Mingyue Cui | Computer Science and Technology | Best Researcher Award

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Mr. Mingyue Cui | Computer Science and Technology | Best Researcher Award

Dr. Mingyue Cui is a pioneering computer scientist whose multidisciplinary work bridges intelligent vehicles, biomedical computing, and real-time embedded systems. He earned his Ph.D. in Computer Science and Engineering from Sun Yat-sen University, with research affiliations at the Technical University of Munich. His scholarly journey reflects deep engagement in applied AI, autonomous driving, edge computing, and sensor data processing. Dr. Cui has authored over 20 high-impact papers in IEEE and AAAI venues and holds several national patents in autonomous systems and LiDAR compression. His innovation has been recognized through prestigious awards, including top honors in robotics and AI design competitions in China. Dr. Cui continues to advance research in scalable, low-cost AI for smart healthcare and mobility, driving collaborations across academia and industry.

Profiles

Google Scholar

Scopus

🎓 Education

Mingyue Cui holds a Ph.D. in Computer Science and Engineering from Sun Yat-sen University (2018–2022), with research conducted in partnership with the Technical University of Munich. His doctoral work, supervised by Prof. Kai Huang, focused on intelligent connected vehicles, emphasizing autonomous driving systems and biomedical signal processing. Prior to this, he completed a Master’s degree in Software Engineering (2015–2017) from the same university, authoring a thesis on real-time scene flow for embedded systems. His Bachelor’s degree in Software Engineering (2010–2014) was obtained from Chongqing Normal University, where he specialized in embedded software engineering. His academic training spans advanced topics like optimization theory, computational complexity, machine learning, and embedded systems.

🧪 Experience

Dr. Mingyue Cui has built a robust research profile with a focus on real-world applications of AI and embedded systems. His Ph.D. thesis explored intelligent connected vehicles, targeting the challenges of real-time computation and network reliability in autonomous driving. He led pioneering efforts in algorithm parallelization, edge computing for autonomous services, and quality of service assurance using low-cost embedded platforms. His current research has expanded to biomedical domains, particularly ECG signal processing and cardiovascular disease diagnostics. With over 20 academic publications and patents, Cui collaborates extensively with Prof. Kai Huang and research groups at both Sun Yat-sen University and the Technical University of Munich. In addition to his academic output, he actively contributes to competitive research through international robotics and AI competitions, where he has earned multiple first and second-place awards.

🏆 Awards and Honors 

Dr. Mingyue Cui’s research excellence is widely recognized through multiple awards. In 2023, he received a Bronze Award at the China College Students’ ‘Internet+’ Innovation Competition. He also secured the First Prize at the CCF Mobile Robot Challenge with a $10,000 grant, and a Second Prize in the International Running Intelligent Robot Competition. Earlier, he won the First Prize in the same international robotics event in 2019. In 2021, he earned the Second Prize in the World 5G Conference Application Design Competition. These accolades highlight his ability to translate complex theoretical work into high-impact innovations, especially in robotics, autonomous systems, and AI-powered design.

🔍 Research Focus 

Dr. Mingyue Cui’s research integrates real-time embedded systems, AI-driven autonomous vehicles, biomedical signal processing, and point cloud compression. His Ph.D. centered on Intelligent Connected Vehicles (ICV), where he developed methods for optimizing service offloading and computing efficiency while maintaining Quality of Service under network fluctuations. His recent research includes developing hybrid CNN-Transformer models for ECG denoising, distributed AI processors for seizure detection, and octree-based transformers for LiDAR compression. With applications spanning autonomous mobility to wearable health diagnostics, Cui’s work emphasizes scalable, cost-effective, and intelligent system architectures. He is also deeply involved in collaborative SLAM for multi-vehicle networks and cross-modal sensor fusion, pushing the boundaries of edge computing in real-time robotics and healthcare contexts.

