Dipesh | Computational Neuroscience | Best Researcher Award

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Assist. Prof. Dr. Dipesh | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Dipesh | SR University | India

Dr. Dipesh is a dedicated mathematician specializing in mathematical modeling, with extensive experience in both academic and research domains. He has made significant contributions to applied mathematics, particularly in areas intersecting numerical methods, AI/ML, and fluid dynamics. Dr. Dipesh has actively organized and coordinated multiple academic programs, including national workshops, faculty development programs, and departmental initiatives, demonstrating strong leadership in fostering educational and research excellence. His efforts in coordinating the Department of Intellectual Property Rights and successfully conducting events such as RAFAS highlight his commitment to academic growth and institutional development. Academically, he has pursued rigorous training from undergraduate to postdoctoral levels, culminating in advanced research at Harran University, Turkey. Dr. Dipesh’s scholarly output includes 30 documents that have been cited 103 times, reflecting an h-index of 7, underscoring the impact and relevance of his research contributions in applied mathematics and related interdisciplinary fields. His approach emphasizes quality teaching, student placement, institutional ranking, and enhancing the overall goodwill of the organizations he serves. Driven by a passion for tackling challenges and improving systems with limited resources, Dr. Dipesh continually seeks to connect with external environments, promote collaborative work, and advance the reach and recognition of academic institutions.

Profiles: Scopus | Orcid | Google Scholar | Research Gate | Linked In

Featured Publications

  1. Mathematical model of Cynodon Dactylon’s allelopathic effect on perennial ryegrass for exploring plant-plant interactions based upon ordinary differential equations. (2025). Partial Differential Equations in Applied Mathematics.

  2. Modelling the role of delay in blood flow dynamics in human body using delay differential equations. (2025). Physica A: Statistical Mechanics and Its Applications.

  3. On the modeling the impact of delay on stock pricing fluctuations using delay differential equations. (2025). Physica A: Statistical Mechanics and Its Applications.

Masoud Kargar | Computational Neuroscience | Best Researcher Award

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Assist. Prof. Dr. Masoud Kargar | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Masoud Kargar | Islamic Azad University | Iran

Dr. Masoud Kargar is an Assistant Professor in the Department of Computer Engineering at Islamic Azad University, Tabriz Branch, specializing in artificial intelligence, machine learning, reinforcement learning, and software system engineering. He earned his bachelor’s degree in applied mathematics, master’s degree in software engineering, and Ph.D. in software engineering with a focus on modularization of multi-programming software systems. Dr. Kargar has extensive academic experience, having taught a wide range of undergraduate, master’s, and doctoral courses in advanced programming, algorithms, software engineering, data mining, big data, project management, and natural language processing across multiple universities. He also serves as the Director of Information and Communication Technology and leads the development of various software systems. Dr. Kargar is a member of the editorial board of the Iranian Journal of Computer Science (Springer) and has published 19 documents, which have been cited 89 times, giving him an h-index of 6. His research contributions have significantly advanced the fields of machine learning and software engineering, and his academic leadership continues to inspire both students and colleagues. Dr. Kargar remains committed to fostering innovation and excellence in computer engineering education and research.

Profiles: Scopus | Google Scholar | Orcid | Research Gate

Featured Publications

Karegar, M., Isazadeh, A., Fartash, F., Saderi, T., & Navin, A. H. (2008). Data-mining by probability-based patterns. Proceedings of the 30th International Conference on Information Technology Interfaces, 28.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2019). Multi-programming language software systems modularization. Computers & Electrical Engineering, 80, 106500.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2017). Semantic-based software clustering using hill climbing. 2017 International Symposium on Computer Science and Software Engineering.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2020). Improving the modularization quality of heterogeneous multi-programming software systems by unifying structural and semantic concepts. Journal of Supercomputing, 76(1), 17.

Navin, A. H., Fesharaki, M. N., Mirnia, M., & Kargar, M. (2007). Modeling of random variable with digital probability hyper digraph: Data-oriented approach. Proceedings of World Academy of Science, Engineering and Technology, 25, 25.

Bayani, A., & Kargar, M. (2024). LDCNN: A new arrhythmia detection technique with ECG signals using a linear deep convolutional neural network. Physiological Reports, 12(17), e16182.

Karegar, M., Saderi, T., Isazadeh, A., & Fartash, F. (2008). Electronic consulting in marketing. 2008 3rd International Conference on Information and Communication Technology, 5.

Ramesh Chatragadda | Systems Neuroscience | Best Researcher Award

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Dr. Ramesh Chatragadda | Systems Neuroscience | Best Researcher Award

Dr. Ramesh Chatragadda, National Institute of Oceanography, India.

Dr. Ramesh Chatragadda is a leading Indian marine biologist whose academic and professional journey reflects a deep commitment to ocean science. With a strong educational foundation in Marine Biology, he has steadily progressed through research fellowships, national postdoctoral work, and various scientific roles, ultimately becoming a Senior Scientist at the CSIR-National Institute of Oceanography and an Assistant Professor at AcSIR. His research focuses on biological oceanography, marine microbial ecology, and environmental sustainability. Internationally recognized through numerous early-career awards and travel fellowships, Dr. Chatragadda’s work continues to influence marine science both in India and globally. His role as a researcher, mentor, and collaborator underscores his dedication to advancing the understanding of ocean ecosystems.

