academia and industry.

 

Publications

📝 The Impact of Generative AI on Management Innovation

  • Author: Zhang, C., Zhang, H.
  • Journal: Journal of Industrial Information Integration
  • Year: 2025

📝 A Dynamic Attributes-driven Graph Attention Network Modeling on Behavioral Finance for Stock Prediction

  • Author: Zhang, Q., Zhang, Y., Yao, X., Zhang, C., Liu, P.
  • Journal: ACM Transactions on Knowledge Discovery from Data
  • Year: 2023

📝 Acquisition and Cognition Information of Human Body Swing

  • Author: Fan, J.-F., Sigov, A., Ratkin, L., Chen, S.-W., Zhang, C.-M.
  • Journal: Journal of Industrial Information Integration
  • Year: 2022

📝 A Literature Review of Social Commerce Research from a Systems Thinking Perspective

  • Author: Wang, X., Wang, H., Zhang, C.
  • Journal: Systems
  • Year: 2022

📝 Study on the Interaction Between Big Data and Artificial Intelligence

  • Author: Li, J., Ye, Z., Zhang, C.
  • Journal: Systems Research and Behavioral Science
  • Year: 2022