📄 Publication Top Notes

1. Dense Depth-Map Estimation Based on Fusion of Event Camera and Sparse LiDAR

Cui et al., IEEE Transactions on Instrumentation and Measurement, 2022
This paper presents a novel method combining sparse LiDAR data with asynchronous event camera signals to estimate dense depth maps efficiently. The fusion approach leverages temporal resolution from event cameras and spatial accuracy from LiDAR to improve performance in dynamic environments.

2. Offloading Autonomous Driving Services via Edge Computing

Cui et al., IEEE Internet of Things Journal, 2020
A seminal work on optimizing the offloading of AI services in autonomous driving. It explores real-time system performance under various load conditions and proposes an adaptive framework to ensure service continuity with minimal latency.

3. OctFormer: Efficient Octree-Based Transformer for Point Cloud Compression

Cui et al., AAAI Conference on Artificial Intelligence, 2023
Proposes OctFormer, an efficient transformer architecture for compressing point cloud data using octree structures. It achieves local detail preservation with high compression ratios, enabling faster data transmission in autonomous systems.

4. OctFormer: Efficient Octree-Based Transformer for Point Cloud Compression

Cui et al., AAAI 2023
This paper introduces OctFormer, a novel transformer-based framework that leverages the octree structure for efficient point cloud compression. It enhances local feature extraction while achieving significant compression gains, facilitating faster 3D data transfer in autonomous systems.

5. ECG Signal Denoising Based on Hybrid CNN-Transformer Network

Cui et al., Journal of Healthcare Engineering, 2023
This study proposes a deep hybrid model combining Convolutional Neural Networks (CNNs) and Transformers to denoise ECG signals. The model effectively suppresses motion artifacts and improves diagnostic signal quality, contributing to wearable and mobile health solutions.

6. Distributed Lightweight AI Processor for Real-Time Epileptic Seizure Detection

Cui et al., Biomedical Signal Processing and Control, 2022
Presents a low-latency, power-efficient edge processor design for seizure detection using EEG signals. The AI model is optimized for resource-constrained devices, enabling early and accurate detection in remote or wearable healthcare settings.

7. Cooperative SLAM for Multi-Vehicle Systems Based on Dynamic Bayesian Optimization

Cui et al., IEEE Access, 2021
This paper addresses collaborative simultaneous localization and mapping (SLAM) for autonomous vehicles. It proposes a Bayesian optimization strategy to dynamically adjust SLAM parameters across a vehicle fleet, enhancing map accuracy and robustness in changing environments.

8. Quality of Service-Oriented Computation Offloading for Autonomous Driving Applications

Cui et al., Sensors, 2020
Focuses on computation offloading strategies that prioritize QoS in vehicle-to-edge communication. It balances task latency and network reliability to ensure real-time performance for self-driving applications, even under fluctuating network conditions.

9. Real-Time Scene Flow Estimation for Stereo Vision Using Embedded GPU Platforms

Cui et al., International Conference on Embedded Systems and Applications, 2019
Develops a lightweight algorithm for estimating scene flow from stereo images, optimized for embedded GPU platforms. The approach supports real-time performance, enabling practical deployment in mobile robots and AR/VR applications.

10. LiDAR-Assisted Pedestrian Detection Based on Multi-Sensor Fusion with Deep Learning

Cui et al., Proceedings of the Chinese Conference on Intelligent Transportation, 2021
Integrates LiDAR data with camera input using a deep fusion network to enhance pedestrian detection accuracy in autonomous vehicles. The fusion technique improves robustness in low-light or occluded conditions.

Conclusion

Dr. M. Cui is a highly accomplished and forward-thinking researcher with:

  • A clear impact in autonomous systems and intelligent robotics,

  • Strong innovation credentials (patents and real-world applications),

  • Recognized technical contributions through competitive awards, and

  • A trajectory that continues to expand into biomedical applications.

He is highly suitable for a Best Researcher Award, especially in fields related to smart mobility, embedded systems, and AI-powered healthcare technologies.

