Abdullah Alghamdi | Emerging Areas in Neuroscience | Best Researcher Award

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Mr. Abdullah Alghamdi | Emerging Areas in Neuroscience | Best Researcher Award

Mr. Abdullah Alghamdi, University of Birmingham (UK) and Taibah University (Saudi Arabia),  United Kingdom.

Eng. Abdullah A. Zohaid (SMIEEE, SMIET) is an accomplished electrical engineer and academic with a specialization in Smart Power Systems, focusing on electric vehicles, AI-integrated transportation systems, and sustainable smart city infrastructure. With a solid educational foundation—earning distinctions at every academic level—he has seamlessly merged academic excellence with real-world engineering experience. From his early career at Saudi Aramco to his dual lecturing roles at Taibah University and the University of Birmingham, Abdullah has built a reputation as a forward-thinking researcher, educator, and strategist. His work bridges technical innovation with societal needs, aiming to optimize power grids and energy systems for a sustainable future.

Profile

Google Scholar

🎓 Early Academic Pursuits

From the historic city of Medina, Saudi Arabia, Eng. Abdullah A. Zohaid embarked on his academic journey in Electrical Engineering at Taibah University, where his talent and determination earned him distinction in his final project. His academic passion soon carried him to the United Kingdom, where he pursued an MSc in Electrical Power Systems at the University of Birmingham, graduating with First-Class Honors and distinction. Abdullah’s unwavering commitment to academic excellence continued as he embarked on a Ph.D. in Smart Power Systems at the same institution. Excelling in all areas, he has distinguished himself through both research prowess and scholastic achievement.

⚡ Professional Endeavors

Eng. Alghamdi has established himself as a dynamic professional straddling the worlds of academia and industry. His journey began with Saudi Aramco’s Dodsal Company, contributing to the vital 56″ Gas Pipeline project as an assistant electrical engineer. He transitioned into academia with his role as a Lecturer at Taibah University in Yanbu and later joined the University of Birmingham as a faculty member. Balancing dual academic roles in Saudi Arabia and the UK, Abdullah has developed a unique global perspective, blending practical engineering insight with cutting-edge educational delivery. His presence as an educator underscores his belief in empowering future engineers with real-world readiness.

🔬 Contributions and Research Focus

A scholar deeply embedded in the future of sustainable power, Eng. Alghamdi’s research focuses on Smart Power Systems, electric vehicles, smart charging infrastructures, and the integration of AI in intelligent transportation systems. Through his ongoing Ph.D. research, he explores how emerging technologies can enhance smart grid resilience and contribute to the development of smart cities. He utilizes advanced simulation and optimization tools such as MATLAB/SIMULINK, Python, and Gurobi, combined with machine learning techniques (ANN/CNN), to propose innovative solutions that address pressing energy challenges. His passion for sustainability is evident in his contributions to the global energy discourse, especially in urban mobility and decarbonization.

🏆 Accolades and Recognition

Eng. Zohaid’s career is adorned with recognition and academic milestones. His consistent distinction in every academic phase, including honors during both his MSc and Ph.D. studies, reflects a sustained trajectory of excellence. As a senior member of prestigious engineering bodies like IEEE and IET, and a certified Professional Engineer by the Saudi Council of Engineers, his credentials are a testament to his standing in the professional community. Furthermore, his publications in Q1 journals and contributions to leading international conferences validate the depth of his research and the quality of his scholarly communication.

🌍 Impact and Influence

With affiliations across IEEE working groups and university research circles, Eng. Alghamdi’s influence spans global academic and professional spheres. As a presenter and contributor at numerous high-level conferences — from the IEEE Power & Energy Society to Net Zero Futures and Saudi Innovation events — he has played a key role in shaping conversations on smart energy. His multidisciplinary expertise allows him to drive collaborations across AI, optimization, and power systems, impacting both policy and practice. His ability to simplify complex engineering concepts and communicate them effectively has enabled him to become a trusted voice among peers and students alike.

💡 Innovation and Strategic Vision

Abdullah’s strength lies in visionary thinking and strategic problem-solving. He doesn’t merely research problems—he crafts systems and strategies that reflect future-forward thinking. His approach to sustainable urban infrastructure blends technological acumen with strategic planning, leadership, and innovation. As an educator and researcher, he fosters environments that promote critical thinking and team-based innovation, cultivating the next generation of engineers equipped to face tomorrow’s challenges. His work on smart charging and intelligent transportation embodies the essence of transformative impact through design thinking and systems innovation.

