Mehrdad Esmaeilipour | AI-based Smart Devices | Sustainable Solutions Award

Mr. Mehrdad Esmaeilipour | AI-based Smart Devices | Sustainable Solutions Award

Engineer | Arya Plasma Gostar Pars | Iran

Mr. Mehrdad Esmaeilipour is an accomplished Electronics Engineer specializing in green technology, cold plasma systems, and sustainable electronic solutions. With extensive experience in air purification, wastewater treatment, and smart health devices, he has contributed significantly to advancing environmental sustainability and innovative assistive technologies. He is recognized for combining technical expertise, entrepreneurship, and academic scholarship, making impactful contributions to both industry and research.

Professional Profile

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Education

Mr. Esmaeilipour holds a Bachelor’s Degree in Electronics Engineering Technology from Islamic Azad University. He also completed an Associate Degree in Electronics from the same institution, following his early academic foundation in electronics at the technical high school level. His formal education provided a strong background in circuit design, power systems, and digital control methods, which later shaped his industrial and research achievements

Experience

Mr. Esmaeilipour currently serves as Senior Electronics Engineer at Arya Plasma Gostar Pars Company (Plasma Systems), where he leads projects in designing and implementing advanced plasma-based purification systems for water and air. He has been instrumental in developing patented wastewater treatment solutions and integrated intelligent systems applied in various industrial sectors.

In addition, he is the Founder and CEO of Parsa Pardazesh Bushehr Sanat (PPBS Co.), a company providing electronics and IT solutions while offering employment opportunities to young engineers and students. He has also contributed as a volunteer mentor at Islamic Azad University, guiding a robotics team in developing prototypes and advanced control systems.

Research Interests

His primary research interests include cold plasma applications in wastewater treatment, electronic system optimization, renewable energy technologies, robotics, and artificial intelligence integration in electronics. He has explored innovations in smart wearable devices for digital health, photovoltaic systems, and advanced controller designs. His work bridges practical industrial applications with academic research, ensuring both sustainability and technological advancement.

Honors

Mr. Esmaeilipour has been honored with multiple international research and innovation awards, including recognition for his contributions to technological devices, wearable sensing systems, and environmental sustainability. He has received distinctions such as the Global Leaders Award, Best Innovator Award, Tech Excellence Award, International Material Scientist Award, and Global Recognition Award™. His achievements have been covered in media interviews, highlighting him as both an inventor and entrepreneur.

Top Noted Publications

Design, Construction and Performance Comparison of Fuzzy Logic Controller and PID Controller for Two-Wheel Balance Robot (Smart Sensors)
Index: Scopus Indexed
Year: 2025

Global Innovation Technologist Awards – Excellence in Innovation Award (Biotechnology)
Index: International Award Recognition
Year: 2025

Global Leaders Awards – Enterprise Edition
Index: International Award Recognition
Year: 2025

Best Wearable Sensing Technology Award
Index: International Award Recognition
Year: 2025

Engineering Industry Impact Award
Index: International Award Recognition
Year: 2025

Conclusion

Mr. Mehrdad Esmaeilipour’s career reflects a unique balance of industry innovation, academic research, and social responsibility. His leadership in developing cold plasma systems, renewable energy strategies, and assistive smart devices underscores his impact on both sustainability and digital health. With a portfolio of patents, publications, and international recognitions, he continues to advance the field of electronics engineering. His future research potential, combined with his entrepreneurial vision and mentorship efforts, position him as a highly influential figure in engineering innovation and academic contributions.

Mr Yu Zhang | Artificial Intelligence | Best Researcher Award |

Mr. Yu Zhang | Artificial Intelligence | Best Researcher Award 

Engineer, at The Third Research Institute of the Ministry of Public Security, China.

Mr. Yu Zhang is a dynamic and promising young researcher specializing in computer technology, artificial intelligence, and the security of large language models (LLMs). With a strong academic background and a deep passion for innovation, he has demonstrated exceptional capabilities in both theoretical research and practical application. His work spans a variety of domains including machine learning, natural language processing, and intelligent systems, making him a valuable contributor to the next generation of computing research.

Professional Profile

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🎓 Education 

Mr. Zhang completed his Bachelor’s degree in Software Engineering from the School of Information Science and Engineering, Linyi University (2018–2022), graduating in the top 10% of his class with a GPA of 3.52/4. His coursework included data structures, operating systems, computer networks, and object-oriented programming.He is currently pursuing a Master’s degree in Computer Technology at the School of Intelligent Industry (School of Cybersecurity), Inner Mongolia University of Science and Technology (2022–2025), maintaining a GPA of 3.62/4. His graduate research includes machine learning, numerical analysis, natural language processing, and the ethical implications of AI.

