Sarah Marzen | Data Science | Best Researcher Award

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Prof. Sarah Marzen | Data Science | Best Researcher Award

Associate Professor | Keck Graduate Institute, Claremont | United States

Professor Sarah Marzen is a prominent physicist and interdisciplinary researcher based at the W. M. Keck Science Department, representing Pitzer, Scripps, and Claremont McKenna Colleges in California. With a strong foundation in theoretical physics and complex systems, she is widely recognized for her research at the intersection of information theory, neuroscience, and machine learning. Her work explores how biological and artificial systems perceive, predict, and adapt to their environments. Through academic excellence and a commitment to scientific inquiry, she has established herself as a respected voice in computational neuroscience and resource-rational modeling

Professional Profile

Scopus | Google scholar

Education

Professor Marzen earned her Ph.D. in Physics from the University of California, Berkeley, where she conducted pioneering research on “Bio-inspired problems in rate-distortion theory” under the mentorship of Professor Michael R. DeWeese. Prior to her doctoral studies, she completed a Bachelor of Science degree in Physics at the California Institute of Technology (Caltech), reflecting an early and consistent commitment to scientific excellence. She has also participated in several prestigious summer schools and professional development programs, including the Santa Fe Institute’s Complex Systems School and the MIT Kauffman Teaching Certificate Program.

Experience

Dr. Marzen currently serves as Associate Professor of Physics at the W. M. Keck Science Department. Prior to this, she served as an Assistant Professor at the same institution . Her earlier career includes a postdoctoral fellowship at the Massachusetts Institute of Technology, where she collaborated with Professors Nikta Fakhri and Jeremy England. Her teaching experience is complemented by her role as a Seminar XL/LE Facilitator at MIT, underscoring her dedication to student engagement and mentorship.

Research Interests

Professor Marzen’s research focuses on sensory prediction, reinforcement learning, resource rationality, and the integration of information theory with biological systems. She investigates how both living and artificial neural systems process and respond to information in complex, dynamic environments. Her interdisciplinary approach spans computational modeling, machine learning theory, and theoretical neuroscience. She is currently involved in major research initiatives, including an Army Research Laboratory MURI project centered on hybrid biological-artificial neural networks and a series of workshops supported by the Sloan Foundation and Carnegie Institute

Honors

Dr. Marzen has received numerous recognitions for her academic contributions, including serving as Principal Investigator (PI) or Co-PI on several major research grants. Within her institution, she has held key service roles such as membership on the Executive Committee, DEI Committee, and Data Science Curriculum Coherence Committee, reflecting her leadership in fostering academic inclusivity and interdisciplinary learning.

Top Noted Publications

Title: Statistical mechanics of Monod–Wyman–Changeux (MWC) models
Citation: 128
Year of Publication: 2013

Title: On the role of theory and modeling in neuroscience
Citation: 100
Year of Publication: 2023

Title: The evolution of lossy compression
Citation: 65
Year of Publication: 2017

Title: Informational and causal architecture of discrete-time renewal processes
Citation: 46
Year of Publication: 2015

Title: Predictive rate-distortion for infinite-order Markov processes
Citation: 45
Year of Publication: 2016

Conclusion

Professor Sarah Marzen is a highly accomplished academic whose innovative research bridges physics, neuroscience, and artificial intelligence. Her work advances our understanding of how systems learn, adapt, and make decisions under constraints, with implications for both scientific theory and technological development. Through her leadership, mentorship, and scholarly impact, she continues to shape the future of interdisciplinary research and education. Her academic rigor, commitment to collaboration, and visionary research make her a key contributor to the global scientific community.

Mr Yu Zhang | Artificial Intelligence | Best Researcher Award |

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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

Scopus

Orcid

🎓 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

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

Scopus

Google Scholar

Orcid

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.