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🌟 Strengths for the Best Researcher Award

Dr. Ramesh Chatragadda stands out as a highly deserving candidate for the Best Researcher Award due to his impressive research trajectory and impactful scientific contributions. His specialization in biological oceanography and marine microbial ecology demonstrates a critical understanding of marine ecosystems and environmental sustainability. With a Ph.D. in Marine Biology and a robust professional history at premier institutions like CSIR-NIO, NIOT, and NCCR, he brings both field experience and academic depth to his research.

A major strength lies in his international recognition, having secured multiple prestigious awards and travel grants from global bodies such as COBRA, SCOR, PICES, and the Grantham Foundation. These accolades reflect not only the quality but also the global relevance of his research. Additionally, his dual role as a Senior Scientist and Assistant Professor underlines his capacity to balance innovation, publication, and mentorship. His contributions are actively shaping the future of Indian marine research and building strong international scientific networks.

🔍 Areas for Improvement

While Dr. Chatragadda’s achievements are significant, he may consider expanding his interdisciplinary collaborations further, especially with climate scientists, policy makers, and data modelers to translate research into direct marine conservation policies. Increasing open-access publications, science communication efforts, and involvement in community outreach or citizen science programs could enhance public engagement and increase the societal impact of his work. Additionally, assuming editorial roles in international journals or organizing global symposiums would further cement his position as a thought leader in ocean science.

🎓 Early Academic Pursuits

Dr. Ramesh Chatragadda’s journey into the depths of marine science began with a strong academic foundation. He completed his B.Sc. in 2009 from Acharya Nagarjuna University with a focus on Botany, Zoology, and Chemistry. His passion for the ocean and its living resources led him to pursue an M.Sc. in Marine Biology and Fisheries from Andhra University, graduating in 2011. Driven by an insatiable curiosity about marine ecosystems, he earned his Ph.D. in Marine Biology from Pondicherry University in 2016. These formative years not only refined his academic interests but laid a solid groundwork for his future explorations in biological oceanography.

🧪 Professional Endeavors

Dr. Chatragadda’s professional journey reflects a consistent rise in scientific responsibility and academic excellence. After gaining experience as a Junior and Senior Research Fellow at Pondicherry University, he became a National Postdoctoral Fellow at the Atal Centre for Ocean Science and Technology for Islands under the National Institute of Ocean Technology. His career further advanced with his appointment as Project Scientist-B at the National Centre for Coastal Research. He later joined the CSIR-National Institute of Oceanography (NIO) as a Scientist, and was promoted to Senior Scientist in September 2023. Alongside, he holds the designation of Assistant Professor at the Academy of Scientific and Innovative Research (AcSIR), mentoring the next generation of ocean scientists.

🌊 Contributions and Research Focus

At the heart of Dr. Chatragadda’s career lies his profound commitment to understanding marine life and the ecological complexities of ocean systems. His expertise in biological oceanography allows him to explore the intricate interactions between marine organisms and their environment. He is especially noted for his work in marine microbial ecology, bioluminescence, and the functional dynamics of oceanic biological processes. His research endeavors contribute to sustainable marine resource utilization, climate resilience, and biodiversity conservation in coastal and deep-sea ecosystems.

Publication

1. Multifaceted Applications of Microbial Pigments: Current knowledge, Challenges, and Future Directions for Public Health Implications
L Ramesh, CH., Vinithkumar, N.V., Kirubagaran, R., Venil, C.K. and Dufosse — 2019

2. Ecological and biotechnological aspects of pigmented microbes: a way forward in development of food and pharmaceutical grade pigments
CH Ramesh, L Dufosse — 2021

3. Marine pigmented bacteria: A prospective source of antibacterial compounds
R Ramesh, CH., Vinithkumar, N.V. and Kirubagaran — 2019

4. Applications of Prodigiosin Extracted from Marine Red Pigmented Bacteria Zooshikella sp. and Actinomycete Streptomyces sp.
C Ramesh, NV Vinithkumar, R Kirubagaran, CK Venil, L Dufosse — 2020

5. Marine natural products from tunicates and their associated microbes
CH Ramesh, T Bhushan Rao, R Mohanraju, N Thakur, L Dufossé — 2021

6. Natural substrates and culture conditions to produce pigments from potential microbes in submerged fermentation
CH Ramesh, VR Prasastha, M Venkatachalam, L Dufosse — 2022

7. Toxicity studies of Trichodesmium erythraeum (Ehrenberg, 1830) bloom extracts, from Phoenix Bay, Port Blair, Andamans
S Narayana, J Chitra, SR Tapase, V Thamke, P Karthick, C Ramesh, … — 2014

