Kiran Solingapuram Sai | Neuroimaging | Best Researcher Award

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Dr. Kiran Solingapuram Sai | Neuroimaging | Best Researcher Award

Dr. Kiran Solingapuram Sai, Wake Forest School of Medicine, United States.

Dr. Kiran K. Solingapuram Sai, PhD, is an Associate Professor with tenure in the Department of Radiology at Wake Forest School of Medicine. He holds a Ph.D. in Organic Chemistry from Northern Illinois University and has extensive research experience in radiopharmaceutical chemistry. His postdoctoral training at Washington Universityā€™s Mallinckrodt Institute of Radiology focused on radiotracer development.

Profile

Orcid

 

āœØ Early Academic Pursuits

Dr. Kiran K. Solingapuram Sai embarked on his academic journey with a strong foundation in chemistry, earning a Bachelor of Science degree in Chemistry, Biochemistry, and Microbiology from Osmania University, Hyderabad, India, in 2001. His passion for organic chemistry led him to pursue a Master of Science in the same field at Osmania University, where he honed his expertise in chemical synthesis and molecular interactions. Determined to explore the depths of organic chemistry, he pursued his Ph.D. at Northern Illinois University, DeKalb, IL, under the mentorship of Dr. Douglas A. Klumpp. During this period, his research focused on synthetic methodologies and organic reaction mechanisms, paving the way for his future contributions to medicinal and radiopharmaceutical chemistry.

šŸŒ Professional Endeavors

Dr. Saiā€™s professional journey commenced with a prestigious postdoctoral research associate position at the Mallinckrodt Institute of Radiology at Washington University in St. Louis, MO, where he worked under the guidance of Dr. Robert H. Mach. During his tenure from 2010 to 2013, he delved into the complexities of radiochemistry, developing novel radiotracers and exploring their applications in medical imaging. This experience laid the groundwork for his career in radiopharmaceutical sciences. In 2014, he joined Wake Forest School of Medicine as a Research Instructor and Chief Radiochemist, marking the beginning of his significant contributions to translational imaging and radiopharmaceutical production.

āš›ļø Contributions and Research Focus

At Wake Forest School of Medicine, Dr. Sai played a pivotal role in the Department of Radiology and the Clinical Translational Science Institute (CTSI). He specialized in managing clinical and research-based radiopharmaceutical production at the Wake Forest PET Research Center. As a cyclotron manager and coordinator, he oversaw the synthesis and quality control of radiotracers essential for PET imaging. His expertise extended to the development and implementation of cGMP-approved protocols for C-11 and F-18 radiopharmaceutical production, ensuring the highest standards of safety and efficacy. His research focuses on advancing PET imaging techniques, exploring new radiotracers for diagnostic and therapeutic applications, and improving imaging biomarker development.

šŸ† Accolades and Recognition

Dr. Saiā€™s dedication to radiochemistry and molecular imaging has earned him recognition in the scientific community. His work has been instrumental in developing radiopharmaceuticals for neurological and oncological imaging, contributing significantly to early disease detection and targeted therapy. His contributions have been acknowledged through numerous research grants, collaborative projects, and publications in high-impact scientific journals. His commitment to excellence and innovation has positioned him as a leading figure in the field of radiopharmaceutical sciences.

šŸ”¬ Impact and Influence

Beyond his research and technical expertise, Dr. Sai has mentored budding scientists and researchers in the field of radiochemistry and imaging sciences. His guidance has helped shape the next generation of radiopharmaceutical experts, fostering a culture of innovation and scientific curiosity. His role in translational imaging programs has bridged the gap between basic research and clinical applications, directly impacting patient care by improving diagnostic imaging techniques.