💼 Experience

Mr. Zhang has participated in a variety of innovative projects and industry internships. He worked as a development engineer intern at Ambow Education Technology Group, where he focused on enterprise-grade applications using the Spring Boot framework, API design, database integration, and software testing. He also led and contributed to national-level innovation projects such as a WeChat Mini-Program competition platform and an Arduino-based smart aquaculture monitoring system. His recent work includes intelligent heating IoT systems and knowledge mining from police text data using BERT models.

🔬 Research Interests 

Mr. Zhang’s primary research interests lie in the development and security evaluation of large language models (LLMs). His projects involve toxic speech detection, prompt attack strategies, and benchmarking LLM safety. He has hands-on experience with advanced AI models such as GPT-4o, Claude-3-Opus, LLaMA-3, and others. His work explores cutting-edge areas like RAG (Retrieval-Augmented Generation), prompt tuning, and microfine training techniques, all aimed at enhancing the safety, ethics, and performance of generative AI.

🏆 Awards 

Mr. Zhang has received over 15 prestigious awards, including 6 national-level honors such as:

  • Third Prize, Central Committee Financial Challenge Final

  • Siemens Cup National Third Prize (Smart Manufacturing)

  • Second Prize, National College Computer Skills Competition

  • International Third Prize, American College Modeling Contest

  • Multiple provincial-level recognitions including First Prize in the National University Computer Competition and honors in math modeling events.
    He has also been awarded multiple academic scholarships for both undergraduate and graduate performance.

📚Top Noted  Publications 

Title: Security Assessment and Generation Improvement Strategies for Large Language Models
Authors: Yu Zhang, Yongbing Gao, Lidong Yang
Citations: [Not yet cited – early publication]
Index: Crossref
Year of Publication: 2025

Title: Chinese Generation and Security Index Evaluation Based on Large Language Model
Authors: Yu Zhang, Yongbing Gao, Wei Li, Zhi Su, Lidong Yang
Citations: Scopus EID: 2-s2.0-85204765727
Index: Scopus, IEEE Xplore
Year of Publication: 2024

Conclusion

In conclusion, Mr. Yu Zhang stands out as a highly competent and forward-thinking researcher with a robust academic foundation, a track record of innovation, and a clear research trajectory in artificial intelligence and cybersecurity. His interdisciplinary skill set, practical project experience, and passion for responsible AI make him an outstanding candidate for the Best Researcher Award. With continued dedication, he is well-positioned to make impactful contributions to the global scientific community

Dr. Bhavana Kaushik | Image Processing | Best Researcher Award |

Dr. Bhavana Kaushik | Image Processing | Best Researcher Award

Assistant Professor at University of Petroleum and Energy Studies, India.

Dr. Bhavana Kaushik is a dynamic academician, researcher, and technology leader with over a decade of experience in teaching, research, and innovation. She currently serves as an Assistant Professor at the University of Petroleum and Energy Studies (UPES), Dehradun. With a deep commitment to blending technology with societal transformation, Dr. Kaushik is actively involved in projects that promote digital inclusion, women’s empowerment, and entrepreneurship. Her interdisciplinary expertise spans computer vision, artificial intelligence, data science, and sustainable development. In addition to her academic accomplishments, she also holds leadership roles such as the State President (Uttarakhand) for the Information Technology Council under WICCI, where she champions women in technology across the state.

Professional Profile

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🎓 Education 

Dr. Kaushik is currently pursuing her Ph.D. in Computer Vision and Image Processing at UPES, Dehradun, where her research explores the intersection of artificial intelligence and visual computing. She holds a Master of Technology (M.Tech) in Computer Science from GLA University, Mathura, where she graduated with a Silver Medal and an impressive CGPA of 9.34. Her foundational education includes a Bachelor of Technology (B.Tech) in Computer Science and Engineering from Uttar Pradesh Technical University, graduating with distinction. She also excelled in her secondary and higher secondary schooling under the ICSE and CBSE boards.

💼 Experience 

Dr. Kaushik brings over 10 years of diverse experience across academia and industry. She has served as an Assistant Professor at UPES since 2018, where she teaches core computer science subjects and mentors student projects. Prior to this, she worked as a Systems Engineer at Infosys Limited, Pune, where she gained hands-on experience in Python programming, mainframe technologies, and application development. She also contributed to academia as a Teaching Assistant at GLA University. Her roles have included curriculum development, lab modernization, academic administration, and leadership of student societies and hackathons. Additionally, she leads women-in-tech initiatives as the WICCI State President (Uttarakhand) for the IT Council.