8. Seaweed potential of Little Andaman, India
CH Karthick, P., Mohanraju. R., Murthy, K.N., Ramesh — 2013

9. Antibacterial activity of certain cephalopods from Andamans, India
R Mohanraju, DB Marri, P Karthick, S Narayana, KN Murthy, C Ramesh — 2013

10. Distribution and diversity of seaweeds in North and South Andaman Island
P Karthick, R Mohanraju, CH Ramesh, KN Murthy, S Narayana — 2013

🏁 Conclusion

In conclusion, Dr. Ramesh Chatragadda demonstrates a rare combination of scholarly excellence, research productivity, and global outreach. His commitment to marine biology, recognized by multiple international honors, positions him as a strong contender for the Best Researcher Award. While a few strategic enhancements could broaden the impact of his work, his existing contributions already reflect a high level of research merit, leadership potential, and long-term vision. Based on his credentials and continued dedication to advancing marine science, he is highly suitable for this prestigious recognition.

Aiying Zhang | Computational Neuroscience | Best Researcher Award

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Assist. Prof. Dr. Aiying Zhang | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Aiying Zhang, University of Virginia, United States.

Dr. Aiying Zhang is a rising scholar in the field of mental health data science, currently serving as an Assistant Professor at the University of Virginia and a Faculty Member at the UVA Brain Institute. Her academic foundation spans statistics, biomedical engineering, and clinical biostatistics, acquired from esteemed institutions including USTC, Tulane University, and Columbia University. Her research focuses on developing advanced computational and statistical tools—such as graphical models and multimodal fusion—to decode complex brain data from imaging and genetics. She applies these innovations to better understand and predict psychiatric conditions such as schizophrenia and Alzheimer’s disease. Her work is distinguished by its interdisciplinary nature, translational relevance, and potential to reshape clinical approaches to mental health.

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🎓 Early Academic Pursuits

Aiying Zhang’s journey into the realm of data science and mental health research began with a strong foundation in quantitative sciences. She earned her Bachelor of Science degree in Statistics from the prestigious School for the Gifted Young at the University of Science and Technology of China (USTC) in 2014. Driven by a passion for biomedical innovation and its intersection with human health, she pursued a Ph.D. in Biomedical Engineering from Tulane University, which she completed in 2021. Her graduate years were marked by deep inquiry into statistical modeling and neuroimaging, laying the groundwork for her later interdisciplinary research. She further honed her expertise through postdoctoral training in Clinical Biostatistics and Psychiatry at Columbia University Irving Medical Center, where she blended statistical rigor with clinical insight.

💼 Professional Endeavors

Dr. Zhang is currently an Assistant Professor of Data Science at the University of Virginia, where she has been on the tenure-track faculty since August 2023. She also holds a concurrent position as a Faculty Member at the UVA Brain Institute, underscoring her active role in advancing brain research across institutional boundaries. Prior to her academic appointment at UVA, she served as a Research Scientist II at the New York State Psychiatric Institute, contributing to high-impact psychiatric research. Her professional journey also includes research assistantships at Tulane University and the University of Florida, roles in which she cultivated strong collaborative and translational research skills.

🧠 Contributions and Research Focus

Dr. Zhang’s research lies at the intersection of data science, neuroscience, and mental health. She specializes in developing advanced statistical and computational methodologies to investigate the biological underpinnings of psychiatric and neurodevelopmental disorders. Her work prominently features the use of graphical models—both directed and undirected—and machine learning techniques to analyze complex datasets, such as MRI, DTI, fMRI, MEG, and various genomic modalities including SNP and DNA methylation. Her research has contributed to a deeper understanding of conditions like schizophrenia, Alzheimer’s disease, obsessive-compulsive disorder, and anxiety disorders, through the lens of multimodal data fusion and integrative neurogenetics.

🧪 Innovation in Mental Health Data Science

A distinctive hallmark of Dr. Zhang’s scholarship is her innovative application of multimodal fusion techniques to disentangle the complexities of typical and atypical brain development. Her work leverages high-dimensional neuroimaging and genetic data to draw meaningful inferences about mental health trajectories. She is particularly focused on building interpretable models that bridge the gap between data and clinical insight, thereby enabling earlier and more precise diagnostics. By combining machine learning with biomedical expertise, her contributions pave the way for next-generation tools in psychiatry and neuroscience.

🏅 Accolades and Recognition

Throughout her academic and professional trajectory, Dr. Zhang has earned widespread respect for her analytical acumen and interdisciplinary collaborations. Her postdoctoral role at Columbia, a hub for clinical psychiatry and biostatistics, positioned her among leaders in the field and enriched her research portfolio with translational applications. Her selection as faculty at a leading institution like UVA further reflects recognition of her scholarly excellence and her potential to drive future innovations in mental health data science.

🌍 Impact and Influence

Dr. Zhang’s work has significant implications for both the scientific community and clinical practice. Her methods empower researchers and clinicians alike to draw meaningful patterns from multimodal datasets, thereby advancing precision psychiatry. Moreover, her collaborative efforts across biomedical engineering, statistics, and clinical disciplines have fostered integrative frameworks that extend beyond academic settings into real-world applications. Her contributions are helping to shape a more data-driven and personalized future in mental health care.

🔮 Legacy and Future Contributions

As she continues her academic journey, Dr. Zhang aims to expand her research frontiers by exploring dynamic brain-behavior associations and improving the interpretability of AI models in clinical contexts. With a commitment to mentorship and open science, she is building a legacy rooted in intellectual rigor, innovation, and societal relevance. Her future contributions are expected to not only deepen our understanding of mental health disorders but also inspire a new generation of data scientists dedicated to neuroscience and human well-being.

Publication

  • Leverage multimodal neuro-imaging and genetics to identify causal relationship between structural and functional connectivity and ADHD with Mendelian randomization
    C Ji, S Lee, S Sequeira, J Jin, A Zhang — 2025

 

  • Integrated brain connectivity analysis with fmri, dti, and smri powered by interpretable graph neural networks
    G Qu, Z Zhou, VD Calhoun, A Zhang, YP Wang — 2025

 

  • Altered hierarchical rank in intrinsic neural time-scales in autism spectrum disorder
    A Solomon, W Yu, J Rasero, A Zhang — 2025

 

  • A Privacy-Preserving Domain Adversarial Federated learning for multi-site brain functional connectivity analysis
    Y Zhang, L Wang, KJ Su, A Zhang, H Zhu, X Liu, H Shen, VD Calhoun, … — 2025

 

  • A Novel GNN Framework Integrating Neuroimaging and Behavioral Information to Understand Adolescent Psychiatric Disorders
    W Yu, G Qu, Y Kim, L Xu, A Zhang — 2025

 

  • A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence
    A Zhang, G Zhang, B Cai, TW Wilson, JM Stephen, VD Calhoun, YP Wang — 2024

 

  • Exploring hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer’s disease
    A Zhang, K Wengler, X Zhu, G Horga, TE Goldberg, S Lee — 2024

 

  • Time‐varying dynamic Bayesian network learning for an fMRI study of emotion processing
    L Sun, A Zhang, F Liang — 2024

 

  • Altered hierarchical gradients of intrinsic neural timescales in mild cognitive impairment and Alzheimer’s disease
    A Zhang, K Wengler, X Zhu, G Horga, TE Goldberg, S Lee, … — 2024

 

  • Associations Between Brain Connectivity and Psychiatric Symptoms in Children: Insights into Adolescent Mental Health
    D Mutu, K Ji, X He, S Lee, S Sequeira, A Zhang — 2024

 

🧾 Conclusion

Dr. Zhang’s journey exemplifies a seamless integration of data science and neuroscience to address pressing mental health challenges. Her innovative use of multimodal data and machine learning not only contributes to scientific advancement but also enhances real-world clinical decision-making. As she continues to pioneer research at the intersection of computation and psychiatry, her influence is poised to grow, shaping the future of precision mental health care and empowering both academia and clinical practice through data-driven insights.

 

Fabiano Papaiz | Computational Neuroscience | Best Researcher Award

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Prof. Fabiano Papaiz | Computational Neuroscience | Best Researcher Award

Prof. Fabiano Papaiz, IFRN, Brazil.

Fabiano Papaiz is a dedicated academic and professional in the field of education and technology, affiliated with the Federal Institute of Education, Science, and Technology of Rio Grande do Norte (IFRN) in Brazil. With a strong foundation in the intersection of education and technology, his work focuses on integrating modern technological innovations into educational practices. Through his research and professional endeavors, Papaiz has contributed significantly to advancing educational methods and improving learning environments. His accolades reflect his influence both within Brazil and internationally. His research aims to enhance educational outcomes by leveraging digital tools and resources, benefiting the academic community and shaping the future of learning.

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📚 Early Academic Pursuits

Fabiano Papaiz began his academic journey in Brazil, where he cultivated a strong foundation in the field of education and technology. His early academic pursuits were centered around exploring the intersections of education and technological advancements. With a keen interest in applied sciences, he honed his knowledge and skills through his academic experiences, leading him to a path of lifelong learning and research. Papaiz’s commitment to education in Brazil is evident, and his passion for technology-driven academic progress is one of the key pillars of his professional career.

💻 Professional Endeavors

Currently affiliated with the Federal Institute of Education, Science, and Technology of Rio Grande do Norte (IFRN), Fabiano Papaiz plays a pivotal role in shaping the future of education and technology. At IFRN, he is part of the DATINF (Department of Information Technology), where he works on integrating modern technological solutions with academic practices. His professional journey reflects his dedication to advancing educational methodologies and bridging the gap between technology and learning. As part of the institution, Papaiz has contributed to a wide range of educational initiatives that aim to enhance the learning experience in Brazil, especially in the field of information technology.

🔬 Contributions and Research Focus

Papaiz’s research interests lie in the dynamic field of information technology and its application to educational contexts. His research focuses on leveraging technological innovations to improve educational outcomes, develop new learning tools, and address contemporary challenges in the digital age. Fabiano’s academic contributions have been significant, with a strong emphasis on the role of technology in shaping modern education. His work not only influences the academic community but also helps to create a more tech-savvy generation of students who can navigate and thrive in a rapidly evolving digital world.

🏆 Accolades and Recognition

Throughout his career, Fabiano Papaiz has received numerous accolades for his contributions to education and technology. His work at IFRN has been recognized not only within Brazil but also internationally, as he continues to share his expertise with global academic and technological communities. His dedication to advancing the integration of information technology into education has earned him admiration from peers, students, and academic institutions alike. His reputation as a thought leader in the intersection of education and technology is well-established, marking him as an influential figure in his field.

🌍 Impact and Influence

Fabiano Papaiz’s work has made a profound impact on both the academic and technological landscapes of Brazil. His influence extends beyond the classroom, as his research and professional endeavors have shaped the way information technology is applied in education. Through his leadership and innovation, he has fostered the growth of more effective learning environments, enhanced by the use of digital tools and resources. His contributions have not only benefited his institution but also contributed to the wider educational community by offering solutions that address modern teaching and learning needs.

Publication

  • Title: Predicting ALS progression using Autoregressive deep learning models
    Authors: Fabiano Papaiz, Mario Emílio Teixeira Dourado, Jr, Ricardo Alexsandro de Medeiros Valentim, Felipe Ricardo dos Santos Fernandes, João Paulo Queiroz dos Santos, Antonio Higor Freire de Morais, Fernanda Brito Correia, Joel Perdiz Arrais
    Year: 2025

 

  • Title: RR3D: Uma solução para renderização remota de imagens médicas tridimensionais
    Author: Fabiano Papaiz
    Year: 2013

 

Conclusion

Fabiano Papaiz’s career exemplifies the transformative power of technology in education. His contributions, ranging from research to institutional leadership, have made a lasting impact on the integration of technology in educational settings. As he continues to innovate and lead, Papaiz’s legacy will undoubtedly shape the future of education, paving the way for more inclusive and effective learning environments. His ongoing work ensures that technology will remain a key driver in educational progress, with the potential to benefit generations of students and educators worldwide.

 

Francisco Mena | Computational Neuroscience | Best Researcher Award

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Mr. Francisco Mena | Computational Neuroscience | Best Researcher Award

Mr. Francisco Mena, University of Kaiserslautern-Landau, Germany.

Francisco Mena is a dynamic researcher in the field of machine learning, currently pursuing a PhD at the University of Kaiserslautern-Landau (RPTU), Germany. His academic roots trace back to Federico Santa María Technical University (UTFSM) in Chile, where he developed a strong foundation in computer engineering and data science. With a specialization in unsupervised learning, deep learning, and multi-view data fusion, his work focuses on building robust and scalable models that minimize human intervention and adapt to incomplete or noisy datasets—particularly in the context of Earth observation and crowdsourced data. He has worked across international research institutes like DFKI in Germany and Inria in France, contributing to global advancements in AI and data science. His teaching and mentoring roles, combined with his innovative research, mark him as a rising contributor to the future of intelligent systems.

Profile

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🎓 Early Academic Pursuits

Francisco Mena’s academic journey began with a strong foundation in computer engineering at Federico Santa María Technical University (UTFSM) in Chile. Demonstrating exceptional academic performance, he ranked in the top 10% of his class, securing the 4th position among 66 students. He pursued an integrated path that led him to obtain a Bachelor of Science, a Licenciado, and later the Ingeniería Civil en Informática degree. Driven by curiosity and a passion for machine learning, he transitioned seamlessly into postgraduate studies, earning a Magíster en Ciencias de la Ingeniería Informática at UTFSM. His master’s thesis, focused on mixture models in crowdsourcing scenarios, set the stage for his growing interest in unsupervised learning and probabilistic models.

💼 Professional Endeavors

Alongside his studies, Francisco actively engaged in diverse professional roles that enriched his technical and academic expertise. He served as a research assistant at the Chilean Virtual Observatory (CHIVO), contributing to astroinformatics projects by processing and organizing astronomical datasets from ALMA and ESO observatories. His early professional stint as a front-end and back-end developer provided him with hands-on industry experience. In academia, he held several teaching roles, progressing from laboratory assistant to lecturer in key courses such as computational statistics, artificial neural networks, and machine learning. Currently, as a Student Research Assistant at the German Research Centre for Artificial Intelligence (DFKI), he contributes to Earth observation projects, enhancing models for crop yield prediction using multi-view data.

🔬 Contributions and Research Focus

Francisco’s research is anchored in machine learning with a special emphasis on unsupervised learning, deep neural architectures, multi-view learning, and data fusion. His doctoral work at University of Kaiserslautern-Landau (RPTU) focuses on handling missing views in Earth observation data, an increasingly important issue in remote sensing. He explores innovative methods that challenge traditional domain-specific models by advocating for approaches that minimize human intervention and labeling. His core research areas include autoencoders, deep clustering, dimensionality reduction, and latent variable modeling, with applications extending to vegetation monitoring, neural information retrieval, and crowdsourcing.

🌍 Global Collaborations

Francisco’s commitment to impactful research is evident in his international collaborations. In addition to his work in Germany, he undertook a research visit to Inria in Montpellier, France, where he explored cutting-edge topics such as multi-modal co-learning, multi-task learning, and mutual distillation. These collaborations allow him to expand the practical relevance of his research across geographical and disciplinary boundaries, contributing to global discussions in artificial intelligence and data science.

🧠 Impact and Influence

Through his extensive academic involvement, Francisco has shaped the understanding of machine learning models that are both scalable and adaptable to real-world challenges. His contributions in crowdsourcing, particularly the use of latent group variable models for large-scale annotations, reflect his commitment to developing resource-efficient models. His influence extends into education, where he has mentored students and shaped curriculum delivery in machine learning-related subjects. By leveraging tools like PyTorch, QGIS, and Slurm, he ensures his work remains at the cutting edge of technological advancement.

🏆 Recognition and Growth

Francisco’s academic excellence is evident from his consistent achievements and recognition. His GPA of 94% during his master’s program stands as a testament to his dedication and intellect. Being ranked #4 in his undergraduate program highlights his sustained academic brilliance. His teaching roles at UTFSM and lecturing at RPTU further underscore the trust institutions place in his knowledge and teaching abilities.

🚀 Legacy and Future Contributions

With a clear research vision and a strong international presence, Francisco Mena is poised to leave a lasting impact in the field of artificial intelligence, particularly in unsupervised learning and Earth observation. His focus on reducing dependency on human intervention, increasing model generalizability, and handling incomplete or noisy data reflects a future-forward approach. As his doctoral journey progresses, he is expected to continue influencing how machine learning models are conceptualized, designed, and deployed in real-world applications—especially those that require scalable, domain-agnostic solutions.

Publication

 

  • Harnessing the power of CNNs for unevenly-sampled light-curves using Markov Transition Field – M Bugueño, G Molina, F Mena, P Olivares, M Araya – 2021

 

  • Common practices and taxonomy in deep multiview fusion for remote sensing applications – F Mena, D Arenas, M Nuske, A Dengel – 2024

 

  • A binary variational autoencoder for hashing – F Mena, R Ñanculef – 2019

 

  • Refining exoplanet detection using supervised learning and feature engineering – M Bugueño, F Mena, M Araya – 2018

 

  • Predicting crop yield with machine learning: An extensive analysis of input modalities and models on a field and sub-field level – D Pathak, M Miranda, F Mena, C Sanchez, P Helber, B Bischke, … – 2023

 

  • Adaptive fusion of multi-modal remote sensing data for optimal sub-field crop yield prediction – F Mena, D Pathak, H Najjar, C Sanchez, P Helber, B Bischke, P Habelitz, … – 2025

 

  • A comparative assessment of multi-view fusion learning for crop classification – F Mena, D Arenas, M Nuske, A Dengel – 2023

 

  • Self-supervised Bernoulli autoencoders for semi-supervised hashing – R Ñanculef, F Mena, A Macaluso, S Lodi, C Sartori – 2021

 

  • Impact assessment of missing data in model predictions for Earth observation applications – F Mena, D Arenas, M Charfuelan, M Nuske, A Dengel – 2024

 

  • Increasing the robustness of model predictions to missing sensors in Earth observation – F Mena, D Arenas, A Dengel – 2024

 

🧩 Conclusion

Driven by curiosity and innovation, Francisco Mena is reshaping the landscape of machine learning through his pursuit of generalizable, efficient, and human-independent models. His research not only addresses technical limitations but also responds to the growing need for AI systems that are adaptable across domains and disciplines. With a solid academic background, global collaborations, and a clear research vision, he is set to make lasting contributions to unsupervised learning and its applications in critical areas like Earth observation and neural information retrieval. As he continues to build on his expertise, his work promises to influence both the academic world and the practical deployment of intelligent systems in complex, real-world scenarios.

Rasoul Sabetahd | Systems Neuroscience | Best Researcher Award

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Dr. Rasoul Sabetahd | Systems Neuroscience | Best Researcher Award

Dr. Rasoul Sabetahd, Islamic Azad University, Iran.

Dr. Rasoul Sabetahd, a distinguished civil engineer and academic, has dedicated his career to advancing the field of civil engineering through teaching, research, and practical contributions. As a faculty member at the Department of Civil Engineering, Sofian Branch, Islamic Azad University, Iran, he has played a transformative role in fostering innovation, mentoring future engineers, and addressing the pressing challenges of modern infrastructure. His work, rooted in sustainability and resilience, has left a profound impact on academia and the engineering industry alike.

 

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🌱 Early Academic Pursuits

Dr. Rasoul Sabetahd embarked on his academic journey with an enduring passion for civil engineering. He pursued his foundational studies in this field, demonstrating exceptional aptitude and dedication. His formative years were marked by a deep curiosity about structural systems and an eagerness to contribute to the advancement of infrastructure development. These early academic experiences laid the groundwork for his future scholarly achievements.