🚀 Legacy and Future Contributions

Looking ahead, Eng. Abdullah A. Zohaid is poised to leave a lasting legacy in the realm of smart power systems and urban sustainability. His dual role as a lecturer and researcher gives him a powerful platform to shape both academic knowledge and real-world applications. With his continued focus on electrification, smart mobility, and AI-driven infrastructure, he is on track to influence policy, inspire innovation, and expand the boundaries of what is possible in modern power systems. His legacy will be defined not only by the technologies he helps build but also by the students and professionals he inspires along the way.

Publication

  • Innovative Prepositioning and Dispatching Schemes of Electric Vehicles for Smart Distribution Network Resiliency and Restoration
    AAM Alghamdi, D. Jayaweera, 2022

 

  • Resilience of Modern Power Distribution Networks with Active Coordination of EVs and Smart Restoration
    AAM Alghamdi, D. Jayaweera, 2023

 

  • Modelling Frameworks Applied in Smart Distribution Network Resiliency and Restoration
    AAM Alghamdi, D. Jayaweera, 2022

 

  • Resilience-Oriented Restoration in Modern Power Distribution Networks with Smart Electric Vehicles Coordination Framework
    A. Alghamdi, D. Jayaweera, 2023

 

  • Risk and Resilience Based Residential Electric Vehicle Integration Framework for Restoration of Modern Power Distribution Networks
    A. Alghamdi, D. Jayaweera, 2025

 

  • Electric Boats and Electric Vehicles Data-Driven Approach for Enhanced Resilience in Power Distribution Networks
    AAM Alghamdi, D. Jayaweera, 2025

 

✅ Conclusion

Eng. Alghamdi stands at the forefront of energy transformation, using research, innovation, and teaching as tools to drive meaningful change. His contributions reflect a blend of technical mastery and visionary leadership, enabling progress in smart mobility, clean energy, and intelligent infrastructure. With a growing portfolio of Q1 publications, prestigious memberships, and impactful conference roles, he continues to influence the field of electrical engineering on a global scale. As he advances in his career, his legacy will be marked by both technological advancements and the future minds he mentors—solidifying his role as a transformative figure in the evolution of smart power systems.

VIKRAM SINGH KARDAM | Neuroinformatics | Best Researcher Award

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Mr. VIKRAM SINGH KARDAM | Neuroinformatics | Best Researcher Award

Mr. VIKRAM SINGH KARDAM, DTU DELHI, India.

Vikram Singh Kardam is a dedicated researcher and academician specializing in signal processing, currently pursuing his Ph.D. at Delhi Technological University (DTU). With a strong educational foundation, including an M.Tech in Signal Processing and Digital Design, and a B.Tech in Electronics and Communication Engineering, he has consistently demonstrated academic excellence. Vikram has diverse professional experience, having worked both in industry and academia, including roles as a Project Engineer and Assistant Professor. His innovative M.Tech thesis on real-time iris recognition highlights his ability to apply advanced concepts to practical challenges in biometric security. Proficient in multiple programming languages and known for his problem-solving attitude, he blends technical skill with teaching acumen, influencing students and peers alike. His GATE rank and contributions to student development further underscore his commitment to excellence in engineering and education.

Profile

Scopus

 

🎓 Early Academic Pursuits

Vikram Singh Kardam’s academic journey began with a solid foundation in science and technology. He completed his 10th and 12th education from Government Inter College, Agra, achieving commendable marks that laid the groundwork for his future in engineering. His higher education commenced at the University Institute of Engineering and Technology, CSJM University, Kanpur, where he earned his Bachelor of Technology in Electronics and Communication Engineering in 2007 with a respectable score of 73.2%. Driven by a passion for advanced studies, he pursued a Master of Technology in Signal Processing and Digital Design from Delhi Technological University (DTU), securing a CGPA of 8.06 in 2017. His academic path reflects not only consistent effort but also a dedication to the field of signal processing.

