Rituraj Upadhyay | Healthcare Data Analysis | Best Researcher Award

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Dr. Rituraj Upadhyay | Healthcare Data Analysis | Best Researcher Award

The Ohio State University, United States

Author Profiles

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Early Academic Pursuits 🎓

Dr. Rituraj Upadhyay began his academic journey with a strong foundation in medical education at the prestigious All India Institute of Medical Sciences (AIIMS), New Delhi. There, he completed his Bachelor of Medicine and Surgery (MBBS) in 2014, followed by an MD in Radiation Oncology (2017). His early medical training was marked by a deep interest in radiotherapy and oncology, leading him to pursue a Diplomate of National Board (DNB) certification in Radiation Oncology. His academic endeavors during this time reflected a commitment to advancing medical knowledge and improving patient care through radiation oncology.

Professional Endeavors 🌍

Dr. Upadhyay’s professional career has been driven by a passion for advancing radiation oncology, particularly through his work in clinical and academic settings. His residency at The Ohio State University Wexner Medical Center (2021–2025) is a notable highlight in his professional journey, demonstrating his commitment to mastering the latest technologies and treatments in radiation oncology. Dr. Upadhyay’s time at renowned institutions like MD Anderson Cancer Center and Rutgers Cancer Institute of New Jersey has further solidified his standing as an emerging leader in the field. His pursuit of innovation and excellence is evident from his involvement in advanced radiation oncology fellowships and international research collaborations.

Contributions and Research Focus 🔬

Dr. Upadhyay’s research is at the forefront of radiation oncology, with a focus on improving treatment outcomes and minimizing side effects. He has contributed significantly to clinical trials and funded research, such as the “PRIMe-STAR trial” on progressive/recurrent intracranial meningiomas and the “AVATAR” system aimed at reducing anesthesia needs in pediatric radiotherapy. His research on stereotactic radiosurgery for brain metastases and radiation therapy for conditions like penile cancer and renal stereotactic ablative therapy underscores his diverse interests in cancer treatment. His studies have potential global impact, as reflected in his leadership role in multinational research endeavors.

Impact and Influence 🌟

Dr. Upadhyay’s influence extends beyond his research. As an educator and mentor, he actively shapes the next generation of radiation oncologists. His roles in mentoring medical students, residents, and fellows at institutions like The Ohio State University and Massachusetts General Hospital highlight his dedication to guiding aspiring professionals. He also plays a key role in enhancing the field through his involvement in various professional organizations such as the American Society for Radiation Oncology (ASTRO) and the Radiosurgery Society (RSS). His work as a guideline reviewer and committee member for several radiation oncology societies reflects his broad influence on the development of standards and best practices in the field.

Academic Cites 📚

Dr. Upadhyay’s research and academic work are well-regarded, with his contributions earning recognition through numerous awards and honors. Notable accolades include the American College of Radiation Oncology (ACRO) Best Abstract Award and the American Radium Society (ARS) Early Career Oncologist Award, which are testaments to his influential research on topics like stereotactic radiosurgery and palliative radiation therapy. These accolades further cement his reputation in the academic community, demonstrating the high regard in which his peers hold his research.

Technical Skills 💻

Dr. Upadhyay has developed a comprehensive set of technical skills that position him at the cutting edge of radiation oncology. His expertise spans advanced radiation therapy techniques such as stereotactic radiosurgery (SRS), stereotactic body radiotherapy (SBRT), proton therapy, and image-guided brachytherapy. In addition, he is well-versed in cutting-edge technologies, including the use of artificial intelligence and machine learning in radiation oncology for treatment planning and quality assurance. His technical acumen is further demonstrated by his involvement in developing new approaches to enhance clinical outcomes for complex cancer cases.

Teaching Experience 📖

Dr. Upadhyay has dedicated substantial time to teaching and mentorship, sharing his expertise with medical students, residents, and fellow researchers. He has served as a moderator for educational webinars and a mentor for various research initiatives. His roles as a panelist and speaker at international conferences, such as the ASTRO Annual Meeting and the Ohio State University Cardio-Oncology Symposium, reflect his commitment to advancing education within the field of oncology. Through these initiatives, he has played a key role in shaping the future of radiation oncology education.

