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

Bo Zhai | Healthcare Data Analysis | Best Researcher Award

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Prof Dr. Bo Zhai | Healthcare Data Analysis | Best Researcher Award

The Fourth Hospital of Harbin Medical University, China

Author Profile

Scopus

Early Academic Pursuits 📚

Dr. Bo Zhai, a highly respected Chief Physician and Associate Professor at The Fourth Hospital of Harbin Medical University, began his academic journey with a focus on hepatology and cell biology. After earning his MD, Dr. Zhai pursued advanced training as a Postdoctoral Fellow and later became a Fellow of the American College of Surgeons (FACS). His early academic work laid the foundation for his ongoing contributions to liver cancer research, particularly in the realm of hepatocellular carcinoma (HCC).

Professional Endeavors 🏥

Dr. Zhai has had a distinguished professional career, having served as a visiting scholar at the Liver Research Center of Brown University in the USA, sponsored by the National Foreign Experts Bureau. His work on liver cancer has been pivotal in understanding the complexities of HCC, a disease known for its resistance to conventional therapies like sorafenib. His international experience has broadened his research scope and enriched his academic and clinical expertise.

Contributions and Research Focus 🧬

Dr. Zhai’s primary research focus is on hepatocellular carcinoma (HCC), particularly how ASPH (Aspartate β-hydroxylase) influences cell death and contributes to chemoresistance in HCC. He has discovered that high levels of ASPH in HCC enhance proliferation, migration, and invasion, and also predict worse clinical outcomes for patients undergoing sorafenib treatment. His groundbreaking work suggests that targeting ASPH could break new ground in HCC therapy, overcoming the challenges posed by drug resistance.

Impact and Influence 🌍

Dr. Zhai’s research has had a significant impact on the field of liver cancer research, especially in understanding mechanisms of resistance to conventional cancer therapies. His studies on ASPH in HCC have opened new avenues for therapeutic interventions, providing insights into the role of autophagy, ferroptosis, and cell survival pathways in cancer progression. His work has been published in prestigious journals, including Cancer Letters, and is cited widely, underlining his contribution to the scientific community.

Academic Citations 📈

With an impressive citation index of 17.7, Dr. Zhai’s work is highly regarded in the academic community. His research publications, particularly those related to ASPH and HCC, have made substantial contributions to the understanding of liver cancer biology. His studies have provided valuable insights into the molecular mechanisms behind HCC’s resistance to chemotherapy, paving the way for new therapeutic strategies.

Technical Skills 🔬

Dr. Zhai has a wide range of technical skills, including expertise in molecular biology, cancer cell biology, and animal model studies. His proficiency in studying autophagy, ferroptosis, and tumor metastasis has made him a leader in the field of liver cancer research. Additionally, his experience with gene silencing and knockout models has allowed him to explore new potential targets for cancer treatment.

Teaching Experience 🧑‍🏫

As an Associate Professor, Dr. Zhai has contributed significantly to the education and mentoring of graduate and medical students. He has supervised numerous Master’s students and postdoctoral fellows, passing on his expertise in liver cancer research. His teaching extends beyond the classroom, as he is also involved in sharing his knowledge and findings through academic conferences and seminars.

Legacy and Future Contributions 🌱

Dr. Zhai’s legacy in liver cancer research is already well-established, with his groundbreaking work on ASPH setting the stage for future therapeutic developments. As he continues to pursue innovative approaches in HCC treatment, his research promises to lead to better clinical outcomes for patients battling liver cancer. His future contributions to the field will likely focus on developing targeted therapies that can overcome chemoresistance and improve patient survival rates.

Top Noted Publications 📖

ASPH dysregulates cell death and induces chemoresistance in hepatocellular carcinoma
    • Authors: Jingtao Li, Guocai Zhong, Fengli Hu, Qiushi Lin, Xiaoqun Dong, Bo Zhai
    • Journal: Cancer Letters
    • Year: 2024
Mechanisms of vascular co-option as a potential therapeutic target in hepatocellular carcinoma
    • Authors: Ming-Hao Qi, Jing-Tao Li, Bo Zhai
    • Journal: World Chinese Journal of Digestology
    • Year: 2024
Aspartate-β-hydroxylase as a promising prognostic and therapeutic biomarker for HBV-positive hepatocellular carcinoma
    • Authors: Jingtao Li, Zongwen Wang, Xiaohang Ren, WenYu Liu, Shicong Zeng, Bo Zhai
    • Journal: Research Square
    • Year: 2023
Is hepatic resection always a better choice than radiofrequency ablation for solitary hepatocellular carcinoma regardless of age and tumor size?
    • Authors: Shicong Zeng, Yao Zhang, Zongwen Wang, Qiankun Zhu, Yan Yan, Bo Zhai
    • Journal: Biomolecules & Biomedicine
    • Year: 2023
Identification of risk and prognostic factors for intrahepatic vascular invasion in patients with hepatocellular carcinoma: a population-based study
    • Authors: Shicong Zeng, Zongwen Wang, Qiankun Zhu, Fengli Hu, Lishan Xu, Bo Zhai
    • Journal: Translational Cancer Research
    • Year: 2022

Christopher Prashad | Public Health | Best Researcher Award

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Dr. Christopher Prashad | Public Health | Best Researcher Award

York University, Canada

Author Profile 📚

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🔍 Summary

Dr. Christopher Prashad is a PhD candidate in Mathematics and Statistics, specializing in Data Science for Public Health at York University. With a strong foundation in advanced quantitative research, including time series analysis, machine learning, stochastic simulation, and probabilistic programming, Dr. Prashad excels in transforming complex data into actionable insights. He has a proven track record of collaborating with academic and industry teams, effectively communicating technical concepts, and is eager to apply his skills in Data Science to drive meaningful decision-making.

🎓 Education

Dr. Prashad is currently pursuing his PhD in Mathematics and Statistics – Data Science for Public Health at York University (expected June 2025). He is also completing a MicroMasters in Finance from MIT Sloan School of Management (expected January 2025). He holds a Master’s degree in Mathematics and Statistics from York University and a Bachelor of Science in Mathematics and Chemistry from the University of Toronto.

💼 Professional Experience

Dr. Prashad has worked as a Mathematics for Public Health Researcher at York University–Sanofi Pasteur (2022–2024), where he collaborated with pharmaceutical companies and public health organizations to drive evidence-based policies and modeling initiatives. Prior to this, he worked as a Statistician at Western University (2014–2019), conducting longitudinal studies to assess the impact of STEM education programs. He has also served as a Course Director for Statistical Methods in Health Studies at York University (2018–2019), delivering lectures and tutorials while fostering student engagement in applied statistics.

📚 Academic Projects & Presentations

Dr. Prashad has contributed to several notable academic projects, such as Multiperiod Forecasting of Epidemic Prevalence using machine learning to predict the spread of flu-like illnesses, and Stochastic Threshold Analysis for SIRS Model, where he applied advanced mathematical techniques to epidemic modeling. He also analyzed Indexed GIC Investment Products using stochastic volatility models, presenting his findings to industry leaders in finance.

💻 Technical Skills

Dr. Prashad is proficient in a wide range of software and analytical tools, including Python, R, MATLAB, SQL, SPSS, and C. He specializes in Time Series Analysis, Stochastic Simulation, Machine Learning, Multivariate Statistics, and Probabilistic Programming, with expertise in Bayesian Methods, Optimization, and Data Visualization.

👩‍🏫 Teaching Experience

As a Course Director at York University, Dr. Prashad designed and delivered lectures on statistical methods in health studies, supported diverse student learning needs, and contributed to collaborative course design and student development.

🔬 Research Interests

Dr. Prashad’s research interests lie at the intersection of data-driven public health modeling, machine learning in healthcare, and mathematical epidemiology, with a particular focus on applying quantitative analysis to solve public health challenges.

 

📖 Top Noted Publications

Stochastic Threshold Analysis for Mean-Reverting SIRS Model
    • Authors: Dr. Christopher Prashad (and collaborators)
    • Journal: Journal of Theoretical Biology
    • Year: 2024
Problems and Solutions in Modern Finance, Financial Accounting, Mathematical Methods for Quantitative Finance, and Derivatives Markets
    • Authors: Dr. Christopher Prashad (and collaborators)
    • Journal: Independent publication
    • Year: 2024
Assessing the Impact of Community Mobility on COVID-19 Dynamics
    • Authors: Dr. Christopher Prashad (and collaborators)
    • Journal: PLOS Computational Biology
    • Year: 2024
State-Space Modelling for Infectious Disease Surveillance Data: Stochastic Simulation Techniques and Structural Change Detection
    • Authors: Dr. Christopher Prashad (and collaborators)
    • Journal: Journal of Infectious Disease Modelling, Primer Articles
    • Year: 2024
State-Space Modelling for Infectious Disease Surveillance Data: Dynamic Regression and Covariance Analysis
    • Authors: Dr. Christopher Prashad (and collaborators)
    • Journal: Journal of Infectious Disease Modelling, Primer Articles
    • Year: 2024

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