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 University’s Mallinckrodt Institute of Radiology focused on radiotracer development.

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✨ 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.

🌐 Professional Endeavors

Dr. Sai’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.

⚛️ 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.

🏆 Accolades and Recognition

Dr. Sai’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.

🔬 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.

💡 Legacy and Future Contributions

Dr. Sai’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 Sai’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 β-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.

Maria Habib | Optimization | Best Researcher Award

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Ms. Maria Habib | Optimization | Best Researcher Award

Ms. Maria Habib, Granada University/ Samsung R&D (SRJO), Jordan.

Maria Habib is a distinguished researcher and AI engineer whose journey spans academia and industry. With a strong foundation in Computer Engineering, she advanced her expertise through a Master’s in Web Intelligence and is currently pursuing a Ph.D. in Information Technology and Communication. Maria’s professional endeavors include leading AI projects at Samsung R&D, transforming telehealth services at Altibbi, and contributing to bioinformatics at McGill University. Her research focuses on artificial intelligence, machine learning, evolutionary algorithms, and NLP, producing innovative solutions and influential publications. Her work has significantly impacted telemedicine, educational data mining, and speech technologies, establishing her as a transformative force in AI.

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Early Academic Pursuits 🎓

Maria Habib embarked on her academic journey with a robust foundation in Computer Engineering, earning her Bachelor’s degree from the University of Jordan in 2014. Demonstrating early promise, she excelled in her Master’s program in Web Intelligence at the prestigious King Abdullah II School for Information Technology, attaining an outstanding GPA of 3.91/4. Her passion for leveraging technology to address real-world challenges was evident from the outset, as she explored advanced concepts in information systems and web technologies. Maria is currently pursuing her Ph.D. in Information Technology and Communication at Granada University, Spain, where she continues to delve into cutting-edge AI research.

Professional Endeavors 💼

Maria’s career trajectory reflects a seamless blend of academic rigor and industry innovation. At Samsung R&D Institute in Jordan, she leads AI projects focusing on speech recognition and natural language processing, showcasing her prowess in automation and advanced search systems. Prior to this, Maria honed her skills at Altibbi, where she developed machine learning and deep learning models to revolutionize telehealth services. Her expertise spans diverse roles, from Python development for logistics platforms at Polares LLC to teaching Computer Science at ADS School. Each position has deepened her technical acumen and solidified her reputation as a versatile problem-solver.

Contributions and Research Focus 🔬

Maria’s research centers on artificial intelligence, machine learning, and evolutionary algorithms, emphasizing their transformative potential in healthcare, education, and NLP. Her collaborations with renowned academics like Prof. Hossam Faris and Dr. Ghaith Rabadi have resulted in influential publications in prestigious journals. Her work extends to bioinformatics, where she contributed to microbiome data visualization during her tenure as a Graduate Research Trainee at McGill University. As a member of the Evo-ML research group, Maria explores innovative solutions that bridge academia and industry, reinforcing her commitment to advancing AI for societal benefit.

Accolades and Recognition 🏆

Maria’s dedication to excellence has not gone unnoticed. Her stellar academic performance earned her accolades throughout her educational journey, culminating in a Master’s GPA of 3.91/4.0. Her professional roles have been marked by commendations for innovation and leadership, particularly at Samsung R&D and Altibbi. References from distinguished mentors like Prof. Ibrahim Aljarah and Prof. Jiangou Xia underscore the high regard in which she is held within the academic and professional communities.

Impact and Influence 🌍

Through her work in AI, Maria has significantly impacted fields such as telemedicine, educational data mining, and speech understanding. Her contributions to Altibbi transformed telehealth services, making them more accessible and efficient. Her teaching and mentorship roles have inspired students and peers alike, fostering a new generation of tech enthusiasts. Her initiatives in AI automation and optimization continue to resonate within the global technology landscape.

Legacy and Future Contributions 🌟

Maria’s journey is far from over. As an AI Project Lead and researcher, she is poised to shape the future of speech and language technologies. Her ongoing Ph.D. research promises groundbreaking insights into AI and communication systems. With a clear vision for the future, Maria aspires to bridge the gap between research and real-world applications, ensuring her legacy as a pioneer in computational innovation.