Legacy and Future Contributions 🔮

Dr. Upadhyay’s legacy in radiation oncology is already being established through his groundbreaking research and mentorship. His involvement in international clinical trials, such as the AVATAR system and the PRIMe-STAR trial, is likely to make a long-lasting impact on the clinical management of cancer patients globally. Looking forward, Dr. Upadhyay plans to continue advancing his research, particularly in the areas of stereotactic radiosurgery and precision medicine. His work promises to significantly shape the future of radiation oncology, particularly in improving treatment efficacy, minimizing side effects, and enhancing patient care across diverse populations.

 

Top Noted Publications 📖

Additive Value of Magnetic Resonance Simulation Before Chemoradiation in Evaluating Treatment Response and Pseudoprogression in High-Grade Gliomas

Authors: Divya Yadav, Rituraj Upadhyay, Vinodh A. Kumar, Melissa M. Chen, Jason M. Johnson, Holly Langshaw, Brandon J. Curl, Maguy Farhat, Wasif Talpur, Thomas H. Beckham et al.

Journal: Practical Radiation Oncology

Year: 2024

Risk-Stratified Radiotherapy in Pediatric Cancer

Authors: Rituraj Upadhyay, Arnold C. Paulino

Journal: Cancers

Year: 2024

Disease Control and Toxicity Outcomes after Stereotactic Ablative Radiation Therapy for Recurrent and/or Metastatic Cancers in Young-Adult and Pediatric Patients

Authors: Rituraj Upadhyay, Brett Klamer, Jennifer Matsui, Vikram B. Chakravarthy, Thomas Scharschmidt, Nicholas Yeager, Bhuvana A. Setty, Timothy P. Cripe, Ryan D. Roberts, Jennifer H. Aldrink et al.

Journal: Cancers

Year: 2024

Quantifying the Risk and Dosimetric Variables of Symptomatic Brainstem Injury after Proton Beam Radiation in Pediatric Brain Tumors

Authors: Rituraj Upadhyay, Kaiping Liao, David R Grosshans, Susan L McGovern, Mary Frances McAleer, Wafik Zaky, Murali M Chintagumpala, Anita Mahajan, Debra Nana Yeboa, Arnold C Paulino

Journal: Neuro-Oncology

Year: 2022

Patterns of Failure after Radiation Therapy in Primary Spinal High-Grade Gliomas: A Single Institutional Analysis

Authors: Rituraj Upadhyay, Swapnil Khose, Halyna Pokhylevych, Arnold C Paulino, Mary Frances McAleer, Amol Ghia, Jing Li, Debra Nana Yeboa, Monica Loghin, Rebecca Harrison et al.

Journal: Neuro-Oncology Advances

Year: 2022

Wei Liang | Healthcare Data Analysis | Best Researcher Award

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Dr. Wei Liang | Healthcare Data Analysis | Best Researcher Award

Doctorate at East China University of Science and Technology, China

 Author Profile 👨‍🎓

Early Academic Pursuits 🎓

Dr. Wei Liang embarked on his academic journey at East China University of Science and Technology, where he earned his Bachelor’s degree in Engineering (B.E.) in 2020. His interest in Brain-Computer Interfaces (BCI) and Machine Learning became evident during his undergraduate studies, setting the stage for his continued academic success. Currently, he is pursuing his PhD at the same institution, delving deeper into the intersection of neuroscience, computer science, and biomedical engineering. His early education laid a strong foundation for his research in the emerging field of BCI technology.

Professional Endeavors 💼

As a PhD candidate, Wei Liang is already contributing to the rapidly evolving field of Brain-Computer Interfaces, particularly in motor imagery and neural signal processing. His research involves collaboration with prominent experts in the fields of computer science, neuroscience, and biomedical engineering, such as Andrzej Cichocki, Ian Daly, and Brendan Allison. Liang’s professional journey has been shaped by these collaborations, allowing him to gain insights from diverse disciplines, further honing his expertise in BCI.

Contributions and Research Focus 🧠

Wei Liang’s research focuses on advancing Brain-Computer Interface (BCI) technology, particularly in motor imagery and neural signal processing. His work has led to the development of SecNet, a second-order neural network designed to improve motor imagery decoding from electroencephalography (EEG) signals. Liang’s innovative approaches include variance-preserving spatial patterns for EEG signal processing and the use of graph convolutional networks for optimal channel selection. These contributions have enhanced the accuracy and reliability of BCI systems, making them more applicable to real-world scenarios such as stroke rehabilitation and neural engineering.

