Prof. Dr Chih-Yung Tsai | Machine learning | Best Researcher Award |

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Prof. Dr Chih-Yung Tsai | Machine learning | Best Researcher Award

Professor, at University of Taipei, Taiwan.

Prof. Dr. Chih-Yung Tsai is a distinguished academic and researcher specializing in electrical engineering and nanotechnology. He is currently a professor at the Department of Electrical Engineering, National Taiwan University (NTU). Dr. Tsai’s work has significantly advanced the fields of nanolithography, integrated circuit design, and advanced manufacturing processes

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🎓 Education 

Dr. Tsai earned his Bachelor of Science and Master of Science degrees from National Taiwan University. He then pursued his Ph.D. in Aeronautics and Astronautics, with a minor in Electrical Engineering, at Stanford University, completing it in 2002.

💼 Experience 

From 2002 to 2005, Dr. Tsai served as a Senior Process Engineer in lithography at Intel Corporation. During this time, he worked on performance monitoring and improvement of 193-nm microlithography scanners for Intel’s 90-nm process technology. In 2005, he joined the faculty of NTU’s Department of Electrical Engineering, where he established and directed several research laboratories, including the Nanoscale Design and Fabrication Systems Lab (NDFSL), Particle Beam Precision Patterning and Imaging Lab (PBPPIL), and High-Performance Servo Systems Lab (HPSSL).

🔬 Research Interests 

Dr. Tsai’s research centers on the design and application of advanced control, simulation, signal processing, optimization, and machine learning techniques to solve nanolithography and nanotechnology-related problems. His current focus includes the design and fabrication techniques of exploratory nanoscale integrated circuits at the IRDS 10 nm half-pitch node and beyond. He is also involved in aerospace-related research activities and has conducted research on control system design automation, automotive and aerospace electronics, consumer electronics, and biomedical equipment design.

🏆 Awards 

Dr. Tsai has been recognized for his contributions to the field with several honors. He has been invited by The Japan Society of Applied Physics to serve as Program Committee Section Sub Head in International Microprocesses and Nanotechnology since 2007. He has also been invited to present on innovative applications of helium ion beam nanofabrication and techniques for EUV mask defect detection technology research and development at various international workshops and seminars.

📚 Top Noted Publications 

Title: Applying the theory of planned behavior to explore the independent travelers’ behavior
Author(s): CY Tsai
Citations: 109
Index: African Journal of Business Management 4 (2), 221
Year of Publication: 2010

Title: Using the technology acceptance model to analyze ease of use of a mobile communication system
Author(s): CY Tsai, CC Wang, MT Lu
Citations: 79
Index: Social Behavior and Personality: an international journal 39 (1), 65-69
Year of Publication: 2011

Title: The impact of tour guides’ physical attractiveness, sense of humor, and seniority on guide attention and efficiency
Author(s): CY Tsai, MT Wang, HT Tseng
Citations: 55
Index: Journal of Travel & Tourism Marketing 33 (6), 824-836
Year of Publication: 2016

Title: An analysis of usage intentions for mobile travel guide systems
Author(s): CY Tsai
Citations: 48
Index: African Journal of Business Management 4 (14), 2962
Year of Publication: 2010

Title: Learning under time pressure: Learners who think positively achieve superior learning outcomes from creative teaching methods using picture books
Author(s): CY Tsai, YH Chang, CL Lo
Citations: 39
Index: Thinking Skills and Creativity 27, 55-63
Year of Publication: 2018

Conclusion

Prof. Dr. Chih-Yung Tsai’s illustrious career in electrical engineering and nanotechnology has significantly advanced the understanding and application of nanolithography and integrated circuit design. His dedication to research, education, and innovation continues to inspire and shape the future of technology.

Ms Lara Pörtner | Data Management | Best Researcher Award |

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Ms. Lara Pörtner | Data Management | Best Researcher Award | 

PhD Student , at Université Grenoble Alpes, Germany.

Lara Pörtner is a researcher and industry expert specializing in digital strategy, data analytics, and industrial engineering. With a strong academic foundation and professional experience in master data governance, she bridges the gap between research and real-world applications. Fluent in multiple languages, she has worked on international projects in data strategy, innovation management, and digital transformation.

Professional Profile

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Education 🎓

Lara is currently pursuing a PhD in Digital Strategy at Université Grenoble Alpes, France (2022–2025), where she focuses on developing customer-specific reference models for optimizing data strategies using maturity analysis methods. She holds a double master’s degree (M.Sc. Industrial Engineering and Management) from Karlsruhe Institute of Technology (KIT), Germany, and Institute National Polytechnique Grenoble (G-INP), France, with a specialization in innovation management, digitalization, and automotive engineering. Her academic journey began with a B.Sc. in Industrial Engineering and Management from KIT (2016–2020), where she built expertise in supply chain management, strategy, and organization.

