Mr. André Guimarães | Computer Science | Best Researcher Award

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Mr. André Guimarães | Computer Science | Best Researcher Award

Researcher, University of Beira Interior, Portugal

Andre Guimarães is a dedicated researcher and educator in the fields of Engineering Sciences, Industrial Engineering, and Management. With a strong academic background, he has contributed significantly to various research projects related to Industry 4.0 and digital transformation. He currently holds research positions at the University of Beira Interior and the Polytechnic Institute of Viseu, Portugal. Alongside his academic work, Andre has accumulated practical experience in industrial environments, particularly in production management and technical consulting, where he focuses on quality management, lean methodologies, and engineering innovations. He is also a passionate educator, teaching engineering and management-related courses at the higher education level. 📚🔬

Publication Profile

ORCID

Education:

Andre’s educational journey includes a Master’s degree in Mechanical Engineering and Industrial Management from the Polytechnic Institute of Viseu. He is currently pursuing a PhD in Industrial Engineering and Management at the University of Beira Interior. Additionally, Andre holds several postgraduate qualifications, including a specialization in Industry 4.0 and Digital Transformation from the Polytechnic Institute of Porto. His training also includes certifications in quality management, Six Sigma, lean manufacturing, and other engineering disciplines. 🎓📖

Experience:

Andre’s professional career spans both academia and industry. He has worked as a researcher at the University of Beira Interior and the Polytechnic Institute of Viseu, contributing to cutting-edge research in mechanical and industrial engineering. Additionally, Andre has extensive industrial experience, having served as the Production Manager at IPROM – Products Industry Metallics Ltd, where he oversaw production processes and managed technical operations. As a consultant and facilitator at the Welding and Quality Institute, Andre applies his expertise in quality management systems and continuous improvement. 🏭⚙️

Awards and Honors:

Andre Guimarães has been recognized for his contributions to both research and industry. He is a full member of the Order of Engineers in Portugal and a fellow at FCT Research. His work has been acknowledged through various academic and industry accolades, cementing his reputation as a skilled professional and educator in his field. 🏅🌟

Research Focus:

Andre’s research interests are deeply rooted in Industry 4.0 technologies, digital transformation, lean management, and quality systems in industrial engineering. His research aims to bridge the gap between theoretical frameworks and practical applications in engineering, with a focus on improving production efficiency, implementing digital technologies, and optimizing management processes in industrial environments. His recent projects explore advanced methodologies in electromechatronics and systems research. 🔍📊

Conclusion:

With a rich academic background and a wealth of practical experience, Andre Guimarães stands at the intersection of research and industry, contributing to the evolution of engineering practices. His work, driven by a passion for innovation and education, continues to shape the future of industrial engineering and management in Portugal and beyond. Andre’s ongoing commitment to advancing the field through both research and practical applications makes him a valuable asset to the academic and industrial communities. 🚀🌍

Publications:

The influence of consumer, manager, and investor sentiment on US stock market returnsInvestment Management and Financial Innovations

Effects of Lean Tools and Industry 4.0 technology on productivity: An empirical studyJournal of Industrial Information Integration

Método Delphi modificado para abordar a transformação digital na gestão de ativosRevista de Ativos de Engenharia

Lean philosophy and Value Engineering methodologies. Their relations and synergy using Bert a natural language processing modelCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Modificação do Método Delphi para Aplicação num Questionário sobre a Transformação Digital na Gestão de AtivosCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Overview of the use of data assets in the context of Portuguese companies: Comparison between SMEs and large companiesCongrEGA 2024 – Sustainable and Digital Innovation in Engineering Asset Management

Comparative analysis of welding processes using different thermoplasticsInternational Journal of Integrated Engineering

Mr. Ahmad Faraz Hussain | Machine learning | Best Scholar Award

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Mr. Ahmad Faraz Hussain | Machine learning | Best Scholar Award

PhD student, Zhejiang university, China

Ahmad Faraz Hussain is an accomplished researcher and engineer specializing in audio signal processing, speaker recognition, and wireless sensor networks. With a strong academic background and extensive technical experience, he has contributed significantly to the field of electronics and information engineering. His work spans research, teaching, and industry, reflecting his passion for innovation and education.