🧑‍🏫 Professional Endeavors

Vikram embarked on his professional career with diverse roles that bridged academia and industry. He served as a Project Engineer at ITI Limited, Delhi, and as a Lab Engineer at Dayalbagh Engineering College, Agra, gaining hands-on experience in real-world engineering environments. His passion for teaching led him to academia, where he worked as an Assistant Professor in reputed institutions such as Galgotias College of Engineering and Technology, Greater Noida, and HMR Institute of Technology and Management, Delhi. With around three years of cumulative teaching experience, he has imparted theoretical knowledge and practical insights in Electronics and Communication Engineering, contributing to the academic development of numerous students.

🔬 Contributions and Research Focus

Currently pursuing his Ph.D. in Signal Processing at Delhi Technological University, Vikram Singh Kardam’s research delves into the intricacies of digital signal processing with real-world applications. His M.Tech thesis, titled “Real Time Iris Recognition”, showcases his innovation in biometric security systems. By integrating iris recognition with eye-blinking detection using a basic webcam, he proposed a novel, low-cost, and more secure method for identity verification. The system’s robustness and its resistance to hacking highlight his ability to merge theoretical concepts with practical utility. His fluency in programming languages such as MATLAB, C, C++, and Python3 supports his technical versatility in algorithm development and simulation.

🏅 Accolades and Recognition

A noteworthy milestone in Vikram’s academic journey is securing an All India Rank of 5334 in the GATE 2021 examination in Electronics and Communication Engineering. This national-level achievement is a testament to his strong grasp of core concepts and problem-solving acumen. Additionally, his academic performances during B.Tech and M.Tech reflect sustained excellence. His thesis project, recognized for its practical application and innovative approach, further enhances his academic reputation.

📚 Impact and Influence

In his role as an Assistant Professor, Vikram Singh Kardam has significantly influenced his students’ academic and professional growth. His commitment to regularly conducting lectures, his focus on ensuring student understanding, and his hands-on approach to lab sessions highlight his dedication to holistic teaching. Beyond knowledge delivery, his empathetic and analytical mindset enables him to mentor students, offer academic guidance, and solve problems effectively. His ability to integrate teaching with research creates an inspiring learning environment.

🌐 Legacy and Future Contributions

Looking forward, Vikram aspires to contribute to both academia and industry through innovative research in signal processing, embedded systems, and biometric technology. His current Ph.D. pursuits are expected to yield impactful contributions to the scientific community, particularly in the areas of real-time data analysis and secure identification systems. With a forward-thinking vision, he aims to blend educational excellence with technological advancement, fostering a new generation of engineers equipped with both critical thinking and creative problem-solving skills.

🧠 Vision and Intellect

At the core of Vikram Singh Kardam’s career is a mindset defined by curiosity, dedication, and the pursuit of knowledge. A quick learner and an effective communicator, he embodies the spirit of modern engineering – adaptive, analytical, and collaborative. His ability to learn and implement complex systems, along with his respect for students and colleagues, reflects not just technical competence but also emotional intelligence. As a lifelong learner and educator, he is poised to make enduring contributions in signal processing and beyond.

Publication

  • Title: BSPKTM-SIFE-WST: Bispectrum based channel selection using set-based-integer-coded fuzzy granular evolutionary algorithm and wavelet scattering transform for motor imagery EEG classification

  • Authors: V.S. Kardam, S. Taran, A. Pandey

  • Year: 2025

 

 

✅ Conclusion

Vikram Singh Kardam stands out as a promising scholar and educator in the field of signal processing. His journey reflects a balance of theoretical rigor, practical implementation, and a passion for continuous learning. With a future-oriented mindset, he is poised to make meaningful contributions to biometric systems, digital design, and the broader engineering community. As he advances through his doctoral research and professional engagements, Vikram’s legacy is one of innovation, dedication, and impactful mentorship in the evolving landscape of technology and education.

Che Ping Cheng | Translational Neuroscience | Best Researcher Award

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Prof. Che Ping Cheng | Translational Neuroscience | Best Researcher Award

Prof. Che Ping Cheng, Wake Forest University School of Medicine, United States.