Professional Experience đź’Ľ

Lara has held multiple roles in leading organizations across data & analytics, digital transformation, and strategy consulting. She started her career as an intern and working student in Master Data Management at cbs Corporate Business Solutions (2020–2021), where she supported SAP MDG system implementations. She later joined CAMELOT Management Consultants AG (2022–2024) as a Senior Consultant, contributing to SAP MDG BP implementation, process design, user training, and data strategy assessments. Currently, she is a Senior Associate in Data & Analytics at PricewaterhouseCoopers (PwC), Munich (2025–present), focusing on enterprise-wide digital strategy initiatives. Her industry experience is complemented by her early research work as a Student Assistant at wbk Institute of Production Tech., Karlsruhe Institute of Technology (2020), and an internship in Strategy & Innovation Management at Lufthansa Cargo AG (2018).

Research Interests 🌍

Her research primarily revolves around digital strategy, data analytics, and master data governance. She works on designing advanced methodologies for data maturity assessment, enabling organizations to optimize data-driven decision-making. Her work integrates elements of machine learning, enterprise data management, and business process optimization, contributing to the evolution of digital transformation frameworks.

Awards & Honors 🏆

Lara has received several prestigious recognitions, including the DLR Graduate Program (2022–2024), demonstrating her involvement in high-impact research. She was selected for the Accenture Female Talent Program (2021), highlighting her leadership potential in the tech and consulting space. Early in her academic career, she secured 2nd place in the Jugend Forscht competition (2016), showcasing her research abilities. She also holds professional certifications such as SCRUM Master, SAFe 6 Agilist, and LEAN Basic Certificate.

Top Noted Publications đź“š

Title: Data Literacy Assessment – Measuring Data Literacy Competencies to Leverage Data-Driven Organizations
Authors: Lara Pörtner, Andreas Riel, Vivian Klaassen, Dilara Sezgin, Ysaline Kievits
Citations: 0

Conclusion

Lara Pörtner has an impressive profile with a strong academic foundation, industry research experience, and technical expertise in data strategy and analytics. If the award prioritizes applied research, digital strategy, and industry impact, she is a strong candidate. However, if the focus is on academic publications and fundamental research contributions, she may need to enhance her research output to improve her chances.

Assist. Prof. Dr Saeid Afshari | Artificial intelligence | Best Researcher Award |

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Assist. Prof. Dr Saeid Afshari | Artificial intelligence | Best Researcher Award | 

Faculty , at University of Isfahan , Iran.

Dr. Saeid Afshari is an Assistant Professor of Computer Engineering at the University of Isfahan, Iran. With extensive expertise in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning, and Human-Computer Interaction (HCI), he has significantly contributed to both academia and industry. His research spans AI-driven solutions for healthcare, security, organizational management, and multimedia applications. An experienced IT project manager, he has successfully led the development of various smart software systems, AI-based analytics platforms, and e-Government services. Dr. Afshari is also a dedicated educator, mentoring numerous students in AI, data science, and software engineering.

Professional Profile

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Education 🎓

Ph.D. in Computer Engineering – Artificial Intelligence (2015) | University of Isfahan, Iran

Thesis: Online Quality of Experience Assessment System for Interactive Applications in Computer Networks

M.Sc. in Computer Engineering – Artificial Intelligence (2005) | University of Isfahan, Iran

Thesis: Using Agents in Workflow Management System of Distributed Organizations

B.Sc. in Hardware Engineering (2000) | University of Isfahan, Iran

Professional Experience đź’Ľ

Dr. Afshari has extensive experience in managing and developing AI-powered IT projects. He has led multiple organizational management software, AI-based sports and athlete management platforms, and e-Government solutions. As an educator, he has taught a range of subjects, including AI, data science, statistical pattern recognition, and programming in Python, C++, and MATLAB. His supervision of numerous master’s theses on AI applications highlights his mentorship and contribution to academic research.

Research Interests 🌍

Dr. Afshari’s research explores AI-driven problem-solving, deep learning applications, and human-computer interaction. His work includes machine learning-based image processing for medical diagnostics (cancer detection, skin tissue analysis), AI-powered workflow automation, smart organizational management, and multimedia quality assessment. He has also worked on neural network-based human activity recognition, deep learning models for license plate recognition, and machine translation systems. His interdisciplinary approach integrates AI with healthcare, business management, and security applications.