Publication Profile

Scopus

🎓 Education:

Ahmad Faraz Hussain earned his Master of Science in Electronics & Information Engineering from the South China University of Technology, China (2017–2019), achieving an impressive 90%. His thesis focused on “Speaker Recognition with Emotional Speech,” showcasing his expertise in audio processing. He completed his Bachelor of Science in Electrical Engineering from the University of Engineering and Technology, Peshawar, Pakistan (2009–2014), with a thesis on “ZigBee-Based Wireless Sensor Network for Building Safety Monitoring.”

💼 Professional Experience:

Ahmad has a diverse professional journey, beginning as a Research Assistant at the South China University of Technology (2017–2019), where he worked on cutting-edge projects in speech recognition. Before that, he served as a Lecturer at Polytechnical College Kohat (2016–2017), imparting knowledge to aspiring engineers. His technical expertise was further honed during his two-year tenure as a Technical Engineer at PTCL, Pakistan, where he worked on telecommunications and networking solutions.

🏆 Awards and Honors:

Ahmad was a recipient of the prestigious CSC Scholarship, which enabled him to pursue his master’s degree in China. His academic excellence and dedication to research have earned him recognition in both academic and professional circles.

🔬 Research Focus:

Ahmad’s research interests lie in audio signal processing, speaker recognition, speech recognition, and wireless sensor networks. His work focuses on developing advanced methodologies for improving speech-based systems and enhancing security through smart sensor networks. His contributions to these fields are evident in his multiple publications and research projects.

🔚 Conclusion:

Ahmad Faraz Hussain is a dedicated researcher and engineer with a strong foundation in speech and wireless sensor technologies. His academic achievements, professional experience, and research contributions highlight his commitment to innovation and education. With a passion for higher learning and community service, he continues to make impactful contributions to the field of electronics and information engineering. 🚀

📚 Publications:

Three-Dimensional Dynamic Positioning Using a Novel Lyapunov-Based Model Predictive Control for Small Autonomous Surface/Underwater Vehicles

Fish Detection and Classification Based on Improved ViT

ZigBee-Based Wireless Sensor Network for Building Safety Monitoring – Published in the Journal of TWASP. Read here.

Speaker Recognition with Emotional Speech – Published in GSJ. Read here.

Speech Emotion Recognition – Under review.

ZigBee and GSM-Based Security System for Business Places– Accepted for publication.

Internet of Things-Based Information System for Smart Wireless Sensor Healthcare Applications – Submitted for review.

Huan Zhao | Machine Learning | Best Researcher Award

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Assoc. Prof. Dr . Huan Zhao | Machine Learning | Best Researcher Award

Associate Professor, School of Aeronautics, Northwestern Polytechnical University, China

Huan Zhao is an associate professor at the School of Aeronautics, Northwestern Polytechnical University (NPU), China. He specializes in aerodynamics, multidisciplinary design optimization, uncertainty quantification, and machine learning, focusing on CFD simulation, AI-based global optimization, and surrogate modeling. He is also the executive deputy director of the Institute of Digital Intelligence for Flight Mechanics and Aerodynamic Design (IDIFMAD). Zhao has made significant contributions to the fields of aerodynamic shape optimization, high-dimensional global optimization, and uncertainty-based robust design. He holds several patents and has authored many high-impact publications. 🌐✈️

Publication Profile

Education

Huan Zhao completed his Ph.D. in Fluid Dynamics at Northwestern Polytechnical University (NPU) in 2020, following a B.Eng. in Aircraft Design and Engineering from the same university in 2014. 📚🎓

Experience

Zhao served as a tenure-track assistant professor at Sun Yat-sen University (SYSU) before joining NPU as a tenure-track associate professor in 2023. He has directed and participated in numerous research projects focusing on aerodynamic design optimization, high-speed rotor airfoil design, and surrogate-assisted design techniques. He is a principal investigator (PI) for multiple projects funded by the National Natural Science Foundation of China (NSFC). 👨‍🏫🔬

Awards and Honors

Huan Zhao has received several awards and honors, including recognition as part of the “Hundred Talents Plan” Young Academic Backbone at SYSU and multiple patents for his innovative contributions to aerodynamic design. 🏆🎖️

Research Focus

Zhao’s research interests lie in aerodynamics, including multi-fidelity polynomial chaos-Kriging models, aerodynamic shape optimization, and uncertainty quantification. His work has contributed significantly to the design and optimization of high-lift airfoils, laminar flow airfoils, and robust design methods under uncertainty. His expertise also includes machine learning, AI-based global optimization, and the application of surrogate models in complex design scenarios. 🔍🧑‍💻

Conclusion

Huan Zhao’s innovative work has had a profound impact on the field of aerodynamics and optimization. His research has not only advanced the understanding of aerodynamic design but has also led to practical improvements in the development of high-performance aircraft and related technologies. He continues to drive forward cutting-edge research in aerodynamics and multidisciplinary design optimization. 🚀🌍

Publications

An efficient adaptive forward–backward selection method for sparse polynomial chaos expansion, Computer Methods in Applied Mechanics and Engineering, 2019.