Saad Alqithami | Artificial Intelligence | Sustainable Engineering Award

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Assoc. Prof. Dr. Saad Alqithami | Artificial Intelligence | Sustainable Engineering Award

Associate Professor, ALBAHA UNIVERSITY, Saudi Arabia

Saad Alqithami is an Associate Professor in the Department of Computer Science at Albaha University, Saudi Arabia. With a strong background in computer science, he completed his Ph.D. at Southern Illinois University, USA, in 2016. Alqithami has contributed significantly to the fields of social network analysis, AI, and healthcare technology, particularly in the context of Attention Deficit Hyperactivity Disorder (ADHD). His work also extends to network organizations and pandemic modeling. In addition to his teaching role, he has held leadership positions in various administrative capacities at Albaha University, including General Director of Scholarships and University Relations. Alqithami is also a reviewer and program committee member for several academic conferences, contributing to the academic community’s growth. His interdisciplinary approach and commitment to impactful research make him a notable figure in AI and computational science.

Profile

Education

Saad Alqithami holds a Ph.D. in Computer Science from Southern Illinois University, Carbondale, USA, which he completed in December 2016. Prior to that, he earned his Master’s degree in Computer Science from the same institution in August 2012. His foundational education began with a Bachelor’s degree in Computer Science from Taif University, Saudi Arabia, in July 2008. Throughout his academic journey, Alqithami focused on advanced computational intelligence, AI modeling, and networked systems. His doctoral research focused on network organizations and the use of computational models for complex systems. With a deep interest in both theoretical and applied computer science, Alqithami has consistently pursued research that bridges gaps between AI, healthcare, and social systems. His education has provided a robust foundation for his distinguished career in academia and research.

Experience

Dr. Saad Alqithami has over a decade of experience in academia, beginning as a Lecturer in 2015 at Albaha University in Saudi Arabia. He has progressed through various roles, becoming an Assistant Professor in 2017 and later an Associate Professor in 2022. Alqithami has also held significant leadership positions, including Head of the Department of Computer Information Systems and General Director of Scholarships and University Relations at Albaha University. His administrative expertise spans graduate studies, scientific research, and university relations. He has contributed to enhancing the university’s strategic initiatives, especially in research and development. Furthermore, Alqithami has actively engaged in international collaborations, providing expertise in social networks, machine learning, and computational intelligence. He has worked as a Social Networks Analyst and Programmer at Southern Illinois University, where he gained hands-on experience in social network modeling and data analysis, helping shape his interdisciplinary research approach.

Awards and Honors

Dr. Saad Alqithami’s academic journey has been marked by numerous accolades. He was nominated for an outstanding paper award at the 29th AAAI Conference on Artificial Intelligence. As a co-founder, he played a key role in the launch of the “Square-2: The Intelligent Consultant Agent” project, funded by King Abdulaziz City for Science and Technology (KACST). Alqithami also received research funding from Albaha University for two major projects: “Understanding Social Contagion and Viral Spreading of COVID-19” and “An Intelligent Cognitive Modeling for Enhancing the Behavior of Children with ADHD Using a Mixed Reality Environment.” Additionally, he has been honored as a Rosalind Member by the London Journals Press. His work has not only advanced computational intelligence but has also contributed significantly to social good, especially in healthcare and public health contexts, earning him recognition from both academic and scientific communities.

Research Focus

Dr. Saad Alqithami’s research primarily focuses on the application of artificial intelligence, machine learning, and computational models to real-world problems. His work spans several areas, including social network analysis, healthcare technology, and the development of innovative solutions for behavioral health issues like ADHD. Alqithami has contributed to the design of augmented reality environments for therapeutic interventions and has modeled pandemic dynamics in social networks using AI techniques. His interdisciplinary research is aimed at bridging the gap between AI-driven insights and practical applications, particularly in healthcare and networked systems. He is also keen on exploring the implications of social capital in network organizations and improving communication protocols in industrial systems. Alqithami’s work has led to significant publications in peer-reviewed journals and conferences, showcasing his contributions to advancing AI research, particularly its integration into healthcare and societal applications.