Awards & Honors 🏆

Recognized for significant contributions in AI-driven software development and project leadership

Successfully implemented over 150 AI-based software applications in academia and industry

Leading researcher in QoE (Quality of Experience) assessment for interactive applications

Top Noted Publications đź“š

Load Balancing of Servers in Software-Defined Internet of Multimedia Things Using the Long Short-Term Memory Prediction Algorithm

Authors: S. Imanpour, A. Montazerolghaem, S. Afshari

Conference: 10th International Conference on Web Research (ICWR)

Citations: 7

Year: 2024

QoE Assessment of Interactive Applications in Computer Networks

Authors: S. Afshari, N. Movahhedinia

Journal: Multimedia Tools and Applications, Volume 75, Pages 903-918

Citations: 7

Year: 2016

Non-Intrusive Online Quality of Experience Assessment for Voice Communications

Authors: S. Afshari, N. Movahhedinia

Journal: Wireless Personal Communications, Volume 79, Pages 2155-2170

Citations: 3

Year: 2014

Optimizing Server Load Distribution in Multimedia IoT Environments Through LSTM-Based Predictive Algorithms

Authors: A. R. Montazerolghaem, S. Imanpour, S. Afshari

Journal: International Journal of Web Research

Year: 2025

Projecting Road Traffic Fatalities in Australia: Insights for Targeted Safety Interventions

Authors: A. Soltani, S. Afshari, M. A. Amiri

Journal: Injury

Year: 2025

Conclusion

Dr. Saeid Afshari is a strong candidate for the Best Researcher Award, particularly for his contributions to AI, machine learning, and deep learning applications. To further enhance his competitiveness, he could focus on increasing high-impact publications, international collaborations, patents, and research funding. If the award prioritizes real-world AI applications, software development, and mentorship, he would be an excellent nominee.

Dr Han Gao | Artificial Intellegence | Best Researcher Award |

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Dr. Han Gao | Artificial Intellegence | Best Researcher Award

postdoctoral fellow, at Harvard University, United States.

Dr. Han Gao is a dedicated researcher specializing in scientific deep learning, computational mechanics, and generative models for spatiotemporal physics. With a strong background in machine learning-driven physics simulations, he has contributed significantly to advancing numerical modeling and data-driven solutions for complex physical systems. His work bridges the gap between deep learning and traditional computational fluid dynamics, with applications in turbulence modeling, inverse problems, and reduced-order modeling.

Professional Profile

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Education 🎓

Dr. Gao earned his Ph.D. in Aerospace and Mechanical Engineering from the University of Notre Dame (2018–2023), where he focused on scientific deep learning for forward and inverse modeling of spatiotemporal physics. He also holds a Master’s degree in Mechanical Engineering & Materials Science from Washington University in St. Louis (2016–2018), with research on numerical simulations of jet impingement and rotor blade effects. His academic journey began with a Bachelor’s degree in Mechanical Engineering from Shanghai University of Electric Power (2012–2016).

Professional Experience đź’Ľ

Dr. Gao is currently a Postdoctoral & Teaching Fellow at Harvard University (2023–present), where he continues his research in deep learning-driven physics simulations while mentoring students. Previously, he served as a Research & Teaching Assistant at the University of Notre Dame (2018–2023) and Washington University in St. Louis (2016–2018). Additionally, he gained industry experience as a Research Intern at Google Research (2022), where he worked on advanced AI-driven physics simulations.

Research Interests 🌍

Dr. Gao’s research revolves around the integration of deep learning techniques with physics-based modeling, particularly in solving partial differential equations (PDEs), turbulence modeling, generative models, and reduced-order modeling. He has developed novel physics-informed neural networks (PINNs), Bayesian generative models, and machine-learning frameworks for high-dimensional complex systems. His work is widely applicable in computational fluid dynamics (CFD), climate modeling, aerodynamics, and engineering simulations.

Awards & Honors 🏆

Dr. Gao has been recognized for his outstanding contributions to computational mechanics and machine learning applications in physics. His publications in top-tier journals, including Nature Communications, and prestigious machine learning conferences such as NeurIPS, ICML, and ICLR, reflect his impact in the field. He has also received competitive research opportunities, including a Google Research internship, showcasing his industry relevance.

Top Noted Publications đź“š

Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data
L. Sun, H. Gao, S. Pan, J.-X. Wang – 916 citations – Computer Methods in Applied Mechanics and Engineering, 2020

PhyGeoNet: Physics-informed geometry-adaptive convolutional neural networks for solving parameterized steady-state PDEs on irregular domain
H. Gao, L. Sun, J.-X. Wang – 567 citations – Journal of Computational Physics, 2021

Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems
H. Gao, M. J. Zahr, J.-X. Wang – 240 citations – Computer Methods in Applied Mechanics and Engineering, 2022

Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels
H. Gao, L. Sun, J.-X. Wang – 214 citations – Physics of Fluids, 2021

Predicting physics in mesh-reduced space with temporal attention
X. Han, H. Gao, T. Pfaff, J.-X. Wang, L.-P. Liu – 106 citations – ICLR, 2022

Conclusion

Dr. Han Gao is a highly promising researcher with a strong publication record, interdisciplinary expertise, and experience at prestigious institutions. His contributions to scientific deep learning and computational mechanics make him a strong contender for the Best Researcher Award. To further solidify his case, he could focus on gaining more individual recognitions, expanding his leadership roles, and demonstrating the real-world impact of his research.