Impact and Influence 🌍

Wei Liang’s work is making significant strides in improving BCI systems, which have far-reaching applications in medicine, rehabilitation, and human-computer interaction. By optimizing EEG decoding strategies, his research could impact the development of more effective neuroprosthetics and assistive technologies for individuals with motor impairments. His collaboration with leading researchers from around the world further amplifies the global impact of his work, positioning him as a rising star in BCI research.

Academic Citations 📚

Despite being in the early stages of his career, Wei Liang has already made a notable impact on the academic community. His research has led to the publication of five papers, accumulating a total of 14 citations and an h-index of 2. Notable papers include works published in Information Processing & Management, Frontiers in Human Neuroscience, and IEEE Journal of Biomedical and Health Informatics, among others. These publications highlight his contributions to improving BCI systems and their applications.

Technical Skills 🛠️

Wei Liang possesses a strong technical skill set, particularly in the areas of machine learning, neural network architecture, and EEG signal processing. He has expertise in developing novel algorithms for motor imagery decoding, including the use of second-order neural networks and graph convolutional networks. Liang is proficient in various computational tools and programming languages necessary for his research, positioning him as an expert in his field.

Teaching Experience 🏫

Though primarily focused on research, Wei Liang’s academic journey has also included some teaching experience, collaborating with faculty and providing guidance to students. His strong academic background, coupled with his research expertise, allows him to mentor and inspire others in the field of Brain-Computer Interfaces.

Legacy and Future Contributions 🌟

Wei Liang’s research trajectory holds great promise for shaping the future of Brain-Computer Interface technology. His innovative methodologies have the potential to revolutionize how we understand and utilize EEG signals for communication and rehabilitation. In the long term, his contributions could lead to breakthroughs in neuroprosthetics, enhancing the quality of life for individuals with disabilities. With continued dedication and innovation, Liang is on track to leave a lasting legacy in the realm of neuroscience and technology.

Teaching and Mentorship 🧑‍🏫

Although Liang is primarily focused on research, his experiences collaborating with top researchers and participating in academia have enriched his teaching and mentorship skills. His ability to translate complex ideas into understandable concepts makes him an effective communicator, ready to guide the next generation of researchers in the field of BCI.

Awards and Recognition 🏆

Wei Liang has been recognized for his groundbreaking research, publishing in high-impact journals and earning accolades for his contributions to BCI technology. As a promising young researcher, he is poised to receive even greater recognition as his work continues to influence and shape the future of the field.

Top Noted Publications📖

Novel Channel Selection Model Based on Graph Convolutional Network for Motor Imagery
    • Authors: W Liang, J Jin, I Daly, H Sun, X Wang, A Cichocki
    • Journal: Cognitive Neurodynamics
    • Year: 2023
Variance Characteristic Preserving Common Spatial Pattern for Motor Imagery BCI
    • Authors: W Liang, J Jin, R Xu, X Wang, A Cichocki
    • Journal: Frontiers in Human Neuroscience
    • Year: 2023
SecNet: A Second Order Neural Network for MI-EEG
    • Authors: W Liang, BZ Allison, R Xu, X He, X Wang, A Cichocki, J Jin
    • Journal: Information Processing & Management
    • Year: 2025
Multiscale Spatial-Temporal Feature Fusion Neural Network for Motor Imagery Brain-Computer Interfaces
    • Authors: J Jin, W Chen, R Xu, W Liang, X Wu, X He, X Wang, A Cichocki
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Year: 2024
Leveraging Transfer Superposition Theory for StableState Visual Evoked Potential Cross-Subject Frequency Recognition
    • Authors: X He, BZ Allison, K Qin, W Liang, X Wang, A Cichocki, J Jin
    • Journal: IEEE Transactions on Biomedical Engineering
    • Year: 2024

Shuaa S. Alharbi | Bioimage informatics | Best Researcher Award

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Dr. Shuaa S. Alharbi | Bioimage informatics | Best Researcher Award

Doctorate at Department of Information Technology, College of Computer, Qassim University, Saudi Arabia

👨‍🎓Professional Profiles

Orcid Profile

Scopus Profile

👩‍💻 Summary

Dr. Shuaa S. Alharbi is an Assistant Professor in the Department of Information Technology at the College of Computer, Qassim University, Saudi Arabia. With a strong interdisciplinary background, she specializes in machine learning and image processing, particularly their applications in biomedical fields. Her research focuses on leveraging deep learning techniques to analyze medical images and improve diagnostic accuracy. Dr. Alharbi is dedicated to advancing bioinformatics and medical image analysis using cutting-edge technology.

