Hamna Baig | Artificial Intelligence | Young Researcher Award

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Ms. Hamna Baig | Artificial Intelligence | Young Researcher Award

Research Internee | COMSATS University Islamabad, Attock Campus | Pakistan

Hamna Baig πŸŽ“ is a passionate and award-winning Electrical Engineering graduate from COMSATS University Islamabad, Attock Campus. A gold medalist πŸ₯‡ with a CGPA of 3.66, she blends academic brilliance with innovative research in AI, IoT, and robotics πŸ€–. Hamna’s dynamic work spans smart environments, RF sensing, and machine learning applications πŸ’‘. She has published multiple research papers πŸ“š, led various technical projects, and participated in prestigious conferences πŸ›οΈ. Her leadership roles and technical writing expertise further reflect her versatility 🧠. Hamna aims to revolutionize engineering solutions through creativity, technology, and social impact 🌍.

Professional profile :Β 

Google Scholar

OrcidΒ 

Summary of Suitability :Β 

Hamna Baig exemplifies the essence of a young and emerging researcher through her exceptional academic performance, innovative contributions to AI-driven engineering, and a prolific portfolio of research publications. A gold medalist in Electrical Engineering from COMSATS University Islamabad, she has demonstrated consistent excellence in both theoretical knowledge and practical application. With multiple high-impact publications, advanced project implementations, and recognized conference presentations, she brings outstanding promise to the future of intelligent systems and healthcare engineering. Her dedication to interdisciplinary innovation, backed by hands-on experience and leadership roles, showcases her as a rising star in engineering research.

πŸ”Ή Education & Experience :

πŸ“˜ Education:

  • πŸŽ“ B.Sc. Electrical Engineering, COMSATS University Islamabad, Attock Campus (2020–2024) – CGPA: 3.66/4.00, Gold Medalist πŸ…

  • πŸ“‘ Final Year Project: AI-based Environmental Control Model for Smart Homes πŸ πŸ€–

πŸ§‘β€πŸ’Ό Experience:

  • πŸ§ͺ Internee, Electrical & Computer Engineering Dept., COMSATS, under PEC GIT Program (2024–Present)

  • ⚑ Internee, Ghazi-Barotha Hydro Power Plant (GBHPP), WAPDA (2023)

  • πŸ–‹οΈ Technical Writer (Electrical/Electronics), CDR Professionals (2023–Present)

Professional Development :

Hamna Baig has actively pursued professional growth through certifications, leadership, and community engagement 🌱. She completed the prestigious “Machine Learning Specialization” by DeepLearning.AI πŸ€–, “Generative AI for Everyone” 🧠, and several tech courses from Stanford, Yonsei, and the University of Michigan via Coursera πŸŽ“. As a proactive learner, she enhances her skills in AI, IoT, wireless communication, and public speaking 🎀. Hamna has held key roles such as President of the Sports Society 🏸, Co-Campus Director of AICP πŸ§‘β€πŸ”¬, and VP of COMSATS Science Society. Her drive to uplift communities and advance technology sets her apart 🌟.

Research Focus :Β 

Hamna’s research centers on the integration of Artificial Intelligence and Machine Learning into real-world electrical and biomedical systems πŸ€–πŸ§ . She explores SDR-based gait monitoring for Parkinson’s patients πŸ§“, AI-controlled environmental systems for energy-efficient smart homes 🌑️, and intelligent robotic applications in agriculture πŸ€–πŸŽ. Her work emphasizes non-invasive health monitoring using RF sensing πŸ›οΈ and AI-powered automation solutions. She is deeply invested in translating complex algorithms into practical, user-centric applications that elevate health, comfort, and productivity ⚑. Her interdisciplinary approach bridges electrical engineering with innovative computing solutions πŸ”ŒπŸ“Š.

Awards & Honors :

  • πŸ† Awards & Certificates:

    • πŸ₯‡ Gold Medalist, COMSATS University Islamabad (2024)

    • 🧾 Certificate of Gratitude, ICTIS Conference, UET Peshawar (2024)

    • πŸ“œ Certificate of Gratitude, ICCSI Conference, University of Haripur (2024)

    • 🧠 ML Specialization Certificate, DeepLearning.AI – Stanford (2023)

    • 🧬 Generative AI for Everyone – DeepLearning.AI (2025)

    • πŸ§β€β™€οΈ Public Speaking Specialization – University of Michigan (2024)

    • πŸ“Ά Wireless Communications Course – Yonsei University (2024)

    • πŸŽ“ Prime Minister’s Youth Laptop Scheme Awardee (2023)

    • πŸ₯‡ Winner – IoT Pick and Place Robotic Competition, COMSATS (2024)

    • πŸ§’ Student of the Year – COMSATS University, Attock (2023)