Review of robust aerodynamic design optimization for air vehicles, Archives of Computational Methods in Engineering, 2019.

Effective robust design of high lift NLF airfoil under multi-parameter uncertainty, Aerospace Science and Technology, 2017.

Adaptive multi-fidelity sparse polynomial chaos-Kriging metamodeling for global approximation of aerodynamic data, Structural and Multidisciplinary Optimization, 2021.

Uncertainty-based design optimization of NLF airfoil for high altitude long endurance unmanned air vehicles, Engineering Computations, 2019.

 Efficient aerodynamic analysis and optimization under uncertainty using multi-fidelity polynomial chaos-Kriging surrogate model, Computers & Fluids, 2022.

Research on efficient robust aerodynamic design optimization method of high-speed and high-lift NLF airfoil, Acta Aeronautica et Astronautica Sinica, 2021.

Research on Novel High-Dimensional Surrogate Model-Based Aerodynamic Shape Design Optimization, Acta Aeronautica et Astronautica Sinica, 2022.

Research on novel multi-fidelity surrogate model assisted many-objective global optimization method, Acta Aeronautica et Astronautica Sinica, 2022.

Adaptive multi-fidelity polynomial chaos-Kriging model-based efficient aerodynamic design optimization method, Chinese Journal of Theoretical and Applied Mechanics, 2023.

 

Hsiu Hsia Lin | Machine learning | Best Researcher Award

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Prof. Hsiu Hsia Lin | Machine learning | Best Researcher Award

Research Fellow, Chang Gung Memorial Hospital, Taiwan

Dr. Hsiu-Hsia Lin is a dedicated Research Fellow at the Craniofacial Research Center, Chang Gung Memorial Hospital, Taiwan, and an Adjunct Assistant Professor at the Graduate Institute of Dental and Craniofacial Science, Chang Gung University. With a strong foundation in AI and 3D craniofacial image processing, her research contributes significantly to advancements in orthognathic surgery. Dr. Lin’s expertise in surgical navigation and CAD/CAM-assisted surgery is pivotal in improving craniofacial surgical outcomes. 🌟

Publication Profile

Education:

Dr. Lin earned her Ph.D. in Computer Science and Engineering from National Chung Hsing University, Taiwan, following a Master’s in Computer Science from Tunghai University. Her academic journey is deeply rooted in computer science, blending AI with craniofacial research. 🎓📚

Experience:

Dr. Lin has held key research positions, including Assistant Research Fellow and Postdoctoral Fellow at the Craniofacial Research Center, Chang Gung Memorial Hospital. Her postdoctoral work also extended to the Department of Computer Science and Engineering at National Chung Hsing University. Her extensive experience has helped bridge the gap between AI technology and clinical applications. 💼🔬

Research Focus:

Dr. Lin’s research revolves around Pattern Recognition, Artificial Intelligence, and 3D Craniofacial Image Processing. She specializes in computer-aided surgical simulation for orthognathic surgery, surgical navigation, and CAD/CAM-assisted procedures, aiming to optimize outcomes in facial surgery. 🧠💻

Awards and Honors:

Dr. Lin has received multiple recognitions for her contributions to craniofacial research and AI in surgery. Her work continues to shape modern surgical approaches, particularly in orthognathic surgery, enhancing patient outcomes. 🏆👏

Publication Top Notes:

Dr. Lin’s publications focus on integrating AI with medical applications, particularly in 3D craniofacial analysis and orthognathic surgery. Her studies offer novel methods for surgical planning, facial attractiveness assessment, and facial symmetry evaluation.