🔬 Research Interests

Dr. Kaushik’s research primarily centers around Computer Vision, Image Processing, and the application of Artificial Intelligence in Medicine, Surveillance, and Socioeconomic Development. Her work includes medical image compression, object tracking in videos, solar flare classification, and deepfake detection. She has also contributed to impactful research in rural development and digital empowerment through ICT tools. Her current pursuits explore the integration of AI technologies within healthcare imaging and metaverse environments, reflecting her commitment to high-impact, interdisciplinary research.

🏆 Honors & Awards

Dr. Kaushik’s academic journey is marked by notable accolades. She has been awarded a Silver Medal for her M.Tech performance and consistently topped her class in B.Tech. She is a qualified NET and GATE candidate (multiple years), which reflects her academic rigor. As an International Speaker at the Women Economic Forum – ASEAN 2025 and a regular contributor to national development programs funded by DST, she continues to receive recognition for both scholarly and social innovation contributions.

Top Noted Publications:

Title: Computational Intelligence‐Based Method for Automated Identification of COVID‐19 and Pneumonia by Utilizing CXR Scans
Authors: B. Kaushik, D. Koundal, N. Goel, A. Zaguia, A. Belay, H. Turabieh
Citations: 8
Index: Computational Intelligence and Neuroscience
Year of Publication: 2022

Title: Investigation of Solar Flare Classification to Identify Optimal Performance
Authors: A. Kakde, D. Sharma, B. Kaushik, N. Arora
Citations: 6
Index: ELCVIA Electronic Letters on Computer Vision and Image Analysis
Year of Publication: 2021

Title: A Context Based Tracking for Similar and Deformable Objects
Authors: B. Kaushik, M. Kumar, C. Bhatanagar, A.S. Jalal
Citations: 5
Index: International Journal of Computer Vision and Image Processing (IJCVIP)
Year of Publication: 2018

Title: Intelligent Interactions: Exploring Human–Computer Interaction in the Metaverse Through Artificial Intelligence
Author: B. Kaushik
Citations: 3
Index: Understanding the Metaverse (Springer Book Chapter)
Year of Publication: 2024

Conclusion:

Dr. Bhavana Kaushik exemplifies the modern academic researcher — technically proficient, socially responsible, and future-focused. Her balanced contributions to both scholarly research and community development make her a valuable asset to the academic and innovation ecosystem. With her ongoing Ph.D., growing list of high-impact publications, and active role in promoting women in STEM, she stands out as an ideal candidate for recognition such as the Best Researcher Award. Her journey reflects a perfect harmony between academic depth, leadership, innovation, and empowerment.

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

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

Professional Profile

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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.

Mr Bhavya Gandhi | Data Science for Health | Best Researcher Award |

Mr. Bhavya Gandhi | Data Science for Health | Best Researcher Award | 

Medical Student , at Michael G. DeGroote School of Medicine , Canada.

Mr. Bhavya Gandhi is an aspiring physician-researcher with a growing reputation for his contributions at the intersection of medicine, artificial intelligence, and global health. Currently pursuing his Doctor of Medicine at the Michael G. DeGroote School of Medicine (McMaster University), he has already led and collaborated on several research projects with a strong focus on AI applications in clinical diagnostics and patient safety. Bhavya’s profile reflects a rare blend of academic excellence, innovative thinking, and research leadership, making him a standout early-career scholar in Canadian medical academia.

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Education 🎓

Bhavya is currently enrolled in the Doctor of Medicine (M.D.) program at the Michael G. DeGroote School of Medicine, Hamilton Campus (2023–Present). He previously earned a Bachelor of Science at the University of Toronto (2020–2023), majoring in Biology for Health Sciences with minors in Biomedical Communication and Environmental Science. He graduated with a perfect 4.00 GPA and was recognized as a Dean’s List Scholar throughout his undergraduate studies, underscoring his academic diligence and commitment to excellence.

Experience 👩‍

Bhavya brings valuable hands-on experience from both research and clinical settings. From 2021 to 2023, he served as a Clinical Study Coordinator at Albion Finch Medical Centre, working on high-profile clinical trials for pharmaceutical companies including Moderna. This role involved responsibilities as a blinded/unblinded coordinator and pharmacist, providing him with a robust foundation in trial design and execution. Concurrently, he has held various Research Assistant and Lead Investigator roles at McMaster University and the Research Institute of St. Joe’s Hamilton, contributing to numerous interdisciplinary and collaborative studies involving AI, medication safety, and systematic reviews.