Publication Top Notes :Β 

  • β€’ Title: Intelligent Frozen Gait Monitoring using Software Defined Radio Frequency Sensing
    Citation: Electronics, 14(8), 1603, 2025
    Authors: Khan, M. B., Baig, H., Hayat, R., Tanoli, S. A. K., Rehman, M., Thakor, V. A., & Haider, D.
    Year: 2025

  • β€’ Title: Machine Learning-Based Estimation of End Effector Position in Three-Dimension Robotic Workspace
    Citation: IJIST Journal (Impact Factor: 4.312)
    Authors: Baig, H., Ahmed, E., Jadoon, I., & Pakistan, K. C. A.
    Year: 2024

  • β€’ Title: A Robotic Approach for Fruit Harvesting with Machine Learning-Based Joint Angles Prediction
    Citation: Submitted to ICCSI – International Conference on Computational Sciences and Innovations
    Authors: Baig, H., Baig, A.A, Ahmed, E., Jadoon, I., & Pakistan
    Year: 2024

  • β€’ Title: Artificial Intelligence Based Adaptive Fan Control in Office Settings for Energy Efficiency
    Citation: Submitted to ICCIS – Proceedings to Springer Journal
    Authors: Baig, H.
    Year: 2024

  • β€’ Title: A Robotic Arm Based Intelligent Biopsy System
    Citation: Submitted to ICCIS – Kohat University, Springer Proceedings
    Authors: Baig, H.
    Year: 2024

  • β€’ Title: Design of an Intelligent Wireless Channel State Information Sensing System to Prevent Bedsores
    Citation: IEEE Sensors Journal (Under Review)
    Authors: Baig, H.
    Year: 2024

  • β€’ Title: Enhancing Home Comfort and Energy Consumption with an Artificial Intelligence-Based Environmental Sensing Control Model
    Citation: PeerJ (Computer Science) (Under Review)
    Authors: Baig, H.
    Year: 2024

  • β€’ Title: Breathing Techniques Redefined: The Pros and Cons of Traditional Methods and the Promise of SDRF Sensing
    Citation: Elsevier – Digital Communications and Networks (Under Review)
    Authors: Baig, H.
    Year: 2024

Conclusion :Β 

  • Hamna Baig not only meets but exceeds the expectations of a Young Researcher Award recipient. Her innovative mindset, research productivity, and real-world problem-solving approach make her an ideal candidate. Her work is not just academically sound but socially impactfulβ€”especially in the domains of healthcare and automation. She is a beacon of excellence and innovation, representing the future of engineering research. 🌟

 

Dr. Ryszard Δ†wiertniak | Artificial Intelligence | Best Researcher Award

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Dr. Ryszard Δ†wiertniak | Artificial Intelligence | Best Researcher Award

Dr. Ryszard Δ†wiertniak, Krakow University of Economics, Poland

Dr. Ryszard Δ†wiertniak is an accomplished expert in project management, specializing in agile methodologies, Design Thinking, and AI-driven innovation. He holds a PhD in Management and Quality Sciences from the University of Economics in Krakow and has a strong academic and professional background in administration, management, and electrical engineering. With extensive experience in research and teaching, he has contributed to the fields of digital transformation, e-learning, and Industry 4.0. As an IBM Design Thinking mentor and Early Warning Europe ambassador, he helps businesses implement cutting-edge solutions. His work spans academia, consulting, and applied research in AI and business process optimization.

🌍 Professional Profile:

Orcid

Google Scholar

πŸ† Suitability for Best Researcher AwardΒ 

Dr. Ryszard Δ†wiertniak’s pioneering research in AI-driven project management, digital transformation, and innovation management makes him an outstanding candidate for the Best Researcher Award. His involvement in Erasmus+ projects, contributions to Industry 4.0, and mentorship in agile methodologies showcase his impact on academia and industry. His expertise in AI-based decision-making, personalized education, and digital business models has transformed organizational processes. With numerous peer-reviewed publications, a book, and a grant-winning project, his research advances the future of smart business ecosystems. His leadership in AI-powered business solutions and educational innovations solidifies his reputation as a top researcher in the field.

πŸŽ“ EducationΒ 

Dr. Ryszard Δ†wiertniak earned his PhD in Management and Quality Sciences from the University of Economics in Krakow (2019), focusing on innovation management. He also holds a Master’s degree in Administration and Management from the University of Warsaw (1994). In addition, he has a background in electrical engineering, equipping him with a multidisciplinary approach to research. His academic journey reflects a deep commitment to combining management principles with technology, particularly in AI applications, e-learning, and agile business strategies. His education has laid the foundation for his expertise in digital transformation, business innovation, and advanced project management methodologies.