Dr. Che Ping Cheng, M.D., Ph.D., FAHA, is a distinguished cardiovascular physiologist and internal medicine specialist whose career has been dedicated to advancing the understanding of heart function and failure. From earning his medical degree in China to completing a Ph.D. in Physiology at Wayne State University, and later conducting pivotal postdoctoral research at Wake Forest School of Medicine, Dr. Cheng has consistently pursued excellence in science and education. His research on ventricular mechanics, volume loading, and heart failure has significantly influenced both experimental cardiology and clinical practice. Recognized as a Fellow of the American Heart Association, he is also a dedicated mentor, shaping the next generation of cardiovascular researchers through his academic leadership.

Profile

Scopus

 

🎓 Early Academic Pursuits

Dr. Che Ping Cheng’s journey into medicine and science began in Nanjing, China, where he earned his M.D. degree from Nanjing Railway Medical University in 1977. His early academic path reflected a deep interest in understanding the intricacies of human health, particularly in cardiovascular physiology. Driven by a desire to expand his knowledge and research capabilities, Dr. Cheng pursued his Ph.D. in Physiology at Wayne State University School of Medicine in Detroit, Michigan, completing his degree in 1986. Under the mentorship of Dr. Robert S. Shepard, his doctoral work focused on exploring the mechanisms of cardiovascular response to volume loading in a canine model with tricuspid valvulectomy, setting a strong foundation for his lifelong focus on heart function and disease mechanisms.

🩺 Professional Endeavors

Following his academic training, Dr. Cheng embarked on postdoctoral studies at the Bowman Gray School of Medicine (now part of Wake Forest School of Medicine), where he continued to cultivate his expertise in internal medicine and cardiovascular physiology. Between 1986 and 1988, he served as a Postdoctoral Fellow under the guidance of Dr. William C. Little. His research during this period focused on ventricular dynamics and the physiological factors affecting active ventricular filling, which would later inform his broader work on heart failure and cardiac function. Dr. Cheng has since remained at Wake Forest School of Medicine, where he is currently a distinguished member of the Section on Cardiovascular Medicine.

🧪 Contributions and Research Focus

Dr. Cheng’s career has been characterized by a deep commitment to advancing the understanding of cardiac hemodynamics, ventricular interaction, and heart failure mechanisms. His research has explored how ventricular function responds under altered physiological states, and how these responses inform disease progression and treatment strategies. His early animal model studies have provided critical insights into the interplay between structural and functional changes in the heart, especially in the context of diastolic dysfunction and volume overload conditions. Dr. Cheng has also made significant strides in translating these findings to clinical contexts, influencing how cardiologists approach diagnosis and therapy.

🏅 Accolades and Recognition

Throughout his career, Dr. Cheng has received considerable recognition for his scholarly contributions. He is a Fellow of the American Heart Association (FAHA), an honor that reflects his standing in the field of cardiovascular research and his commitment to scientific excellence. His work has earned the respect of colleagues and institutions alike, leading to numerous invitations to contribute to collaborative projects, serve on peer-review panels, and mentor future generations of cardiovascular researchers.

🌍 Impact and Influence

Dr. Cheng’s work has had a lasting impact on both experimental and clinical cardiology. By elucidating the mechanistic basis of ventricular dysfunction, he has helped shift paradigms in heart failure management, particularly in the areas of ventricular interdependence and preload responsiveness. His research findings are frequently cited in textbooks and high-impact journals, and they continue to inform guidelines for cardiac care and interventions. Through his work at Wake Forest and beyond, Dr. Cheng has played a pivotal role in bridging laboratory discoveries with bedside applications.

👨‍🏫 Legacy and Mentorship

As a respected mentor and educator, Dr. Cheng has dedicated a significant portion of his career to training medical students, residents, and postdoctoral fellows. His mentorship has influenced numerous emerging scholars in cardiovascular medicine, many of whom have gone on to successful academic and clinical careers. His guidance combines a rigorous scientific approach with a deep sense of responsibility to patient care and scientific integrity, shaping a legacy that extends well beyond his own research output.

🔬 Future Contributions and Vision

Looking ahead, Dr. Cheng remains committed to the advancement of cardiovascular research, with a continued focus on uncovering the cellular and mechanical determinants of heart disease. His vision includes fostering collaborative projects that integrate biomedical engineering, imaging, and computational modeling to further understand cardiac performance. With decades of experience and a forward-thinking approach, Dr. Cheng’s future contributions are poised to leave a lasting mark on the field of translational cardiovascular medicine.

