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.

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

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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.

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

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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

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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.

Professional Profile

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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. 🚀