🎓 Education

Dr. Alharbi holds a Ph.D. in Computer Science from Durham University, UK (2020), and both an M.Sc. and B.Sc. in Computer Science from Qassim University (2007) and King Saud University (2014), respectively. Her academic journey has provided her with a solid foundation in computer science, further augmented by extensive research in machine learning and bioimaging.

💼 Professional Experience

Dr. Alharbi has accumulated years of academic experience. She started as a Teaching Assistant at Qassim University in 2008, then progressed to Lecturer in 2015. Since 2020, she has served as an Assistant Professor at the same institution. Throughout her career, she has mentored students and contributed significantly to the academic environment at Qassim University, particularly in the Information Technology Department.

📝 Academic Committees & Administrative Roles

Dr. Alharbi has been deeply involved in various administrative roles at Qassim University. She served as E-content Supervisor (2020-2022), and currently coordinates the IT Department (2020-present). She is also a Postgraduate Supervisor (2023-present) and has been a Permanent Member of the Standing Committee for Assistance in the Scientific Council since 2023, contributing to the advancement of educational practices and research policies at the university.

🔬 Research Interests

Dr. Alharbi’s research interests are at the intersection of machine learning, image processing, and bioinformatics. She focuses on the application of deep learning for medical image analysis, working to enhance disease detection and diagnostic precision. Her work includes developing novel deep learning architectures and data-driven models to solve complex problems in medical and biological imaging.

🖥️ Technical Skills

Dr. Alharbi is proficient in a range of technical skills, including machine learning and deep learning frameworks, image and signal processing, computer graphics, and bioinformatics. She is experienced with programming languages such as Python, MATLAB, C++, and Java, and is adept at using these tools to solve complex problems in medical image analysis and other interdisciplinary fields.

📚 Teaching Experience

In addition to her research, Dr. Alharbi has taught several graduate-level courses, including Data Science, Computer Graphics, and Health Information Systems. She has also supervised Master’s theses in fields like cybersecurity, blockchain, and medical image processing, contributing to the academic growth of students in the Information Technology and Cybersecurity programs.

🌍 Conferences & Seminars

Dr. Alharbi has presented her work at prestigious international conferences, such as the IEEE BIBM International Conference on Bioinformatics and Biomedicine (Spain) and the Medical Image Computing Summer School at UCL (London). These platforms have allowed her to collaborate with global experts and stay at the forefront of research in bioimaging and machine learning.

💡 Research Grants

Dr. Alharbi was awarded a Coffee Research Grant from the Saudi Ministry of Culture, under the Saudi Heritage Preservation Society, showcasing her active involvement in research funding and promoting innovation in her fields of expertise.

 

📖 Top Noted Publications

nader tarabeih | Healthcare Data Analysis | Best Researcher Award

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Dr. nader tarabeih | Healthcare Data Analysis | Best Researcher Award

Dr. nader tarabeih at Ariel University, Israel

👨‍🎓Professional Profile

👨‍🔬 Summary

Dr. Nader Tarabeih is a dedicated researcher and clinician with a focus on genetic epidemiology and musculoskeletal disorders. Currently a postdoctoral researcher at Ariel University, his work centers on understanding inflammation-related biomarkers and their role in spinal pain. With a solid background in nursing, Dr. Tarabeih transitioned to academic research, publishing impactful studies on low back pain, metabolic factors, and their genetic causes.

🎓 Education

Dr. Tarabeih’s educational journey reflects his deep commitment to advancing medical research. He is currently pursuing a Post-doctoral position in Morphological Studies at the Adelson School of Medicine, Ariel University (2023 – Present). Previously, he completed his PhD in Genetic Epidemiology at Tel Aviv University (2018 – 2022), focusing on how blood biochemical factors and body composition affect spinal pain in complex Arab pedigrees. His MSc (2013 – 2016) also at Tel Aviv University examined genetic, demographic, and body composition risk factors for low back pain. Additionally, he holds a BA in Nursing from Tel Aviv University (2006 – 2010).

💼 Professional Experience

Dr. Tarabeih has gained extensive clinical and leadership experience in the healthcare field. He served as Director of Quality and Safety at the Maale HaCarmel Mental Health Center in Haifa, Israel (2020 – 2023). Prior to this, he worked as a Nurse at the same institution (2013 – 2020), where he applied his clinical expertise in a variety of settings, contributing to patient care and safety.