πŸ’Ό Professional ExperienceΒ 

Dr. Δ†wiertniak currently serves as an academic teacher at Krakow University of Economics, specializing in technology and product ecology. Previously, he was the Rector’s Representative for Quality of Education and E-learning at the College of Economics and Computer Science (2020–2024). His role in the Early Warning Europe initiative highlights his expertise in digital business transformation. He also contributes to the Erasmus+ program, working on AI-powered educational solutions. As an IBM Design Thinking mentor, he facilitates agile project implementation. His professional engagements bridge academia and industry, driving innovation, AI adoption, and digital business strategies in various sectors.

πŸ… Awards and HonorsΒ 

πŸ”Ή Early Warning Europe Ambassador (2021–Present) – Recognized for supporting digital business transformation.
πŸ”Ή Erasmus+ Research Grant Recipient – Contributed to AI-driven education models.
πŸ”Ή Ministerial Research Grant Winner (2021) – Awarded funding for advancing e-learning and digital education techniques.
πŸ”Ή IBM Design Thinking Mentor – Certified expert in guiding agile and innovative project execution.
πŸ”Ή Industry 4.0 & AI Innovation Contributor – Acknowledged for pioneering work in integrating AI with project management and digital marketing.
πŸ”Ή Invited Researcher at THWS Business School (2024) – Recognized for leadership in AI-based digital transformation.

His contributions to AI, project management, and education technology have earned him national and international acclaim.

πŸ”¬ Research Focus

Dr. Δ†wiertniak’s research spans AI-driven project management, innovation strategies, digital transformation, and e-learning technologies. He explores Industry 4.0 applications, AI-based decision-making, and agile methodologies to optimize business processes. His focus on digital business models, social media analytics, and e-commerce strategies has redefined marketing and management practices. Through Design Thinking and AI integration, he enhances project execution efficiency. His research also covers personalized education using AI, ensuring smarter, data-driven learning environments. As an expert in AI-powered business solutions, he contributes to making organizations more adaptable and efficient in an era of rapid technological advancements.

πŸ“ŠΒ Publication Top Notes:

  1. Rola potencjaΕ‚u innowacyjnego w modelach biznesowych nowoczesnych organizacji – prΓ³ba oceny

    • Citations: 11
    • Year: 2015

  2. ZarzΔ…dzanie portfelem projektΓ³w w organizacji: Koncepcje i kierunki badaΕ„

    • Citations: 4
    • Year: 2018

  1. Addressing students’ perceived value with the virtual university concept

    • Citations: 3
    • Year: 2022

  2. KsztaΕ‚towanie portfela projektΓ³w w zarzΔ…dzaniu innowacjami

    • Citations: 2
    • Year: 2018

  1. The concept of project evaluation in the implementation of innovation

    • Citations: 1
    • Year: 2020

 

 

Prof. Dr. Xin Wang | Distributed AI | Best Researcher Award

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Prof. Dr. Xin Wang | Distributed AI | Best Researcher Award

Prof. Dr. Xin Wang, Qilu University of Technology, China

Prof. Dr. Xin Wang is a distinguished scholar in Distributed AIΒ and Federated Learning, currently serving as a Professor at Shandong Computer Science Center, Qilu University of Technology. With a Ph.D. in Control Science and Engineering from Zhejiang University, he has contributed significantly to AI Security, Privacy, and LLM Security. Dr. Wang has led multiple national research projects and received prestigious honors, including the Taishan Scholars Award and the Shandong Provincial Science and Technology Progress Award. His work integrates AI with secure computing, enhancing privacy protection and optimization in collaborative learning systems.

🌍 Professional Profile:

Google Scholar

πŸ† Suitability for AwardΒ 

Dr. Xin Wang’s outstanding contributions to Distributed AI, Federated Learning, and AI Security make him a strong candidate for the Best Researcher Award. As a leader in AI-driven security frameworks, he has spearheaded national-level projects focusing on privacy-preserving AI and secure learning models. His research bridges theory with practical applications, enhancing security in multi-agent and industrial IoT systems. Recognized for his high-impact publications and award-winning research, Dr. Wang’s innovations in cryptographic function identification and UAV data collection optimization demonstrate exceptional originality and real-world relevance, solidifying his place as a leader in computational intelligence and AI security.

πŸŽ“ EducationΒ 

  • Ph.D. in Control Science and Engineering (2015-2020) – Zhejiang University, supervised by Prof. Peng Cheng & Prof. Jiming Chen, specializing in AI Security and Distributed Intelligence.
  • Visiting Scholar in Information Security (2018-2019) – Tokyo Institute of Technology, mentored by Prof. Hideaki Ishii, focusing on cryptographic vulnerabilities and federated learning security.

His multidisciplinary training across AI, security, and automation has positioned him at the forefront of cutting-edge computational research.