Publication Top Notes

  1. Smart Tree Health Assessment Model using Advanced Computer Vision Techniques 🌳📊
  2. A Serious-Gamification Blueprint Towards a Normalized Attention 🧠🎮
  3. Securing Industrial Communication with Software-Defined Networking 🔐🖧
  4. A Generic Encapsulation to Unravel Social Spreading of a Pandemic 🌍💉
  5. Towards Social Capital in a Network Organization 🌐💡
  6. An External Client-Based Approach for Extract Class Refactoring 🔄📚
  7. AR-Therapist: Design and Simulation of an AR-Game for ADHD Patients 🕹️👦
  8. Fluid Dynamics of a Pandemic in a Spatial Social Network 🌍💻
  9. Modeling an AR Serious Game to Increase Attention of ADHD Patients 🎮🧑‍⚕️
  10. Modeling an Augmented Reality Game to Enhance ADHD Behavior 🧠👾

 

 

Armughan Ali | Engineering | Best Researcher Award

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Mr. Armughan Ali | Engineering | Best Researcher Award

Lab Demonstrator, Wah Engineering College, Pakistan

Armughan Ali is a driven and innovative software engineer with a deep focus on artificial intelligence (AI) and its applications in solving real-world challenges. With expertise spanning software development, machine learning (ML), deep learning (DL), and natural language processing (NLP), he specializes in building intelligent systems that enhance efficiency and improve user experiences. Armughan thrives in collaborative environments, leveraging his knowledge of software engineering to create impactful AI-driven solutions. His passion for technology drives him to contribute to cutting-edge projects, making meaningful contributions to the future of AI. He is a published researcher and actively works to bridge the gap between AI theory and practice.

Profile

Google Scholar

Education

Armughan Ali is currently pursuing a Bachelor of Science in Software Engineering at HITEC University, Taxila, Pakistan (2020–2024), where he has excelled in both academic and practical aspects of software engineering. His foundation in engineering principles, coupled with a strong interest in artificial intelligence, positions him as a rising star in the field. Prior to this, Armughan completed his FSC (Pre-Engineering) from Punjab College, Wah-Cantt (2017–2019), where he honed his analytical skills and gained a solid grounding in the sciences. His academic journey has been marked by a commitment to excellence and a passion for emerging technologies, with a focus on AI, machine learning, and software development.

Experience

Armughan Ali’s professional journey includes diverse roles that showcase his versatility and expertise. As a Lab Demonstrator at Wah Engineering College (2024–present), he imparts knowledge to students and fosters a collaborative learning environment. He also serves as a Web Developer on Fiverr (2020–present), where he customizes and develops responsive websites for clients. In his previous role as a Graphic Designer at Graphic Saloon (2023–2024), he created on-brand visuals and marketing materials. Additionally, he contributed to digital solutions as a Digital Solutions Specialist at Ever-Green Corporation (2023), focusing on enhancing the company’s digital presence. He also conducted Front-End Development workshops at HITEC University in 2023, training participants on web technologies like HTML, CSS, and JavaScript. These varied experiences underscore his technical, teaching, and leadership capabilities.

Awards and Honors

Armughan Ali has received numerous accolades, affirming his talent and leadership in the tech community. He is the founder and organizer of the prestigious “CodeWar” event at HITEC University, which has become a significant programming competition. His leadership and dedication have been recognized across multiple seasons, including CodeWar Season I, II, and III (2022-2024). In addition to his role as an organizer, Armughan’s talent in math and programming has earned him awards such as the Math Genius and Speed Programming titles at TECTIQS’ 19 and 18 (IQRA University). These honors highlight his exceptional problem-solving skills and contributions to academic and extracurricular activities. His achievements reflect his commitment to advancing his skills and fostering a culture of innovation.