Research Interests 🔬

Bhavya’s research primarily centers on the integration of artificial intelligence and machine learning into clinical decision-making, with a focus on infectious diseases, cardiac risk prediction, and electronic medical record optimization. He has led or co-led projects examining the use of large language models (LLMs) in analyzing returning traveler infections, fever diagnostics, and AI-driven medication safety alerts. His work also extends to machine learning in myocardial injury prediction post-surgery and computational tools for evaluating prescribing competency in medical students. These contributions place him at the forefront of the evolving field of digital health and AI-enhanced clinical practice.

Awards 🏆

Among Bhavya’s accolades is the NSERC Undergraduate Student Research Award (USRA), awarded for his work in molecular neuroscience and protein interaction studies. He has also been recognized multiple times on the Dean’s List at the University of Toronto for maintaining a perfect GPA. His early leadership in impactful research projects has led to presentations at respected academic forums such as the Research Institute of St. Joe’s Hamilton and the EMRG Annual Student Seminar, further validating his scholarly contributions.

Top Noted Publications 📚

Title: Applications of Generative Artificial Intelligence in Electronic Medical Records: A Scoping Review
Authors: Leo Morjaria, Bhavya Gandhi, Nabil Haider, Matthew Mellon, Matthew Sibbald
Journal: Information
DOI: 10.3390/info16040284
Publication Year: 2025
Publication Date: April 1, 2025
Indexing: Indexed in major academic databases including Scopus, Web of Science, and MDPI

Conclusion

Bhavya Gandhi is a highly promising researcher with notable leadership, academic rigor, and innovation, especially in the emerging domain of AI in healthcare. For student, early-career, or innovation-focused research awards, Bhavya is extremely well-qualified. With a few more published works and individual accolades, Bhavya could easily rise into the top tier of emerging researchers in Canadian medical academia.

Prof. Dr. Harpreet Kaur | Image processing | Best Researcher Award |

Prof. Dr. Harpreet Kaur | Image processing | Best Researcher Award | 

Professor , at lovely Professional University, India.

Prof. (Dr.) Harpreet Kaur is a distinguished academician and researcher in Computer Science & Engineering, specializing in Digital Image Processing and Image Retrieval. She is currently a Professor at Lovely Professional University, Phagwara, Punjab, with over two decades of experience in teaching, research, and academic leadership. Her expertise spans various domains of emerging technologies, and she has significantly contributed to academia through research, mentorship, and administrative roles.

Professional Profile

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Education 🎓

Prof. Kaur holds a Bachelor of Technology (B.Tech) in Computer Science & Engineering, followed by a Master of Technology (M.Tech) in Information Technology. She further pursued her Doctor of Philosophy (Ph.D.) in Computer Science & Engineering, solidifying her expertise in advanced computing and digital technologies. Her strong academic background has enabled her to lead research initiatives and mentor scholars in her domain.

Professional Experience 💼

With an illustrious career spanning over 20 years, she has held various leadership roles, including Head of Department (CSE), Deputy Dean Academics, and Convener of multiple national and international conferences. She has contributed to the academic ecosystem through faculty development programs, workshops, and research conferences, fostering knowledge-sharing and skill development in the field of engineering and technology.

Research Interests 🌍

Her research primarily revolves around Digital Image Processing, Image Retrieval, Artificial Intelligence, and Emerging Technologies. With a passion for innovation, she has actively contributed to cutting-edge research by publishing over 70+ papers in international conferences and journals, along with 25 national-level research publications. Her expertise extends beyond theoretical research, as she has successfully published more than 15 patents, showcasing her commitment to applied research and technological advancements.

Awards & Honors 🏆

Prof. Kaur’s contributions have been widely recognized through multiple prestigious awards, including the Best Paper Presentation Award (Dubai, 2019), Quality Education Leadership Award (2020), International Teaching Excellence Award (2021), International Distinguished Teacher Award (2023), and the International Research Excellence Award (2024-25). These accolades highlight her excellence in both research and academia.