πŸ’Ό ExperienceΒ 

  • Professor (2024–Present) – Shandong Computer Science Center, Qilu University of Technology.
  • Associate Professor (2020–2024) – Shandong Computer Science Center, leading research on privacy protection in collaborative AI.
  • Project PI in National Natural Science Foundation of China (2025-2027) – Developing privacy-preserving defense mechanisms for federated learning.
  • Project PI in National Key Research and Development Program (2021-2024) – Developing AI-driven meta-services for cloud-based industrial manufacturing.
  • Visiting Scholar (2018-2019) – Tokyo Institute of Technology, conducting security research on cryptographic vulnerabilities in multi-agent IoT systems.

πŸ… Awards and HonorsΒ 

  • Taishan Scholars Award (2024) πŸ… – Recognized for research excellence in AI security and distributed systems.
  • Leader of Youth Innovation Team (2022) πŸš€ – Acknowledged for driving innovation in Shandong Higher Education Institutions.
  • Second Prize, Shandong Provincial Science and Technology Progress Award (2022) πŸ† – Contributions to federated learning and privacy-preserving AI.
  • Best Paper Award, CCSICC’21 πŸ“„ – Vulnerability Analysis for IoT Devices in Multi-Agent Systems.
  • Best Paper Award, ICAUS’24 ✈️ – Optimized Data Collection for UAVs in Industrial IoT Environments.

πŸ”¬ Research FocusΒ 

Dr. Wang specializes in Distributed AI, Federated Learning, and AI Security & Privacy. His research integrates cryptographic techniques, optimization algorithms, and adversarial defenses to improve the security of collaborative learning models. He has pioneered LLM security frameworks to safeguard against data leakage and adversarial attacks. His work extends into privacy-preserving AI for multi-agent IoT systems and UAV data collection efficiency. Through national projects, he has developed secure meta-services for cloud computing, advancing the field of intelligent automation and resilient AI architectures for real-world deployment in cyber-physical systems and industrial environments.

πŸ“Š Publication Top notes:

  • Title: Privacy-Preserving Distributed Machine Learning via Local Randomization and ADMM Perturbation
    • Year: 2020
    • Citations: 61
  • Title: Privacy-Preserving Collaborative Computing: Heterogeneous Privacy Guarantee and Efficient Incentive Mechanism
    • Year: 2018
    • Citations: 49
  • Title: Differentially Private Maximum Consensus: Design, Analysis and Impossibility Result
    • Year: 2018
    • Citations: 26
  • Title: Dynamic Privacy-Aware Collaborative Schemes for Average Computation: A Multi-Time Reporting Case
    • Year: 2021
    • Citations: 18
  • Title: Leveraging UAV-RIS Reflects to Improve the Security Performance of Wireless Network Systems
    • Year: 2023
    • Citations: 17

 

Prof. Ching Yee Suen | Artificial Intelligence | Best Researcher Award

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Prof. Ching Yee Suen | Artificial Intelligence | Best Researcher Award

Prof. Ching Yee Suen, Concordia University, Canada

Prof. Ching Yee Suen is a globally recognized expert in Pattern Recognition, AI, and Document Analysis. As the Founding Director and Co-Director of CENPARMI at Concordia University, he has shaped advancements in handwriting recognition, multiple classifiers, and font analysis. A Fellow of IEEE, IAPR, and the Royal Society of Canada, he has mentored 120+ graduate students and 100 visiting scientists. With 550+ research papers, 16 books, and an h-index of 74, his contributions are widely cited. His innovations power millions of devices worldwide. He has led $20M+ research projects, collaborated with global industries, and serves as an editor for top-tier journals.

🌍 Professional Profile:

Google Scholar

πŸ† Suitability for Best Researcher AwardΒ 

Prof. Suen is an exceptional candidate for the Best Researcher Award due to his pioneering contributions in AI, pattern recognition, and handwriting analysis. His research has real-world impact, with millions of users benefiting from his handwriting recognition algorithms. He has received top international awards, including the King-Sun Fu Prize (2021) and ICDAR Award (2005). As a leading AI researcher, he has secured $20M+ in funding, supervised over 120 Ph.D. and master’s students, and led groundbreaking industrial collaborations. His global influence, leadership in AI, and outstanding research output make him a worthy recipient of this prestigious honor.

πŸŽ“ EducationΒ 

Prof. Ching Yee Suen holds a Ph.D. from the University of British Columbia (UBC), Vancouver, and a Master’s degree from the University of Hong Kong. His academic journey has been marked by a deep focus on Artificial Intelligence, Pattern Recognition, and Computational Vision. His early research laid the foundation for his groundbreaking work in handwriting recognition, document analysis, and AI-powered classification systems. He has spent sabbatical leaves at MIT, McGill University, Ecole Polytechnique, and IBM, further expanding his expertise. His academic credentials have established him as a leading scholar in AI and pattern recognition on a global scale.