🏗️ Professional Endeavors

As a prominent member of the Department of Civil Engineering at the Sofian Branch of Islamic Azad University, Iran, Dr. Sabetahd has played a pivotal role in shaping the academic and professional landscape of civil engineering. His career is characterized by a commitment to teaching, mentoring, and equipping students with the practical and theoretical knowledge necessary for addressing modern engineering challenges. He has also collaborated with industry professionals to bridge the gap between academia and practical applications.

📚 Contributions and Research Focus

Dr. Sabetahd’s research has focused on groundbreaking advancements in civil engineering, including sustainable construction techniques, innovative materials, and structural resilience. Through meticulous studies and publications, he has enriched the academic discourse in civil engineering, providing valuable insights that have been widely acknowledged by peers. His work is deeply rooted in addressing contemporary engineering challenges, contributing significantly to the betterment of urban development and infrastructure planning.

🏆 Accolades and Recognition

Dr. Sabetahd’s dedication and expertise have earned him numerous accolades in the field of civil engineering. His research contributions and commitment to education have been recognized at national and international levels, bringing prestige to his institution and inspiring his colleagues and students. These honors reflect his influence as a leader in his domain.

🌍 Impact and Influence

The impact of Dr. Sabetahd’s work extends far beyond academia. His innovations and methodologies have been adopted in various real-world projects, demonstrating their practical value. As a mentor and educator, he has shaped the careers of countless students who now contribute to the field globally. His ability to blend research with practical applications has solidified his reputation as a transformative figure in civil engineering.

🔗 Legacy and Future Contributions

Dr. Sabetahd’s legacy is defined by his unwavering dedication to advancing civil engineering. Looking ahead, he aims to continue contributing to the field through innovative research, fostering new talent, and promoting sustainable engineering practices. His vision for the future involves not only addressing current challenges but also anticipating the needs of future generations.This biography celebrates the remarkable journey of Dr. Rasoul Sabetahd, highlighting his contributions and the lasting impact he has made in civil engineering.

📚 Publications

  1. Development of an Adaptive Chaotic Fuzzy Neural Network Controller for Mitigating Seismic Response in a Structure Equipped with an Active Tuned Mass Damper
    • Authors: Rasoul Sabetahd, Ommegolsoum Jafarzadeh
    • Year: 2025

 

  1. A Multiple Model Type-3 Fuzzy Control for Offshore Wind Turbines Using the Active Rotary Inertia Driver (ARID)
    • Authors: Chunwei Zhang, Meihua Liu, Zhihu Liu, Rasoul Sabetahd, Hamid Taghavifar, Ardashir Mohammadzadeh
    • Year: 2024

 

  1. Design of a Novel Intelligent Adaptive Fractional-Order Proportional-Integral-Derivative Controller for Mitigation of Seismic Vibrations of a Building Equipped with an Active Tuned Mass Damper
    • Authors: Ommegolsoum Jafarzadeh, Rasoul Sabetahd, Seyyed Arash Mousavi Ghasemi, Seyed Mehdi Zahrai
    • Year: 2024

 

  1. Design of an Online Adaptive Fractional-Order Proportional-Integral-Derivative Controller to Reduce the Seismic Response of the 20-Story Benchmark Building Equipped with an Active Control System
    • Authors: Ommegolsoum Jafarzadeh, Seyyed Arash Mousavi Ghasemi, Seyed Mehdi Zahrai, Rasoul Sabetahd, Ardashir Mohammadzadeh, Ramin Vafaei Poursorkhabi, Vasudevan Rajamohan
    • Year: 2024

 

  1. Response Attenuation of a Structure Equipped with ATMD under Seismic Excitations Using Methods of Online Simple Adaptive Controller and Online Adaptive Type-2 Neural-Fuzzy Controller
    • Authors: Rasoul Sabetahd, Seyed Arash Mousavi Ghasemi, Ramin Vafaei Poursorkhabi, Ardashir Mohammadzadeh, Yousef Zandi
    • Year: 2022

 

  1. Evaluation of Pall Friction Damper Performance in Near-Fault Earthquakes by Using Nonlinear Time History Analysis
    • Authors: Jafarzadeh, K., Lotfollahi-Yaghin, M.A., Sabetahd, R.
    • Year: 2012

 

Conclusion

Dr. Sabetahd’s journey exemplifies the fusion of academic excellence, professional dedication, and impactful research. Through his efforts, he has not only contributed to the growth of civil engineering but also inspired a new generation of engineers to pursue excellence. His legacy, defined by a commitment to progress and innovation, ensures his enduring influence in the field. As he continues his work, Dr. Sabetahd remains a beacon of inspiration, shaping the future of civil engineering.