Top Noted Publications 📚

Synthesis and characterization of ZIF-8 nanoparticles for controlled release of 6-mercaptopurine drug – H. Kaur, G.C. Mohanta, V. Gupta, D. Kukkar, S. Tyagi – 363 citationsJournal of Drug Delivery Science and Technology2017

Electrochemical synthesized copper oxide nanoparticles for enhanced photocatalytic and antimicrobial activity – R. Katwal, H. Kaur, G. Sharma, M. Naushad, D. Pathania – 356 citationsJournal of Industrial and Engineering Chemistry2015

Image fusion techniques: a survey – H. Kaur, D. Koundal, V. Kadyan – 319 citationsArchives of Computational Methods in Engineering2021

Computer-aided designing of immunosuppressive peptides based on IL-10 inducing potential – G. Nagpal, S.S. Usmani, S.K. Dhanda, H. Kaur, S. Singh, M. Sharma – 275 citationsScientific Reports2017

Posttraumatic stress disorder in maltreated youth: A review of contemporary research and thought – C.A. Kearney, A. Wechsler, H. Kaur, A. Lemos-Miller – 267 citationsClinical Child and Family Psychology Review2010

Conclusion

Prof. (Dr.) Harpreet Kaur has strong credentials for the Best Researcher Award, particularly due to her extensive research output, innovation through patents, academic leadership, and multiple recognitions. Strengthening international collaborations, securing research grants, and publishing in high-impact factor journals can further enhance her candidacy for elite research awards.

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

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 💼

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 📚

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.

Mr Ernesto Diaz | Data Scientist | Best Researcher Award

Mr Ernesto Diaz |  Data Scientist | Best Researcher Award

Assistant Specialist at University of California, San Francisco – Radiology & Biomedical Imaging , United States.

Ernesto Diaz is an accomplished researcher and data scientist specializing in biomedical imaging and artificial intelligence applications in healthcare. With a strong background in medical imaging, deep learning, and data science, he has contributed significantly to Hyperpolarized Carbon-13 MRI research, cancer imaging, and radiation oncology. His work has been recognized through prestigious NIH awards, peer-reviewed publications, and multiple conference presentations. Passionate about advancing healthcare technology, Ernesto combines technical expertise with a commitment to mentorship and diversity in STEM.

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Education 🎓

Ernesto earned his Bachelor of Science in Computer Science from San Francisco State University in 2022, graduating with Dean’s List honors (2020-2022). His education provided a strong foundation in programming, data analysis, and computational research, which he has applied extensively in biomedical imaging and artificial intelligence projects.

Professional Experience 💼

  • As a Data Scientist at UCSF’s Department of Radiology and Biomedical Imaging, Ernesto leads software development for medical imaging analysis, enhancing data processing and visualization tools. His previous research experience includes working on automated radiation treatment planning and bioinformatics coding for population health studies. His contributions have improved efficiency in clinical workflows and advanced AI applications in medical imaging.

Research Interests 🌍

His research revolves around Hyperpolarized Carbon-13 MRI, deep learning for medical image segmentation, and automation in radiation oncology. At UCSF, he developed a DICOM standardization tool for metabolic imaging and co-developed a U-Net deep learning model for prostate cancer segmentation. Additionally, he has explored health disparities in underserved communities, analyzing COVID-19’s impact on marginalized populations.

Awards & Honors 🏆

  • NIH Diversity Supplement Award (2022-2024) – Recognized for contributions to Hyperpolarized 13C MRI research.
  • NIH-SF BUILD Scholar (2021-2022) – Selected for leadership potential and commitment to diversity in research.
  • Dean’s List (2020-2022) – Awarded for academic excellence at San Francisco State University.

Top Noted Publications 📚

Title: Deep Learning-Based Tumor Segmentation of Murine Magnetic Resonance Images of Prostate Cancer Patient-Derived Xenografts

Authors: Satvik Nayak, Henry Salkever, Ernesto Diaz, Avantika Sinha, Nikhil Deveshwar, Madeline Hess, Matthew Gibbons, Sule Sahin, Abhejit Rajagopal, Peder E. Z. Larson, et al.

Journal: Tomography

Publication Year: 2025

DOI: 10.3390/tomography11030021

Indexing: Indexed in major scientific databases.

Conclusion

Ernesto Diaz is a rising leader in medical imaging research, blending AI, data science, and biomedical imaging to drive innovation. With his technical skills, research excellence, and dedication to mentorship, he continues to push the boundaries of healthcare technology and scientific discovery. 🚀

Dr Han Gao | Artificial Intellegence | Best Researcher Award |

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 💼

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 📚

Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data
L. Sun, H. Gao, S. Pan, J.-X. Wang916 citationsComputer 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. Wang567 citationsJournal 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. Wang240 citationsComputer 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. Wang214 citationsPhysics of Fluids, 2021

Predicting physics in mesh-reduced space with temporal attention
X. Han, H. Gao, T. Pfaff, J.-X. Wang, L.-P. Liu106 citationsICLR, 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.