πŸ’Ό ExperienceΒ 

With a career spanning 50+ years, Prof. Suen has held key leadership roles at Concordia University, serving as Chairman of Computer Science, Associate Dean (Research), and Concordia Chair in AI & Pattern Recognition. He is the Founding Director and Co-Director of CENPARMI, where he has driven cutting-edge research. He has supervised 120+ graduate students and collaborated with top institutions worldwide. As a consultant to Microsoft, Xerox, Canada Post, and the US Congress, his work has had real-world impact. His editorial leadership in top AI journals and conference organization further cements his global influence in the research community.

πŸ… Awards and Honors

Prof. Suen’s excellence is recognized globally, earning him top honors in AI and pattern recognition. He received the King-Sun Fu Prize (2021) πŸ†, the ICDAR Award (2005) πŸŽ–οΈ, and the Elsevier Distinguished Editorial Award (2016)πŸ“œ. His Concordia Lifetime Research Achievement Award (2008) and Teaching Excellence Award (1995) πŸŽ“ highlight his impact in academia. Internationally, he was honored with the Gold Medal from the University of Bari, Italy (2012) πŸ₯‡. As a Fellow of IEEE, IAPR, and the Royal Society of Canada, his contributions to AI, document analysis, and handwriting recognition are celebrated at the highest levels.

πŸ”¬ Research FocusΒ 

Prof. Suen specializes in Pattern Recognition, Artificial Intelligence, and Document Analysis. His innovations in handwriting recognition, fake coin detection, license plate recognition, and multi-classifier systems have transformed industry applications. His research integrates AI, deep learning, and image processing to solve complex problems in computer vision, natural language processing, and fraud detection. His high-impact contributions are widely used in mobile devices, banking security, and postal services. His multi-disciplinary approach in AI has led to real-world solutions adopted by Microsoft, Bell Canada, Canada Post, and global tech firms, making him a pioneer in intelligent pattern analysis.

πŸ“Š Publication Top notes:

  • Title: Developing Knowledge Management Metrics for Measuring Intellectual Capital
    • Year: 2000
    • Citations: 442
  • Title: Modified Hebbian Learning for Curve and Surface Fitting
    • Year: 1992
    • Citations: 322
  • Title: N-Gram Statistics for Natural Language Understanding and Text Processing
    • Year: 1979
    • Citations: 315
  • Title: Analysis and Design of a Decision Tree Based on Entropy Reduction and Its Application to Large Character Set Recognition
    • Year: 1984
    • Citations: 176
  • Title: Large Tree Classifier with Heuristic Search and Global Training
    • Year: 1987
    • Citations: 102

 

 

Mr. Yeonsoo Kim | AI Network Awards | Best Researcher Award

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Mr. Yeonsoo Kim | AI Network Awards | Best Researcher Award

Mr. Yeonsoo Kim, Surromind, South Korea

Yeonsoo Kim is a South Korean researcher specializing in AI and robotics development, with a particular focus on data analytics and autonomous systems. Currently, Yeonsoo is a researcher at Surromind in Seoul, where they contribute to advanced robotics and AI projects. With prior experience as a researcher at HnT in Suwon and an internship at the Korea Railroad Research Institute in Uiwang, Yeonsoo has developed a robust skill set in data-driven innovation. Yeonsoo holds degrees in engineering from Kyonggi University and has earned professional certifications in big data analysis and advanced data analytics. Recognized for their contributions to the AI field, Yeonsoo was awarded the ICONI 2023 Outstanding Paper award. Proficient in Python and ROS 2, they are committed to advancing automation and machine learning in applied technology. Yeonsoo’s background reflects a blend of technical expertise and innovation, making them a promising figure in the realm of AI and robotics.

Professional Profile:

Google Scholar

Summary of Suitability for the Award:

Yeonsoo Kim is a promising candidate for the Best Researcher Award due to her strong background in AI and robotics, relevant industry experience, and award-winning contributions to data analytics and advanced technology. Her work in AI and robotics, supported by her roles at prominent research institutions in South Korea, demonstrates her capability to advance these rapidly evolving fields.

πŸŽ“Education :

Yeonsoo Kim pursued their academic journey in engineering at Kyonggi University, South Korea. Beginning their studies in 2017, Yeonsoo completed a bachelor’s degree with a focus on engineering in early 2023 and is currently engaged in postgraduate studies, expected to finish in August 2024. Throughout their education, Yeonsoo specialized in areas integral to modern AI and robotics, such as big data analysis and autonomous systems, equipping them with the theoretical and practical skills necessary for advanced technological development. Their academic experience includes coursework and projects that emphasize AI applications, data analytics, and robotics programming, providing a comprehensive foundation for their research work. With an emphasis on interdisciplinary learning, Yeonsoo’s education has shaped their approach to real-world challenges in robotics and machine learning, further enhanced by certifications in advanced data analytics.