Quantification of facial symmetry in orthognathic surgery (Dec. 2024) in Comput Biol Med., cited by 5 articles. DOI

Average 3D virtual sk

eletofacial model for surgery planning (Feb. 2024) in Plast Reconstr Surg., cited by 3 articles. DOI

Facial attractiveness assessment using transfer learning (Jan. 2024) in Pattern Recognit., cited by 4 articles. DOI

Optimizing Orthognathic Surgery (Nov. 2023) in J. Clin. Med., cited by 6 articles. DOI

Single-Splint, 2-Jaw Orthognathic Surgery (Nov. 2023) in J Craniofac Surg., cited by 2 articles. DOI

Applications of 3D imaging in craniomaxillofacial surgery (Aug. 2023) in Biomed J., cited by 7 articles. DOI

Facial Beauty Assessment using Attention Mechanism (Mar. 2023) in Diagnostics, cited by 8 articles. DOI

 

Avirup Roy | Machine Learning |Machine Learning Research Award

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Mr. Avirup Roy | Machine Learning |Machine Learning Research Award

PhD Student, Michigan State University, United States

Dr. Avirup Roy is a dedicated researcher and engineer specializing in networked embedded and wireless systems. Currently pursuing his PhD at Michigan State University, his work focuses on developing self-learning mechanisms for embedded hardware systems with limited computational resources. With a solid foundation in electronics and communication engineering, Avirup has gained extensive experience in both academia and industry, contributing to projects ranging from smart malaria detection to automated power management systems. His technical skills span machine learning, embedded systems, cloud computing, and web development. Beyond his professional life, Avirup is passionate about Indian classical music, photography, and swimming. 🌟📚🎵📷🏊‍♂️

Profile

ORCID

 

Education🎓

Michigan State University, East Lansing, MI, US PhD in Electrical and Computer Engineering (2020-Present). Dissertation: Self-learning mechanisms for Embedded hardware systems with limited computational resources. GPA: 3.75/4Maulana Abul Kalam Azad University of Technology, Kolkata, WB, India Bachelor of Technology (BTech) in Electronics and Communication Engineering (2013-2017)

Experience💼

Graduate Research Assistant, Michigan State University (Sep 2020 – Jul 2023),Developed an android and website application for smart malaria detection involving cloud database integration. Graduate Teaching Assistant, Michigan State University (Aug 2023 – Present), Instructed and graded labs for Embedded Cyber-physical Systems, VLSI Systems, and Digital Control courses. ICER Cloud Computing Fellow, Michigan State University (Sep 2023 – Present), Implemented Azure cloud resources in semi-supervised federated learning for embedded devices. Programmer Analyst, Cognizant Technology Solutions (Dec 2017 – Jul 2020), Developer and support analyst for ASP.NET based applications of MetLife Inc. Intern, Calcutta Electric Supply Corporation (CESC) Limited (Jul 2016 – Aug 2016), Worked on automated power management systems using SCADA communication. Intern, Bharat Sanchar Nigam Limited (BSNL) (Jun 2015 – Aug 2015), Explored general trends in wireless communication. Undergraduate Researcher, Maulana Abul Kalam Azad University of Technology (2015-2016), Presented research at various international conferences and served as the vice-president of SPIE Student Chapter.

Research Interests🔍

Embedded Machine Learning: Focused on developing efficient learning algorithms for resource-constrained devices.
Networked Embedded Systems: Exploring self-learning mechanisms and their applications in real-world scenarios.
Cloud Computing: Leveraging cloud resources for semi-supervised federated learning.
VLSI Systems: In-depth study and teaching of Very-Large-Scale Integration systems.
Cyber-Physical Systems: Research on embedded systems interacting with physical processes.

Awards🏆

National Social Entrepreneurship Programme (2014): Secured 2nd position for the ‘Hand-Made Paper Industry’ project.
SPIE Smart Structures and Non-destructive Evaluation Conference (2016): Presented research in Las Vegas, Nevada.
EAPE Conference (2015): Presented research on emerging areas of photonics and electronics.
Graduate Fellowships: Awarded multiple fellowships during PhD for research and teaching excellence.

Publications

Semi-Supervised Learning Using Sparsely Labelled Sip Events for Online Hydration Tracking Systems
A. Roy, H. Dutta, A. K. Bhuyan, and S. K. Biswas, 2023, International Conference on Machine Learning and Applications (ICMLA).
Cited by: 3 articles.

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation
Roy, A., Dutta, H., Griffith, H., & Biswas, S., 2022, Sensors.
Cited by: 5 articles.