Publication

  1. Title: Increased CaMKII activation and contrast changes of cardiac β1-and β3-Adrenergic signaling pathways in a humanized angiotensinogen model of hypertension
    Authors: Sun, Xiaoqiang; Cao, Jing; Chen, Zhe; Ferrario, Carlos M.; Cheng, Cheping
    Year: 2023
    Journal: Heliyon

 

  1. Title: Calmodulin-dependent protein kinase II activation promotes kidney mesangial expansion in streptozotocin-induced diabetic mice
    Authors: Mikhailov, Alexei V.; Liu, Yixi; Cheng, Hengjie; Lin, Jen Jar; Cheng, Cheping
    Year: 2022
    Journal: Heliyon

 

  1. Title: Chronic GPR30 agonist therapy causes restoration of normal cardiac functional performance in a male mouse model of progressive heart failure: Insights into cellular mechanisms
    Authors: Zhang, Xiaowei; Li, Tiankai; Cheng, Hengjie; Groban, Leanne; Cheng, Cheping
    Year: 2021
    Journal: Life Sciences

 

  1. Title: Chronic Ca2+/calmodulin-dependent protein Kinase II inhibition rescues advanced heart failure
    Authors: Liu, Yixi; Shao, Qun; Cheng, Hengjie; Zhao, David Xiao Ming; Cheng, Cheping
    Year: 2021
    Journal: Journal of Pharmacology and Experimental Therapeutics

 

  1. Title: The Angiotensin-(1–12)/Chymase axis as an alternate component of the tissue renin angiotensin system
    Authors: Ferrario, Carlos M.; Groban, Leanne; Wang, Hao; Sun, Xuming; Ahmad, Sarfaraz
    Year: 2021
    Journal: Molecular and Cellular Endocrinology

 

  1. Title: Reversal of angiotensin-(1–12)-caused positive modulation on left ventricular contractile performance in heart failure: Assessment by pressure-volume analysis
    Authors: Li, Tiankai; Zhang, Zhi; Zhang, Xiaowei; Ferrario, Carlos M.; Cheng, Cheping
    Year: 2020
    Journal: International Journal of Cardiology

 

  1. Title: Female Heart Health: Is GPER the Missing Link?
    Authors: Groban, Leanne; Tran, Q. K.; Ferrario, Carlos M.; Wang, Hao; Lindsey, Sarah H.
    Year: (Not specified, but likely 2020 or 2021)
    Journal: (Not specified)

 

🏁 Conclusion

Dr. Cheng’s legacy is one of intellectual rigor, clinical relevance, and mentorship. His work has not only deepened the scientific understanding of cardiac physiology but has also shaped modern approaches to diagnosing and managing heart failure. With a career spanning continents and disciplines, Dr. Cheng continues to be a guiding force in cardiovascular medicine, and his future contributions are anticipated to further advance the frontiers of heart research and patient care.

 

Jun Liu | Neuroimaging | Best Researcher Award

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Prof.Dr. Jun Liu | Neuroimaging | Best Researcher Award

Prof. Dr. Jun Liu,  Department of Radiology, Second Xiangya Hospital of Central South University, China.

Professor Jun Liu is a highly accomplished radiologist and academic leader, serving as the Chief Radiologist and Director of the Radiology Department at the Second Xiangya Hospital, Central South University. With a strong foundation in medical sciences and an early passion for radiology, he has emerged as a national figure in neuroimaging and neuroregeneration research. His professional journey is marked by impactful roles in academic mentorship, hospital administration, and national medical organizations. His research excellence is evident through his leadership in multiple prestigious committees and his contributions to scientific review and innovation. Recognized by both government and medical associations, Professor Liu is a decorated figure, celebrated for his medical service during COVID-19 and his scientific leadership in Hunan Province and beyond.

Profile

Orcid 

Scopus

 

Professor Jun Liu is a highly accomplished radiologist and academic leader, serving as the Chief Radiologist and Director of the Radiology Department at the Second Xiangya Hospital, Central South University. With a strong foundation in medical sciences and an early passion for radiology, he has emerged as a national figure in neuroimaging and neuroregeneration research. His professional journey is marked by impactful roles in academic mentorship, hospital administration, and national medical organizations. His research excellence is evident through his leadership in multiple prestigious committees and his contributions to scientific review and innovation. Recognized by both government and medical associations, Professor Liu is a decorated figure, celebrated for his medical service during COVID-19 and his scientific leadership in Hunan Province and beyond.