🏒Professional Experience :

Yeonsoo Kim has amassed valuable professional experience in AI, robotics, and data analytics. Currently, they work as a researcher at Surromind in Seoul, where they contribute to AI and robotics projects, integrating machine learning techniques to drive innovations in automation. Previously, Yeonsoo was a researcher at HnT in Suwon from 2022 to early 2024, focusing on the practical application of data analytics in industrial settings. Before that, they interned at the Korea Railroad Research Institute in Uiwang (2021-2022), where they gained hands-on experience in real-time data processing and control systems in transportation. Each role has enhanced their expertise in data-driven research and reinforced their commitment to developing AI-driven technologies. Yeonsoo’s work experience has honed their ability to integrate AI methodologies into various industrial applications, making significant contributions to the fields of robotics and big data.

πŸ…Awards and Honors :

Throughout their career, Yeonsoo Kim has been recognized for their achievements in AI and data analytics. They hold several notable certifications and awards, including the Engineer Big Data Analysis certification, which signifies their advanced skill in managing and interpreting complex datasets. In recognition of their expertise in data science, Yeonsoo earned the Advanced Data Analytics Semi-Professional (ADsP) certificate, a credential that underscores their proficiency in advanced analytics and statistical applications. Yeonsoo’s research contributions have also been acknowledged with the ICONI 2023 Outstanding Paper award, reflecting their ability to produce impactful, high-quality research in AI. These awards and certifications highlight Yeonsoo’s dedication to continuous learning and excellence in data analytics and artificial intelligence, positioning them as a forward-thinking researcher committed to pushing the boundaries of robotics and AI technology.

πŸ”¬Research Focus:

Yeonsoo Kim’s research is centered on the development of AI and robotics, with a focus on integrating big data analytics into autonomous systems. Their work encompasses both software and hardware aspects of robotics, with applications ranging from industrial automation to transportation technology. Yeonsoo’s current role at Surromind involves utilizing AI algorithms to enhance robotic functions, leveraging data analytics to optimize decision-making in autonomous systems. Their previous research at HnT and the Korea Railroad Research Institute focused on real-time data processing and implementing machine learning models for system control, showcasing their versatility across different sectors. With proficiency in Python and ROS 2, Yeonsoo develops scalable, data-driven solutions for complex robotic applications, aiming to make autonomous systems more efficient and adaptable. Their work is driven by a commitment to advancing AI as a transformative tool in robotics, with a special emphasis on data-informed system intelligence.

Publication Top notes:

Title:Β “Autoencoder-Based Cargo Recommendation System with Latent Factor Model”

Citations:Β 1

Title:Β “Deep Learning-Based Freight Recommendation System for Freight Brokerage Platform”
Title:Β “Real-Time Detection of Printing Defects with YOLOv5 Models”
Title:Β “Development of a Human-Following Transport Robot for Collaboration with Railway Workers”
Title:Β “Identifying Process Abnormalities through Real-Time Defect Detection”

 

 

Dr. Kuanxin Shen | Artificial intelligent Awards | Best Researcher Award

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Dr. Kuanxin Shen | Artificial intelligent Awards | Best Researcher Award

Dr. Kuanxin Shen , Shenyang University of Technology , China

Kuanxin Shen, a 27-year-old PhD candidate in Control Science and Engineering at Shenyang University of Technology, China, focuses his research on 3D Gaze Estimation using neural networks and deep learning. He holds a Bachelor’s degree earned in 2021 and a Master’s degree obtained in 2024. From 2022 to 2024, Kuanxin worked as an Algorithm Developer at Ningbo Chunjian Electronic Technology Co., Ltd., specializing in 3D intelligent perception in automotive cockpits. His research achievements include a Chinese utility model patent, several Chinese computer software copyrights, and three Chinese invention patents related to 3D eye tracking and gaze estimation. Kuanxin has also authored a book on industrial robot simulation and published a paper in the journal Sensors. He has been recognized with the third prize in the Henan Province College Students’ Robot Innovation Competition, a first-class academic scholarship, and the Excellent Thesis Award from Liaoning Province for his master’s thesis.

Professional Profile:

Orcid

πŸŽ“Educational Background:

Kuanxin Shen earned his Bachelor’s degree in 2021 and obtained his Master’s degree in 2024. He is currently pursuing a PhD in Control Science and Engineering at Shenyang University of Technology, China.

🏒Work Experience:

From 2022 to 2024, Kuanxin Shen worked as an Algorithm Developer at Ningbo Chunjian Electronic Technology Co., Ltd., specializing in 3D intelligent perception in automotive cockpits. His responsibilities included driver gaze detection, skeleton landmark detection, behavior detection (such as smoking and phone usage), and the detection of driver distraction and fatigue. His tasks encompassed image processing, 3D detection, data annotation, cleaning, augmentation, neural network training, and model testing.