Certifications

Armughan Ali has demonstrated a strong commitment to expanding his technical knowledge through numerous certifications in the fields of software engineering, artificial intelligence, and machine learning. Notable certifications include IBM Full Stack Software Developer (2024), Machine Learning (2024), and Google Advanced Data Analytics (2024). Additionally, he has completed training in AI/ML, .NET FullStack Development, and deep learning, further honing his skills in these advanced domains. His continuous learning approach also led him to certifications in cybersecurity, project management, and various front-end technologies. These certifications attest to his technical proficiency and eagerness to stay ahead of industry trends. Armughan’s focus on continuous education empowers him to tackle complex challenges with confidence and agility.

Research Focus

Armughan Ali’s research interests lie at the intersection of artificial intelligence, machine learning, and healthcare. His work focuses on applying AI to solve complex real-world problems, particularly in disease detection and classification. He has co-authored several research papers on topics such as Alzheimer’s disease prediction, fake news classification, and skin cancer detection using deep learning techniques. His recent research involves the use of vision transformers for medical imaging, including cancer detection and stomach gastric detection. Armughan is also exploring the use of ensemble learning models for improving the accuracy of AI systems in real-world applications. His contributions to AI-driven healthcare research aim to advance the potential of technology in improving patient outcomes. With a deep interest in creating explainable AI models, Armughan strives to enhance transparency in AI decision-making processes.

Publication Top Notes

  1. X-News Dataset for Online News Categorization 📊
  2. xCViT: An Improved Vision Transformer Network for Skin Disease Classification 🧑‍⚕️
  3. An Optimized Weighted Voting-Based Ensemble Learning Approach for Fake News Classification 📰
  4. Enhancing Disability-Inclusive Communication Through DynaFuseNet and Transformer Models for Sign Language Interpretation 🦻
  5. Convolutional Transformer-Based Few-Shot Learning for Stomach Gastric Detection 🍽️
  6. Alzheimer’s Disease Prediction at Early Stage Using Vision Transformer Architecture 🧠
  7. An Efficient Approach for Plant Leaf Disease Detection Using Vision Transformer Architecture 🌿

 

Mathieu Chartier | Computer Science and Artificial Intelligence | Best Researcher Award

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Mr. Mathieu Chartier | Computer Science and Artificial Intelligence | Best Researcher Award

PhD student, Poitiers University, France 

Mathieu Chartier is a digital humanities researcher, educator, and web professional based in Buxerolles, France. With expertise in natural language processing (NLP) and information retrieval, he bridges technology and history. Mathieu is an independent consultant at Internet-Formation, specializing in digital training, web marketing, and development. A multilingual scholar, he holds a strong academic background in humanities and digital tools, delivering courses on SEO, AI, and digital communication. As a prolific author, Mathieu has written several books and articles about web technologies and marketing. His current PhD research focuses on improving historical data analysis using AI.

Profile

Orcid

Education

Mathieu Chartier earned a Research Master’s in Ancient and Medieval Archaeology (2008) and a Professional Master’s in Information and Communication, Web Editorial Specialization (2009) from Poitiers University. Currently, he is pursuing a PhD in Digital Humanities, focusing on improving information retrieval in historical research through advanced NLP and large language models. Over the years, Mathieu has also acquired certifications in Google Ads and Google Analytics, enhancing his expertise in digital marketing. His interdisciplinary education combines humanities, web technology, and artificial intelligence.

Experience

With a career spanning over 15 years, Mathieu Chartier has held several key roles in academia and industry. As a freelancer, he leads Internet-Formation, providing training in web marketing, SEO, and digital communication. He has been an adjunct lecturer at institutions like the University of Poitiers and Paris-Sorbonne, teaching digital skills, including web marketing, SEO/SEA, and AI. Mathieu has authored multiple books on SEO and Google Ads and has worked as a web editor for the CNED. He has a deep understanding of web technologies, programming, and digital marketing.

Research Focus

Mathieu Chartier’s research in Digital Humanities focuses on enhancing historical data retrieval using Natural Language Processing (NLP) and Large Language Models (LLM). His work aims to develop innovative methods for historical inquiry, applying cutting-edge AI techniques to optimize information retrieval in history. Mathieu’s interdisciplinary approach blends technology and history, making significant contributions to both fields. His current research project, HiBenchLLM, investigates how to benchmark historical inquiries using LLMs, pushing the boundaries of digital history and artificial intelligence.

Publications

  • HiBenchLLM: Historical Inquiry Benchmarking for Large Language Models (2024) 📜🤖
  • Techniques de référencement web : audit et suivi SEO – 5th edition (2024) 📚💻
  • Google Ads : 60 fiches pour obtenir les certifications officielles (2022) 📘📈
  • Guide complet des réseaux sociaux (2013) 🌐📱
  • Le guide du référencement web (2013) 🔍🌍
  • Du bon usage des réseaux sociaux (BioContact n°313) 🗣️💬
  • Vie privée, l’enjeu du moment (BioContact n°272) 🔐📚
  • Media queries CSS3 pour le web mobile (Oracom, WebDesign magazine) 📱💻

ALEXANDRU-SILVIU | Artificial Intelligence Awards | Excellence in Research

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ALEXANDRU-SILVIU | Artificial Intelligence Awards | Excellence in Research

Goga Alexandru Silviu is a seasoned lawyer and entrepreneur based in Brașov, Romania, with over a decade of legal expertise. As the owner of Cabinet de Avocat Goga Alexandru Silviu since 2013, he specializes in corporate law, tax litigation, and labor law. Goga is also pursuing a PhD in Artificial Intelligence at Universitatea Transilvania, reflecting his commitment to integrating technology into legal practices. He has authored several publications, contributing to legal scholarship in Romania, particularly in criminal law and the implications of artificial intelligence. Known for his excellent communication and mentoring skills, he actively trains junior lawyers and students in the field. Goga’s diverse client base includes international organizations and prominent companies, showcasing his extensive professional network and trust in his legal services. 🌟

Profile

Google Scholar

Strengths for the Award

  1. Extensive Legal Experience: Goga Alexandru Silviu has over a decade of experience in various areas of law, including corporate law, labor law, and tax litigation. His extensive practice as a lawyer and owner of a legal cabinet demonstrates significant expertise.
  2. Diverse Clientele: His work with a range of important clients, including international foundations and companies, indicates a robust professional network and trust in his legal capabilities.
  3. Academic Contributions: His publications, particularly in criminal law and the advent of artificial intelligence, showcase a commitment to advancing legal scholarship. His books and articles have received citations, highlighting their relevance and impact in the field.
  4. Teaching and Mentorship: His role as an associate teaching assistant and mentor to junior lawyers and law students reflects his dedication to education and the development of future legal professionals.
  5. Multilingual Proficiency: Goga’s proficiency in multiple languages enhances his ability to engage with diverse clients and collaborate internationally, a valuable asset in today’s globalized legal environment.
  6. Research in Emerging Areas: His current PhD studies in artificial intelligence suggest a forward-thinking approach to law, preparing for the evolving intersection of technology and legal practice.

Areas for Improvement

  1. Research Focus: While Goga has published on various topics, narrowing his focus to a specific niche within law could enhance his expertise and recognition in that area.
  2. Networking Beyond Legal Circles: Engaging with interdisciplinary fields related to artificial intelligence, such as technology and ethics, could broaden his influence and collaboration opportunities.
  3. Public Speaking and Workshops: Developing skills in public speaking and leading workshops could increase his visibility and thought leadership within the legal community.
  4. Community Engagement: Expanding his outreach efforts within local communities, perhaps through pro bono work or legal education initiatives, could enhance his profile and commitment to social responsibility.