 

 

Karim Abbasian | Functional Brain Connectivity | Excellence in Research

Published on by Neuroscientists

Assist Prof Dr.Karim Abbasian | Functional Brain Connectivity | Excellence in Research

Assist Prof Dr. Karim Abbasian University of Tabriz Iran

Dr. Karim Abbasian is an Associate Professor at the University of Tabriz, specializing in optical systems, quantum electronics, and nanophotonics. With a PhD in Optical Integrated Circuit Design, he has over 55 peer-reviewed publications and extensive teaching experience in advanced topics like Quantum Optics and Nanotechnology. His research focuses on all-optical systems, solar cells, and biosensors. Dr. Abbasian has held key administrative roles, including Rector of University of Bonab, and has been recognized for his contributions to research and teaching. His work is instrumental in advancing optical and quantum technologies for future applications.

profile

google scholar

Academic Position

Current Role: Associate Professor, Faculty of Electrical & Computer Engineering, University of Tabriz

Educational Background

Ph.D. in Optical Integrated Circuit Design from University of Tabriz, 2008Thesis: Electromagnetically Induced Transparency (EIT) for Realization of All-Optical Systems.M.Sc. in Electronic Engineering, University of Tarbiat Modarres, 1997.Thesis: On-Line Recognition of Handwritten Farsi Characters.B.Sc. in Electronic Engineering, University of Urumieh, 1994.

Teaching Experience

Courses taught at undergraduate, master’s, and PhD levels include:Magnetic Resonance Imaging (MRI), NanoPhotonics, Quantum Electronics, NanoElectronics, BioElectromagnetics, Quantum Optics, and more.

Research Interests

All-Optical Systems and Devices.Plasmonic and Nanophotonic Systems.Quantum Computing, Semiconductor Nanocrystals.Solar Cell Design, Optical Biosensors.Electromagnetic Fields in Tissue Engineering.Quantum Electronics, Quantum Cellular Automata.

Administrative Roles

Rector, University of Bonab (2017-2019).Dean, Faculty at University of Bonab (2002-2005).Vice Dean at University of Tabriz and University of Bonab (1999-2005).

Honors & Awards

Distinguished Researcher at University of Tabriz (2009, 2011, 2014).Distinguished Teacher at University of Tabriz (2010)Multiple employment grades for research and management excellence (2011, 2019)

📚 Publications

  • Ultra-fast all-optical plasmonic switching in near infra-red spectrum using a Kerr nonlinear ring resonator
    T. Nurmohammadi, K. Abbasian, R. Yadipour
    Optics Communications, 2018

 

  • All-optical analog-to-digital converter based on Kerr effect in photonic crystal
    D. Jafari, T. Nurmohammadi, M.J. Asadi, K. Abbasian
    Optics & Laser Technology, 2018

 

  • A proposal for a demultiplexer based on plasmonic metal–insulator–metal waveguide-coupled ring resonator operating in near-infrared spectrum
    T. Nurmohammadi, K. Abbasian, R. Yadipour
    Optik, 2017

 

  • Long wavelength infrared photodetector design based on electromagnetically induced transparency
    M. Zyaei, H.R. Saghai, K. Abbasian, A. Rostami
    Optics Communications, 2008

 

  • Low voltage, high modulation depth graphene THz modulator employing Fabry–Perot resonance in a metal/dielectric/graphene sandwich structure
    B. Jafari, H. Soofi, K. Abbasian
    Optics Communications, 2020

 

  • Modeling and analysis of room-temperature silicon quantum dot-based single-electron transistor logic gates
    M. Miralaie, M. Leilaeioun, K. Abbasian, M. Hasani
    Journal of Computational and Theoretical Nanoscience, 2014

 

  • Ultra-fast all-optical plasmon induced transparency in a metal–insulator–metal waveguide containing two Kerr nonlinear ring resonators
    T. Nurmohammadi, K. Abbasian, R. Yadipour
    Journal of Optics, 2018

 

  • Efficiency optimization in a rainbow quantum dot Solar cell
    A. Rostami, K. Abbasian, N. Gorji
    International Journal on Technical and Physical Problems of Engineering, 2011

 

  • A novel proposal for ultra-high resolution and compact optical displacement sensor based on electromagnetically induced transparency in ring resonator
    R. Yadipour, K. Abbasian, A. Rostami, Z. Koozekanani
    Progress In Electromagnetics Research, 2007

 

  • Analytical modeling of quality factor for shell type microsphere resonators
    R. Talebi, K. Abbasian, A. Rostami
    Progress In Electromagnetics Research B, 2011

 

  • All-optical tunable mirror design using electromagnetically induced transparency
    K. Abbasian, A. Rostami, Z. Koozekanani
    Progress In Electromagnetics Research M, 2008

 

  • A three-core hybrid plasmonic polarization splitter designing based on the hybrid plasmonic waveguide for utilizing in optical integrated circuits
    L. Shirafkan Dizaj, K. Abbasian, T. Nurmohammadi
    Plasmonics, 2020

Conclusion

Dr. Karim Abbasian’s extensive academic and research career highlights his significant contributions to the fields of optics, photonics, and nanotechnology. His leadership roles and innovative research on all-optical systems, solar cells, and biosensors underscore his commitment to advancing both theoretical knowledge and practical applications. His achievements, including numerous publications and teaching excellence, place him as a prominent figure in the scientific community. Dr. Abbasian’s work continues to shape the future of optical and quantum technologies, driving progress in critical areas that have wide-reaching implications for science and industry.