πŸ†Awards and Recognitions:

During his undergraduate studies, Kuanxin Shen won the Third Prize in the 6th Henan Province College Students’ Robot Innovation Competition. In April 2024, he was awarded the First-Class Academic Scholarship during his master’s studies. In May 2024, his master’s thesis titled “Research on the Application of Driver Gaze Estimation Technology in DMS” received the Excellent Thesis Award from Liaoning Province, China

Publication Top Notes:

Title: Model-Based 3D Gaze Estimation Using a TOF Camera

  • Journal: Sensors

 

 

Mrs. Marcia Baptista | Machine Learning and Prognostics | Best Researcher Award

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Mrs. Marcia Baptista | Machine Learning and Prognostics | Best Researcher Award

Mrs. Marcia Baptista, Delft University of Technology

Mrs. Marcia Baptista, currently an Assistant Professor at TU Delft and soon joining NOVA IMS, completed her Ph.D. in Engineering Design and Advanced Manufacturing at MIT Portugal Program πŸ“š. Her research in machine learning and deep learning for prognostics in aeronautics, conducted in collaboration with Rolls Royce and Embraer, has led to significant advancements in predictive maintenance technology πŸ”¬. Marcia’s career spans leadership roles at NASA Ames Research Center and Instituto TecnolΓ³gico de AeronΓ‘utica, focusing on technical prognostics and system engineering across continents. Her contributions have earned her Best Paper awards at esteemed conferences and recognition for teaching excellence πŸ†. Beyond academia, Marcia chairs international conference sessions, serves editorial roles, and contributes to advanced engineering literature 🌐.

🌐 Professional Profile:

Orcid

Scopus

πŸ“š Education & Academic Path

I completed my Ph.D. in Engineering Design and Advanced Manufacturing at MIT Portugal Program, focusing on machine learning and deep learning for prognostics in aeronautics. This research involved collaborations with Rolls Royce and Embraer, resulting in significant advancements in predictive maintenance technology.

πŸ”¬ Research & Professional Experience

Currently serving as an Assistant Professor at TU Delft and starting soon at NOVA IMS, I’ve been actively involved in teaching, research, and leadership roles. My work spans multiple continents, including positions at NASA Ames Research Center and Instituto TecnolΓ³gico de AeronΓ‘utica, where I contributed to cutting-edge projects in technical prognostics and system engineering.

πŸ† Achievements & Recognition

Throughout my career, I’ve been honored with numerous awards, including Best Paper accolades at prestigious conferences like WCE 2019 and ISM 2019. I’ve also received recognition for my teaching contributions and was awarded a Doctorate Scholarship from the Foundation for Sciences and Technology in Portugal.

🌐 Contributions & Outreach

Beyond academia, I’ve chaired sessions at international conferences and served as a web chair for the Intelligent Transport Systems Conference. My editorial roles include being a special issue editor for prominent journals and authoring chapters on advanced engineering topics.

Publication Top Notes:

  • Aircraft Engine Bleed Valve Prognostics Using Multiclass Gated Recurrent Unit
    • Year: 2023
    • Citations: 2
  • 1D-DGAN-PHM: A 1-D denoising GAN for Prognostics and Health Management with an application to turbofan
    • Year: 2022
    • Citations: 4
  • Relation between prognostics predictor evaluation metrics and local interpretability SHAP values
    • Year: 2022
    • Citations: 57
  • A self-organizing map and a normalizing multi-layer perceptron approach to baselining in prognostics under dynamic regimes
    • Year: 2021
    • Citations: 14
  • Classification prognostics approaches in aviation
    • Year: 2021
    • Citations: 15

 

 

Dr. Zhihe Lu | Transfer Learning | Best Researcher Award

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Dr. Zhihe Lu | Transfer Learning | Best Researcher Award

Dr. Zhihe Lu, National University of Singapore, Singapore

πŸ‘¨β€πŸ’Ό Zhihe Lu is a dedicated researcher in the field of Computer Vision, with a focus on Transfer Learning, Few-shot Learning, and Continual Learning. He holds a Doctoral Degree in Computer Vision from CVSSP, University of Surrey, UK, where he conducted innovative research under the supervision of Prof. Tao Xiang. Prior to that, he completed his Master’s Degree in Computer Vision at the Institute of Automation, Chinese Academy of Sciences, and obtained a Bachelor of Engineering in Automation from Zhengzhou University. Currently, Zhihe serves as a Research Fellow at the National University of Singapore, contributing to the CARTIN project for scene understanding. His previous experience includes an internship at the AI center of Samsung, UK. Zhihe’s passion for advancing computer vision technologies drives his commitment to exploring novel approaches in the field. πŸ–₯️

Professional Profile:

Google Scholar

πŸ“š Education:

  • Doctoral Degree in Computer Vision from CVSSP, University of Surrey, UK (2019.07 – 2022.09) under the supervision of Prof. Tao Xiang.
  • Master’s Degree in Computer Vision from Institute of Automation, Chinese Academy of Sciences (2016.09 – 2019.06) under the supervision of Prof. Ran He.
  • Bachelor of Engineering in Automation from College of Electrical Engineering, Zhengzhou University (2010.09 – 2014.06).