šŸ’” Legacy and Future Contributions

Dr. Saiā€™s work continues to inspire advancements in molecular imaging and radiopharmaceutical development. As an Associate Professor with tenure at Wake Forest School of Medicine, he remains dedicated to pushing the boundaries of radiochemistry, developing cutting-edge imaging agents, and enhancing the precision of diagnostic medicine. His legacy in the field is defined by his unwavering commitment to scientific discovery, translational research, and the continuous pursuit of excellence in radiopharmaceutical sciences.Dr. Kiran K. Solingapuram Saiā€™s contributions to the field of radiopharmaceutical chemistry stand as a testament to his dedication, innovation, and impact on medical imaging and healthcare. His journey from a passionate chemistry student to a distinguished professor and researcher highlights the transformative power of science in shaping the future of medicine.

 

Publication

  1. Radiation-induced brain injury in non-human primates: A dual tracer PET study with [11C]MPC-6827 and [11C]PiB

    • Authors: Naresh Damuka, George W. Schaaf, Mack Miller, Caleb Bradley, Bhuvanachandra Bhoopal, Ivan Krizan, Krishna K. Gollapelli, Christopher T. Whitlow, J. Mark Cline, Kiran K. Solingapuram Sai
    • Year: 2025

 

  1. The Ī²-Secretase 1 Enzyme as a Novel Therapeutic Target for Prostate Cancer

    • Authors: Hilal A. Rather, Sameh Almousa, Ashish Kumar, Mitu Sharma, Isabel Pennington, Susy Kim, Yixin Su, Yangen He, Abdollah R. Ghara, Kiran Kumar Solingapuram Sai et al.
    • Year: 2023

 

  1. Development and Optimization of 11C-Labeled Radiotracers: A Review of the Modern Quality Control Design Process

    • Authors: Paul Josef Myburgh, Kiran Kumar Solingapuram Sai
    • Year: 2023

 

  1. Binding Parameters of [11C]MPC-6827, a Microtubule-Imaging PET Radiopharmaceutical in Rodents

    • Authors: Avinash H. Bansode, Bhuvanachandra Bhoopal, Krishna Kumar Gollapelli, Naresh Damuka, Ivan Krizan, Mack Miller, Suzanne Craft, Akiva Mintz, Kiran Kumar Solingapuram Sai
    • Year: 2023

 

  1. PET Imaging of [11C]MPC-6827, a Microtubule-Based Radiotracer in Non-Human Primate Brains

    • Authors: Naresh Damuka, Paul W. Czoty, Ashley T. Davis, Michael Nader, Susan H. Nader, Suzanne Craft, Shannon L. Macauley, Lindsey K. Galbo Thomma, Phillip M. Epperly, Christopher T. Whitlow et al.
    • Year: 2020

 

  1. One-pot synthesis of novel tert-butyl-4-substituted phenyl-1H-1,2,3-triazolo piperazine/piperidine carboxylates, potential GPR119 agonists

    • Authors: Nagaraju Bashetti, J.V. Shanmukha Kumar, Naresh Varma Seelam, B. Prasanna, Akiva Mintz, Naresh Damuka, Sriram Devanathan, Kiran Kumar Solingapuram Sai
    • Year: 2019

 

Conclusion

Dr. Kiran K. Solingapuram Sai has established himself as a leading expert in radiopharmaceutical sciences, contributing significantly to translational imaging research. His work in PET radiopharmaceutical production and quality assurance underscores his role in advancing medical imaging techniques. His academic and research contributions make him a valuable asset in the field of radiology and molecular imaging.

Saba Hesaraki | Neurotechnology | Best Researcher Award

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Ms. Saba Hesaraki | Neurotechnology | Best Researcher Award

Ms. Saba Hesaraki,Ā  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 Masterā€™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

šŸŒ± 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 Masterā€™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.

šŸ’¼ Professional Endeavors

Sabaā€™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.

šŸ“š Contributions and Research Focus

As a dedicated researcher, Sabaā€™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.

šŸ† Accolades and Recognition

Sabaā€™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.

šŸŒ Impact and Influence

Sabaā€™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.

šŸš€ 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.