Education 

Goga Alexandru Silviu’s educational background is rooted in law, starting with a Bachelor’s degree from Transilvania University, where he graduated with distinction. He furthered his studies by obtaining a Master’s degree in European Law and Judicial Career, again achieving the prestigious “Summa Cum Laude” honor. He completed Initial Vocational Training for lawyers through INPPA, enhancing his practical legal skills. Additionally, he holds a CNFPA certificate as a communication specialist and has training in managing European Funds Projects. Currently, Goga is advancing his knowledge as a PhD student in Artificial Intelligence at Universitatea Transilvania, focusing on the intersection of technology and law. His dedication to continuous learning positions him at the forefront of modern legal practice. 📚

Experience 

With a robust career spanning over a decade, Goga Alexandru Silviu has built a diverse portfolio of legal expertise. Since December 2013, he has served as the owner and lawyer at Cabinet de Avocat Goga Alexandru Silviu, specializing in corporate law, tax litigation, and labor law. His clientele includes notable organizations such as the Prince of Wales Foundation in Romania and D-Play Sport, among others. Goga has also held significant roles in various companies, including Chief Executive Officer at Oil Trade Masters SRL and legal advisor at several firms across different sectors, including construction and marketing. His previous academic experience as an associate teaching assistant at Transilvania University underscores his commitment to education and mentoring the next generation of legal professionals. Goga’s extensive experience allows him to navigate complex legal landscapes effectively, making him a trusted advisor to his clients. ⚖️

Research Focus 

Goga Alexandru Silviu’s research focus centers on the evolving intersections of law and technology, particularly in the realm of artificial intelligence and its implications for legal practice. As a current PhD student at Universitatea Transilvania, he aims to explore how AI can reshape legal frameworks, enhance legal processes, and improve accessibility to legal resources. His prior publications address critical issues in criminal law, data protection, and the implications of AI on legal standards and practices. Through his research, Goga seeks to contribute to contemporary legal discourse and offer insights that can guide future legislation and policy-making in Romania and beyond. His commitment to exploring innovative solutions in law positions him as a forward-thinking legal scholar, dedicated to bridging traditional legal practices with modern technological advancements. 🔍

Publication Top Notes

  • New Criminal Laws of Romania (February 2014) 📖
  • Repere actuale din jurisprudenta Curtii Constitutionale a Romaniei (2012) 📚
  • Manualul Tanarului Consilier Juridic (2011) 📘
  • New Criminal Laws of Romania — Ten Years After (2024) 📅
  • Manualul Tanarului Avocat Stagiar sau un Altfel de OEPA (December 2023) 📑
  • The Advent of Artificial Intelligence (December 2023) 🌐
  • Trends Regarding Fines and Sanctions in Competition Law, Labor Law and Data Protection Law (2019) 📊
  • Teaching Law Students via Online—Challenges and Opportunities (2021) 💻
  • Unconstitutionality of the New Criminal and Penitentiary Laws (2016) ⚖️
  • Exclusion of a Member of a Political Party: Unconstitutional Provisions of the Law on Political Parties (2015) 🗳️
  • Recent Considerations on the Institution of Probation (2013) ⏳
  • Notes and Proposals Regarding the Changes and Amendments to the Romanian Constitution (2013) 📜

Conclusion

Goga Alexandru Silviu demonstrates a strong profile for the Research for Excellence in Research award, with his extensive legal experience, diverse publications, and commitment to education. By focusing on specific areas of expertise and enhancing his public engagement, he can further solidify his standing in the legal community and contribute meaningfully to the evolving field of law.