πŸ’Ό Working Experiences:

  • Research Fellow at National University of Singapore, Singapore (2022.09 – Present), working on part of the CARTIN project for scene understanding.
  • Intern at AI center of Samsung, UK (2021.10 – 2022.04).

πŸ” Research Interests:

Zhihe Lu’s research interests lie in the areas of Computer Vision, Transfer Learning, Few-shot Learning, and Continual Learning.

Publication Top Notes:

 

 

 

 

 

 

Dr. Ali Rohan | Artificial Intelligence Awards | Best Researcher Award

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Dr. Ali Rohan | Artificial Intelligence Awards | Best Researcher Award

Dr. Ali Rohan, National Subsea Centre, United Kingdom

πŸ‘¨β€πŸ”¬ Dr. Ali Rohan is a versatile researcher and educator in the fields of robotics, artificial intelligence (AI), and computer vision. With a strong academic background including a MSc – PhD in Electrical, Electronics & Control Engineering from Kunsan National University, South Korea, he has delved into various facets of cutting-edge technology. As a Lead Researcher at institutions like the National Subsea Centre in the UK and Dongguk University in South Korea, he spearheaded groundbreaking projects like SeaSense, focusing on underwater visual systems, and DAIRYVISION, revolutionizing livestock farming with AI and machine vision. His expertise spans from real-time implementation of AI for UAVs to structural damage monitoring using AI with UAVs. Dr. Rohan’s contributions extend beyond research, as he has also shared his knowledge as an educator, teaching courses on robotics, data science, and control systems engineering. With a passion for innovation and a dedication to advancing technology, Dr. Rohan continues to make significant strides in shaping the future of AI and robotics. πŸ€–βœ¨

🌐 Professional Profile:

Scopus

Linkedin

Orcid

Google Scholar

πŸŽ“ Education

Ph.D. in Electrical, Electronics & Control Engineering
Department of Control & Robotics Engineering, Kunsan National University, Kunsan, South Korea
(Feb 2016 – Mar 2020)

B.Sc (Hons) in Electrical Engineering
School of Electrical Engineering, The University of Faisalabad, Pakistan
(Oct 2008 – Jul 2012)

πŸ–₯️ Technical Competence

  • Areas of Specialization: AI, Machine Learning, Deep Learning, Computer Vision, Robotics, Automation
  • Programming Languages: C, C++, C#, Matlab, Python
  • AI & Machine Learning Libraries: TensorFlow, PyTorch, Scikit-learn, Keras
  • Operating Systems: Windows, Linux, macOS, Robot Operating System (ROS)

πŸ” Research Interests :

πŸ€– Dr. Ali Rohan, an accomplished researcher, specializes in Robotics, Artificial Intelligence (AI), Computer Vision, Automation and Control, Image Processing, Signal Processing, and Machine Learning. His expertise lies in leveraging these domains to innovate solutions for various real-world challenges, from enhancing industrial automation to advancing medical diagnostics. With a keen interest in interdisciplinary research, Ali consistently explores the intersection of these fields to develop cutting-edge technologies with profound societal impacts. πŸš€

πŸ”¬ Research Experience & Projects

Dr. Rohan has led and contributed to various research projects in areas such as underwater robotics, agricultural monitoring using drones, AI for healthcare, and structural damage detection using UAVs. His work includes projects funded by prestigious bodies like the Net Zero Technology Centre, InnovateUK, and the Australian Research Council.

πŸ‘¨β€πŸ« Teaching Experience

Dr. Rohan has taught a range of modules covering topics such as fundamentals of prognostics and health management, robotics, control systems engineering, data science, and power electronics. His teaching expertise spans both theoretical principles and practical applications in engineering and technology.

πŸ… Certifications & Awards

Dr. Rohan holds certifications in areas such as Prognostics and Health Management and has received recognition for his contributions to research and academia.

πŸ“šΒ Publication Impact and Citations :

Scopus Metrics:

  • πŸ“Β Publications: 19 documents indexed in Scopus.
  • πŸ“ŠΒ Citations: A total of 437 citations for his publications, reflecting the widespread impact and recognition of Dr. Ali Rohan’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 644 πŸ“–
    • h-index: 14Β  πŸ“Š
    • i10-index: 15 πŸ”
  • Since 2018:
    • Citations: 629 πŸ“–
    • h-index: 14 πŸ“Š
    • i10-index: 14 πŸ”

πŸ‘¨β€πŸ« A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. πŸŒπŸ”¬

Publication Top Notes: