Mostafa Jalilifar | Medical Physics | Best Researcher Award

Dr. Mostafa Jalilifar | Medical Physics | Best Researcher Award

Researcher at Iran University of Medical Sciences, Iran

Dr. Mostafa Jalilifar is a medical physicist with expertise in nuclear medicine, radiation therapy, and AI-driven medical imaging. He is currently completing his Ph.D. at Iran University of Medical Sciences, focusing on deep learning-based dosimetry for thyroid cancer treatments. He has taught at leading academic institutions in Iran, contributed to multiple research projects in medical physics, and actively publishes in the field. His work bridges advanced imaging techniques with artificial intelligence to improve patient outcomes in nuclear medicine.

Publication Profile

Scopus

Orcid 

Educational Details

  • Ph.D. in Medical Physics (2019–2024) – Iran University of Medical Sciences
    • Thesis: Estimation of Patient-Specific Absorbed Dose in Radioiodine Therapy of Thyroid Cancer Patients Based on Planar (2D) and SPECT (3D) Images Using Deep Learning.
  • M.Sc. in Medical Physics (2013–2016) – Jundi Shapur University of Medical Sciences, Iran
    • Thesis: Quantitative Evaluation of EEG During Amygdala Kindling to Categorize Different Stages of Kindling: A Step to Develop a Seizure Prevention Technique.
  • B.Sc. in Medical Radiation Engineering (2009–2013) – Islamic Azad University, Tehran Science and Research Branch

Professional Experience

Dr. Mostafa Jalilifar is a medical physicist specializing in nuclear medicine, radiation therapy, and medical imaging analysis. He has taught extensively at various academic institutions, including Iran University of Medical Sciences and Shahid Chamran University of Ahvaz. His teaching portfolio includes undergraduate and graduate courses such as Basic Physics, Medical Physics, and New Perspectives in Nuclear Medicine. He has also contributed to laboratory training and hands-on learning for medical students.

Dr. Jalilifar’s research focuses on dosimetry, radiotherapy optimization, deep learning applications in medical imaging, and quantitative analysis of brain activity during seizure development. His doctoral research integrates artificial intelligence with nuclear medicine imaging to enhance patient-specific dose estimations in thyroid cancer treatments.

Research Interest

  • Nuclear Medicine and Radiation Therapy
  • Dosimetry and Patient-Specific Dose Estimation
  • Medical Imaging Analysis (SPECT, PET, Planar Imaging)
  • AI and Deep Learning in Medical Imaging
  • EEG Analysis and Seizure Prediction

Top Noted Publication

Title: Quantifying Partial Volume Effect in SPECT and Planar Imaging: Optimizing Region of Interest for Activity Concentration Estimation in Different Sphere Sizes
Authors: Mostafa Jalilifar, Mahdi Sadeghi, Alireza Emami-Ardekan, Kouhyar Geravand, Parham Geramifar
Journal: Nuclear Medicine Communications
Year: 2024
Citations: 1

Conclusion

Dr. Mostafa Jalilifar is a strong candidate for the Best Researcher Award. His research in AI-driven nuclear medicine imaging and patient-specific dosimetry is highly innovative and clinically relevant. To enhance his competitiveness, he should focus on increasing citation impact, securing leadership roles, and publishing in high-impact journals. With his expertise in medical physics, radiation therapy, and AI integration, he is well-positioned to make significant contributions to the field.

 

 

Prasanth Kamma | Healthcare Technology | Best Researcher Award

Dr. Prasanth Kamma | Healthcare Technology | Best Researcher Award

Principal Architect at Aetna Inc. (A CVS Health Company) United States

Summary:

Dr. Prashanth Kamma is a visionary Salesforce Principal Architect and thought leader in Salesforce DevOps. Known for his technical expertise and mentorship within the Copado community, he consistently delivers innovative solutions for complex Salesforce implementations, empowering businesses to achieve scalable and sustainable growth.

Profile:

Scopus Profile

Education:

  • Bachelor’s in Electronics and Communication Engineering.

Professional Experience:

Dr. Prashanth Kamma is an accomplished Salesforce Principal Architect with over a decade of experience in designing and implementing scalable, innovative, and AI-driven Salesforce solutions across industries, particularly in healthcare. Currently serving at Aetna Inc. (a CVS Health company), he leads the Salesforce Center of Excellence, driving the development of Care Management Applications and Field Service Lightning (FSL) solutions. His expertise includes crafting enterprise applications, integrating Salesforce with legacy systems, and advancing DevSecOps strategies using tools like Copado and Jenkins. Dr. Kamma has also collaborated with Salesforce Professional Services and Appirio on large-scale FSL implementations, showcasing his technical leadership and commitment to aligning Salesforce functionalities with strategic business goals.

Research Interests:

Dr. Kamma’s research interests focus on the intersection of cloud-based CRM solutions, AI-driven healthcare applications, and predictive analytics. He is particularly passionate about optimizing Salesforce Field Service Lightning for healthcare, integrating AI and machine learning for enhanced patient care, and developing robust CI/CD pipelines to streamline application lifecycle management. His work emphasizes leveraging technology to drive innovation in healthcare systems and enterprise resource planning.

Top Noted Publications:

1. Revolutionizing Patient Care With Data-Driven Healthcare Applications: A “Machine Learning” And Predictive Analytics Framework

  • Author: Dr. Prashanth Kamma
  • Journal: Frontiers in Health Informatics
  • Year: 2024
  • Volume: 13
  • Issue: 3
  • Pages: 203–213
  • Abstract: The article introduces a cutting-edge framework that employs machine learning and predictive analytics to revolutionize patient care. It focuses on leveraging data-driven approaches for enhancing clinical decision-making, optimizing patient outcomes, and improving the efficiency of healthcare processes. Practical examples of real-time data integration and predictive models are provided, showcasing their potential to reshape healthcare delivery systems.

2. AI-Driven Predictive Analytics in Healthcare: Leveraging Salesforce for Scalable, Data-Driven Patient Management Systems

  • Author: Dr. Prashanth Kamma
  • Journal: Frontiers in Health Informatics
  • Year: 2024
  • Volume: 13
  • Issue: 3
  • Pages: 1–13
  • Abstract: This paper explores the integration of AI-driven predictive analytics into Salesforce to develop scalable and efficient patient management systems. The study highlights methods for incorporating advanced machine learning techniques into the Salesforce ecosystem to improve healthcare operations. It details strategies for risk assessment, real-time data monitoring, and predictive modeling to enable personalized care and resource allocation.

Conclusion:

Dr. Prashanth Kamma is a highly accomplished professional whose technical expertise, research contributions, and leadership in healthcare technology make him a strong contender for the Best Researcher Award. His pioneering work in AI-driven predictive analytics and Salesforce-based healthcare applications addresses critical challenges in modern healthcare systems, improving patient care and operational efficiency.

To further solidify his candidacy, Dr. Kamma could diversify his research to encompass other emerging technologies, expand his global outreach, and focus on broader healthcare challenges. However, his innovative contributions to healthcare informatics, coupled with his leadership in the Salesforce ecosystem, position him as a deserving candidate for this recognition.