Profile

Orcid
Scopus

 

🎓 Early Academic Pursuits


From the very beginning of his academic journey, Professor Jun Liu demonstrated exceptional dedication to the medical sciences. He earned his M.D. and laid a solid foundation in radiology, developing a keen interest in diagnostic imaging and neurological disorders. His academic commitment and intellectual curiosity propelled him toward advanced studies and laid the groundwork for a distinguished career in radiology. As a student and early-career academic, he was recognized for his strong analytical skills and leadership potential, setting the stage for the impactful roles he would later assume in both clinical and academic spheres.

🏥 Professional Endeavors


Professor Jun Liu currently serves as the Chief Radiologist and Director of the Radiology Department at the prestigious Second Xiangya Hospital of Central South University. In this role, he oversees cutting-edge radiological practices while also guiding clinical decision-making with expertise and precision. As a Doctoral Supervisor and Professor, he mentors a new generation of radiologists, integrating academic knowledge with clinical excellence. His influence also extends into organizational leadership as the Secretary of the First Party Branch, showcasing his commitment to institutional development and medical governance.

🔬 Contributions and Research Focus


A pivotal force in radiology, Professor Liu has devoted much of his research to neuroimaging and neuroregeneration. His work as the headman of the Neuroregeneration and Neuroimaging Group under the Chinese Research Hospital Association reflects his influence in shaping national research priorities. As a peer review expert for the National Natural Science Foundation of China, he contributes to the advancement of scientific standards and research integrity. His projects often intersect clinical imaging with neuroscience, allowing for better diagnosis and understanding of neurological diseases.

🏅 Accolades and Recognition


Professor Liu’s contributions have earned him numerous national honors. Notably, he was awarded the Advanced Individual against COVID-19 by the Ministry of Science and Technology of the People’s Republic of China, acknowledging his dedication during a critical period in global health. He received the Outstanding Style Award at the 5th People’s Famous Doctor Ceremony, and has been recognized as a leading talent in the Science and Technology Innovation Program of Hunan Province. His role as leader of 225 subjects in the province showcases his broad expertise and leadership in medical research and education.

🌐 Impact and Influence


Nationally, Professor Liu plays a vital role in shaping radiological standards and neurology practices. As a member of the Neurology Group under the Chinese Society of Radiology and the Chinese Medical Association, his insights influence nationwide healthcare policies and training programs. In Hunan, he is the Director of the Diagnostic Radiology Quality Control Center and President of the Radiologists Branch of the Hunan Medical Doctor Association, where he continues to elevate diagnostic standards and ensure quality in radiological services.

🚀 Innovation and Leadership


Professor Liu stands as a prime example of a “Double Leaders” Party Branch Secretary, a title awarded by the Ministry of Education, symbolizing excellence in both administrative and academic leadership. His involvement in technology-driven projects, particularly those that integrate AI and neuroimaging, highlights his forward-thinking approach to medical diagnostics. He champions the evolution of radiology into a more dynamic and precision-focused discipline, blending traditional expertise with technological innovations.

📘 Legacy and Future Contributions


As Professor Liu continues to mentor doctoral candidates and lead national research groups, his legacy is already visible in the improved radiological practices across China. His work in neuroregeneration and imaging not only enhances clinical outcomes but also pushes the boundaries of what medical imaging can achieve. In the years to come, his continued dedication to education, research, and innovation will undoubtedly shape the future of radiology and contribute to better neurological healthcare nationwide and beyond.

Publication

  • Title: Insulinoma detection on low-dose pancreatic CT perfusion: comparing with conventional contrast-enhanced CT and MRI
    Authors: S. Luo, X. Mei, Y. Shang, … W. Yang, J. Liu
    Year: 2025

 

  • Title: Functions and application of circRNAs in vascular aging and aging-related vascular diseases
    Authors: S. He, B. Huang, F. Xu, … X. Lin, J. Liu
    Year: 2025

 

  • Title: Persistent alterations in gray matter in COVID-19 patients experiencing sleep disturbances: a 3-month longitudinal study
    Authors: K. Zhou, G. Duan, Y. Liu, … J. Yang, D. Deng
    Year: 2025

 

  • Title: Multimodal radiopathological integration for prognosis and prediction of adjuvant chemotherapy benefit in resectable lung adenocarcinoma: A multicentre study
    Authors: H. Lin, J. Hua, Z. Gong, … C. Lu, Z. Liu
    Year: 2025

 

  • Title: Prognostic and predictive values of a multimodal nomogram incorporating tumor and peritumor morphology with immune status in resectable lung adenocarcinoma
    Authors: H. Lin, J. Hua, Y. Wang, … J. Liu, Z. Liu
    Year: 2025

 

  • Title: White matter microstructural alterations are associated with cognitive decline in benzodiazepine use disorders: a multi-shell diffusion magnetic resonance imaging study
    Authors: M. Yi, T. Wang, X. Li, … J. Liu, H. Zhou
    Year: 2025

 

  • Title: Unveiling causal relationships between addiction phenotypes and inflammatory cytokines: insights from bidirectional mendelian randomization and bibliometric analysis
    Authors: S. Cao, L. Yang, X. Wang, … S. Tang, J. Liu
    Year: 2025

 

  • Title: Microstructure changes of the brain preceded glymphatic function changes in young obesity with and without food addiction
    Authors: M. Yi, Z. Yule, W. Song, … J. Liu, H. Zhou
    Year: 2025

 

  • Title: Distinct insula subdivisions of resting-state functional connectivity in individuals with opioid and methamphetamine use disorders
    Authors: W. Yang, X. Wen, Z. Du, … K. Yuan, J. Liu
    Year: 2025

 

  • Title: Unraveling the Diffusion MRI-Based Glymphatic System Alterations in Children with Rolandic Epilepsy
    Authors: Y. Yin, M. Ma, F. Wang, … J. Liu, H. Liu
    Year: 2025

 

✅ Conclusion


Professor Jun Liu’s career embodies the intersection of clinical expertise, scientific innovation, and compassionate leadership. Through decades of dedication, he has transformed radiological practice and training in China, especially in neurological diagnostics. As a scholar, mentor, and administrator, his legacy continues to inspire the next generation of medical professionals. With a focus on advancing neuroimaging techniques and quality standards, Professor Liu stands as a beacon of excellence in modern radiology, with his future contributions set to further shape the landscape of medical diagnostics and research.

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

Google Scholar
Scopus
Orcid

 

🎓 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.

Saba Hesaraki | Neurotechnology | Best Researcher Award

Posted on by Neuroscientists

Ms. Saba Hesaraki | Neurotechnology | Best Researcher Award

Ms. Saba Hesaraki,  Islamic Azad University science and research branch, Iran.

Saba Hesaraki is a computer engineer specializing in artificial intelligence (AI), particularly in medical imaging and generative AI. She holds a Master’s degree in Computer Engineering from Islamic Azad University, Science and Research Branch, Tehran, where her thesis focused on breast cancer image segmentation using an improved 3D U-Net++ model. She has a strong academic background with high GPAs in both her bachelor’s and master’s programs.

Profile

Google Scholar

🌱 Early Academic Pursuits

Saba Hesaraki embarked on her academic journey with a deep passion for computer engineering, earning her Bachelor of Science in Software Engineering from Islamic Azad University, West Tehran Branch. With an outstanding GPA of 17.22 out of 20.0, she demonstrated an early inclination toward problem-solving and artificial intelligence. Her intellectual curiosity and commitment to innovation led her to pursue a Master’s degree in the same domain at Islamic Azad University, Science and Research Branch, Tehran. Her thesis, titled “Segmentation of Breast Cancer Images Using Improved 3D U-Net++ Model,” under the supervision of Dr. Maryam Rastgarpour, showcases her dedication to advancing medical imaging technologies through AI-driven solutions. With an exceptional GPA of 18.12 out of 20.0, her academic excellence laid the foundation for a remarkable research career.

💼 Professional Endeavors

Saba’s professional journey reflects her deep expertise in artificial intelligence, particularly in the realms of generative AI and medical imaging. She has worked remotely in various esteemed organizations, contributing her skills to groundbreaking AI projects. Her role as a Generative AI Engineer at Care Vox in Mountain View, California, and Nexus in San Jose, California, enabled her to develop innovative AI-driven solutions. Prior to this, she made significant contributions as a Computer Vision Engineer at Koga Studio and the Quantitative MR Imaging and Spectroscopy Group in Tehran. Her engagement as an NLP Researcher at Asr Gooyesh Pardaz further showcases her versatility in the field of AI. Through these roles, she has gained profound experience in AI-based medical diagnostics, image segmentation, and sustainable AI development, paving the way for impactful innovations.

📚 Contributions and Research Focus

As a dedicated researcher, Saba’s work has revolved around the intersection of AI and healthcare, particularly medical image segmentation and generative AI applications. Her research interests extend to AI-driven personalized medicine and sustainable AI solutions. She has co-authored multiple research papers, including “Capsule Fusion for Extracting Psychiatric Stressors for Suicide from Twitter” and “UNet++ and LSTM Combined Approach for Breast Ultrasound Image Segmentation.” Her work reflects a keen interest in leveraging AI to solve complex medical challenges, from cancer detection to mental health analysis. Her research on classifying 3D point cloud objects using hybrid neural networks also highlights her multidisciplinary expertise.

🏆 Accolades and Recognition

Saba’s dedication to AI research has been recognized through her academic achievements and professional contributions. Her IELTS score of 7.5 and GRE score of 332 underscore her strong analytical and communication skills, essential for global collaboration in AI research. Her research papers have been under review and submission in reputable scientific journals, further solidifying her presence in the AI and medical imaging research community. The recognition she has garnered through collaborations and innovative contributions establishes her as an influential figure in AI-driven healthcare solutions.

🌍 Impact and Influence

Saba’s work extends beyond research, as she actively contributes to the global AI community by developing cutting-edge AI applications for real-world problems. Her role in AI for sustainable development and AI-driven personalized medicine signifies her commitment to leveraging technology for societal benefit. Her experience in deep learning frameworks like PyTorch and Keras, along with her expertise in machine learning algorithms, has allowed her to shape AI-driven healthcare innovations that have the potential to save lives and enhance medical diagnostics. Through collaborations and mentorship, she inspires the next generation of AI researchers to push the boundaries of technological advancements.

🚀 Legacy and Future Contributions

As an AI researcher and engineer, Saba continues to drive innovation in medical imaging and generative AI. Her aspirations include advancing AI methodologies for early disease detection, improving healthcare accessibility through AI-driven solutions, and fostering AI applications in sustainable development. Her ability to blend technical expertise with a deep understanding of healthcare challenges positions her as a leader in the field. With a promising future ahead, she remains dedicated to exploring new AI frontiers that will revolutionize medical imaging, AI ethics, and beyond.

Publication

Title: A Comprehensive Analysis on Machine Learning based Methods for Lung Cancer Level Classification
Authors: S. Farshchiha, S. Asoudeh, M.S. Kuhshuri, M. Eisaeid, M. Azadie, S. Hesaraki
Year: 2025

Title: Breast Cancer Ultrasound Image Segmentation Using Improved 3D Unet++
Authors: S. Hesaraki, A.S. Mohammed, M. Eisaei, R. Mousa
Year: 2025

Title: BERTCaps: BERT Capsule for Persian Multi-Domain Sentiment Analysis
Authors: M. Memari, S.M. Nejad, A.P. Rabiei, M. Eisaei, S. Hesaraki
Year: 2024

Title: UNet++ and LSTM Combined Approach for Breast Ultrasound Image Segmentation
Authors: S. Hesaraki, M. Akbari, R. Mousa
Year: 2024

Title: Classifying Objects in 3D Point Clouds Using Recurrent Neural Network: A GRU LSTM Hybrid Approach
Authors: R. Mousa, M. Khezli, M. Azadi, V. Nikoofard, S. Hesaraki
Year: 2024

Title: CapsF: Capsule Fusion for Extracting Psychiatric Stressors for Suicide from Twitter
Authors: M.A. Dadgostarnia, R. Mousa, S. Hesaraki
Year: 2024

Conclusion

Saba Hesaraki is a highly skilled and motivated AI engineer with a strong academic and research background in medical imaging and generative AI. Her experience across various AI-driven projects, coupled with technical expertise in deep learning and computer vision, positions her as a valuable contributor to the field. With multiple publications and collaborations in AI and machine learning, she continues to make significant advancements in healthcare applications using AI.