🔧 Technical Skills

Dr. Tarabeih brings a broad set of skills to his research and clinical practice. He is proficient in Genetic Epidemiology, specializing in the analysis of complex pedigrees and genetic risk factors for musculoskeletal disorders. His expertise extends to Biomarker Discovery, where he investigates biomarkers to improve the understanding and management of spinal pain. Additionally, he is skilled in Data Analysis and Clinical Research, focusing on inflammation, metabolic health, and spinal disorders.

👩‍🏫 Teaching Experience

Dr. Tarabeih has been an active contributor to academic discussions and has presented his research at several notable conferences. In 2022, he spoke on systemic biomarkers in degenerative lumbar spinal disorders at the Post-Genome Analysis for Musculoskeletal Biology Conference in Tzfat, Israel. He also presented on low back pain and its genetic and biochemical factors at the International Conference on Spine Disorders in Dubai, UAE (2020), and contributed a poster on genetic risk factors for low back pain at the BIRAX Ageing Conference in London, UK (2018).

🔬 Research Interests

Dr. Tarabeih’s research is driven by a passion for understanding the genetic and environmental causes of musculoskeletal disorders. His primary interests lie in Genetic Epidemiology, particularly in how genetic and lifestyle factors contribute to spinal pain. He is also dedicated to identifying biomarkers for pain-related disabilities and exploring the impact of inflammation and metabolism on musculoskeletal health in diverse populations.

 

📖 Top Noted Publications

Pushpa-Medical Image Processing, Biomedical Engineering-Best Researcher Award

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Author Profile

Google Scholar

Early Academic Pursuits

Mrs. Pushpa B embarked on her academic journey with a Bachelor's in Electronics and Instrumentation from St. Peter’s Engineering College, affiliated with Anna University, in 2007. Her dedication to the field was evident as she secured a commendable 73%. Building upon this foundation, she pursued an M.Tech in Electronics and Control from SRM University, Chennai, where she achieved a CGPA of 6.99 in 2010. The continuous academic excellence led her to undertake an MBA in Health Service Management from Anna University in 2023. Currently, she is on the verge of completing her Ph.D. in Medical Image Processing & Artificial Intelligence from Annamalai University, with her thesis submitted.

Professional Endeavors

With an illustrious academic background, Mrs. Pushpa B transitioned into academia, where she has made significant contributions. She held the position of Assistant Professor in various esteemed institutions such as B.S. Abdur Rahman Crescent Institute of Science and Technology and Velammal Institute of Technology. During her tenure, she shouldered numerous responsibilities, including curriculum development, university department audit coordination, and acting as a placement coordinator.

Contributions and Research Focus

Mrs. Pushpa B's expertise spans across diverse fields, including Analog Electronic Circuits, Digital Signal Processing, Machine Learning, and more. Her research primarily revolves around Medical Image Processing, Artificial Intelligence, and Bio-medical Instrumentation. Notably, she has undertaken projects like "Detection of Startle Type Epilepsy using Machine Learning Technique" at Global Medical Hospital, Chennai. Her research is widely recognized, with numerous international and national publications and conference presentations to her credit.

Accolades and Recognition

Mrs. Pushpa B's contributions to the academic and research communities have garnered her several accolades. She has published patents, notably one on "Intelligent estimation of liver fat and its stages by using DICOM." Furthermore, her publications in renowned journals like Technology and Health Care and Measurement Sensors, among others, testify to her expertise and recognition in her field.

Impact and Influence

Mrs. Pushpa B's influence extends beyond her academic and research endeavors. She has organized workshops, training programs, and conferences that have facilitated knowledge dissemination and skill enhancement for students, faculty, and industry professionals alike. Her expertise as a reviewer for esteemed platforms like Taylor & FrancisOnline, Elsevier, and IEEE Xplore further amplifies her impact in the scholarly community.

Legacy and Future Contributions

As a dedicated academician and researcher, Mrs. Pushpa B's legacy is marked by her commitment to advancing knowledge in her specialized domains. Her future contributions are anticipated to further bridge the gap between technology and healthcare, particularly in leveraging AI and machine learning techniques for enhanced medical diagnostics and treatments. With her relentless pursuit of excellence, she is poised to inspire future generations of researchers and academicians in the realms of Medical Image Processing and Artificial Intelligence.

In conclusion, Mrs. Pushpa B's academic pursuits, professional endeavors, and contributions to the field of Medical Image Processing and Artificial Intelligence stand as a testament to her passion, expertise, and commitment. Her multifaceted accomplishments underscore her potential to drive significant advancements and make lasting contributions to academia and healthcare.

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