 

 

Zdzislaw Kowalczuk | Artificial Intelligence Award | Best Researcher Award

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Prof Zdzislaw Kowalczuk | Artificial Intelligence Award | Best Researcher Award

Prof Zdzislaw Kowalczuk , Gdansk University of Technology , Poland

Zdzisław Kowalczuk, Senior Member of IEEE, has been a Full Professor in automatic control and robotics at Gdańsk University of Technology since 1978. He has held visiting positions at University of Oulu, Australian National University, Technische Hochschule Darmstadt, and George Mason University. His research interests include robotics, control theory, AI, and system diagnostics. Kowalczuk has authored 30 books, over 120 journal papers, and 350+ conference publications, with over 3,300 Google Scholar citations and an H-index of 21. He is President of the Polish Consultants Society and founder of PWNT publishing house, receiving numerous awards, including the SEP Medal in 2014. 🎓📚🏅

 

Publication profile 

Google scholar

Academic Background 🎓

Zdzisław Kowalczuk (Senior Member, IEEE) has been with the Faculty of Electronics, Telecomm., and Informatics at Gdańsk University of Technology since 1978. He is a Full Professor in automatic control and robotics and the Chair of the Dept. of Robotics and Decision Systems. He has held visiting appointments at universities including Oulu, Australian National University, Technische Hochschule Darmstadt, and George Mason University.

Scientific Contributions 

His main scientific interests include robotics, control theory, system modeling, diagnostics, artificial intelligence, and control engineering. Kowalczuk has authored/co-authored about 30 books, over 120 journal papers, and over 350 conference publications. His Google Scholar citation index exceeds 3,300, with an H-index of 21.

Research Focus

Zdzisław Kowalczuk’s research focuses on several key areas within engineering and computer science. His primary interests include fault diagnosis and detection, particularly for automotive engines, and the development of intelligent systems for autonomous decision-making. He also explores system modeling and control theory, including the application of artificial intelligence and neural networks. Kowalczuk’s work extends to robotics, adaptive systems, and signal processing, with a notable focus on practical applications like leak detection in pipelines and thermal management in buildings. His contributions span theoretical foundations to real-world implementations, demonstrating a versatile and impactful research portfolio. 🚗🤖📊🔧

 

Publication Top Notes

Fault diagnicial intelligence, applications – J Korbicz, JM Koscielny, Z Kowalczuk, W Cholewa, Springer Science & Business Media, 2012, cited by 1064 📚osis: models, artif

Diagnostyka procesów: modele: metody sztucznej inteligencji: zastosowania – J Korbicz, JM Kościelny, Z Kowalczuk, W Cholewa, Wydawnictwa Naukowo-Techniczne, 2002, cited by 345 📘

Model based diagnosis for automotive engines-algorithm development and testing on a production vehicle – J Gerler, M Costin, X Fang, Z Kowalczuk, M Kunwer, R Monajemy, IEEE Transactions on Control Systems Technology, 1995, cited by 148 🚗

Thermal Barrier as a technique of indirect heating and cooling for residential buildings – M Krzaczek, Z Kowalczuk, Energy and Buildings, 2011, cited by 107 🏠

Model-based on-board fault detection and diagnosis for automotive engines – JJ Gertler, M Costin, X Fang, R Hira, Z Kowalczuk, Q Luo, Control Engineering Practice, 1993, cited by 100 🚗

Autonomous driver based on an intelligent system of decision-making – M Czubenko, Z Kowalczuk, A Ordys, Cognitive computation, 2015, cited by 98 🚘

Discrete approximation of continuous-time systems: a survey – Z Kowalczuk, IEE Proceedings G (Circuits, Devices and Systems), 1993, cited by 84 📈

Computational approaches to modeling artificial emotion–an overview of the proposed solutions – Z Kowalczuk, M Czubenko, Frontiers in Robotics and AI, 2016, cited by 75 🤖

Continuous-time approaches to identification of continuous-time systems – Z Kowalczuk, J Kozłowski, Automatica, 2000, cited by 49 ⏱️

Intelligent decision-making system for autonomous robots – Z Kowalczuk, M Czubenko, Uniwersytet Zielonogórski, 2011, cited by 38 🤖

Detecting and locating leaks in transmission pipelines – Z Kowalczuk, K Gunawickrama, Fault Diagnosis: Models, Artificial Intelligence, Applications, 2004, cited by 36 🛠️📈