📚 Publications

  1. Title: Intelligent detection of hate speech in Arabic social network: A machine learning approach
    Authors: I. Aljarah, M. Habib, N. Hijazi, H. Faris, R. Qaddoura, B. Hammo, …
    Year: 2021

 

  1. Title: A dynamic locality multi-objective salp swarm algorithm for feature selection
    Authors: I. Aljarah, M. Habib, H. Faris, N. Al-Madi, A.A. Heidari, M. Mafarja, …
    Year: 2020

 

  1. Title: Augmented whale feature selection for IoT attacks: Structure, analysis, and applications
    Authors: M. Mafarja, A.A. Heidari, M. Habib, H. Faris, T. Thaher, I. Aljarah
    Year: 2020

 

  1. Title: Android ransomware detection based on a hybrid evolutionary approach in the context of highly imbalanced data
    Authors: I. Almomani, R. Qaddoura, M. Habib, S. Alsoghyer, A. Al Khayer, I. Aljarah, …
    Year: 2021

 

  1. Title: Evolutionary inspired approach for mental stress detection using EEG signal
    Authors: L.D. Sharma, V.K. Bohat, M. Habib, A.Z. Ala’M, H. Faris, I. Aljarah
    Year: 2022

 

  1. Title: Hate Speech Detection using Word Embedding and Deep Learning in the Arabic Language Context
    Authors: H. Faris, I. Aljarah, M. Habib, P.A. Castillo
    Year: 2020

 

  1. Title: An intelligent evolutionary extreme gradient boosting algorithm development for modeling scour depths under submerged weir
    Authors: H. Tao, M. Habib, I. Aljarah, H. Faris, H.A. Afan, Z.M. Yaseen
    Year: 2021

 

  1. Title: Optimizing extreme learning machines using chains of salps for efficient android ransomware detection
    Authors: H. Faris, M. Habib, I. Almomani, M. Eshtay, I. Aljarah
    Year: 2020

 

  1. Title: Salp chain-based optimization of support vector machines and feature weighting for medical diagnostic information systems
    Authors: A.M. Al-Zoubi, A.A. Heidari, M. Habib, H. Faris, I. Aljarah, M.A. Hassonah
    Year: 2020

 

 

Conclusion

Maria Habib’s career exemplifies the intersection of technical expertise and societal impact. Through her leadership and innovative research, she has contributed to advancements in healthcare, communication, and education. Her commitment to bridging research and application ensures her legacy as a pioneer in AI. Maria’s inspiring journey underscores the power of determination and innovation, positioning her as a role model in the global technology community.

Sunday Aboyeji | Feature selection | Best Researcher Award

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Mr. Sunday Aboyeji | Feature selection | Best Researcher Award

Mr. Sunday Aboyeji, Shenzhen Institutes of Advanced Technology, China.

Sunday Timothy Aboyeji is an accomplished researcher in computational science and biomedical signal processing. With an impressive academic foundation in physics and communication science, he has pursued groundbreaking research in patient-independent seizure classification using EEG data. His work combines advanced algorithms, deep learning, and explainable AI to enhance the accuracy and interpretability of diagnostic tools for epilepsy and other neurological disorders. His dedication to interdisciplinary collaboration and his contributions to high-impact publications reflect his influence in the field.

 

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📚 Early academic pursuits

Sunday Timothy Aboyeji began his academic journey with an unwavering passion for physical and computational sciences. Earning his Bachelor of Technology in Physics/Electronics from the Federal University of Technology, Minna, Nigeria, he graduated with first-class honors and a stellar GPA of 4.61/5.00. His undergraduate thesis, which explored the simulation of radiofrequency radiation effects on the brain, laid the foundation for his future endeavors in biomedical signal processing. He further honed his expertise by completing a Master’s degree in Communication Physics at the Federal University of Technology, Akure, Nigeria, achieving an outstanding GPA of 4.86/5.00. His master’s research on radioclimatic variables and refractivity modeling highlighted his ability to blend theoretical knowledge with practical applications.

🔬 Professional endeavors

Sunday is currently pursuing a Ph.D. in Pattern Recognition and Intelligent Systems at the University of Chinese Academy of Sciences, Shenzhen Institute of Advanced Technology, China. His doctoral dissertation focuses on developing patient-independent EEG-based seizure classification algorithms. Over the course of his research, he has designed cutting-edge solutions integrating signal processing, feature engineering, and deep learning. His projects include unsupervised seizure detection, feature fusion of Gramian angular fields, and domain adaptation frameworks, all aimed at revolutionizing epilepsy diagnosis. Beyond his academic achievements, he is an active member of IEEE and serves as a certified first-aider in Shenzhen, demonstrating his dedication to community service and professional growth.

🧠 Contributions and research focus

Sunday’s research has profoundly impacted computational science and biomedical signal processing. He specializes in the analysis of EEG, EMG, and other complex biomedical signals using advanced algorithms and explainable AI techniques. His groundbreaking work emphasizes the interpretability of deep learning models, enabling better diagnostic tools for epilepsy and other neurological disorders. By transforming biomedical signals into visual spectrograms and leveraging hybrid feature selection frameworks, he has created highly accurate and reliable classification models that support patient care and advance brain-computer interface technology.

🏆 Accolades and recognition

Sunday’s academic excellence has been recognized through multiple awards, including the prestigious Chinese Government Scholarship for his Ph.D. studies. His undergraduate achievements earned him commendations from his university dean. These accolades reflect his dedication to academic rigor and his ability to excel in highly competitive environments. He has also been invited to serve as a peer reviewer for leading journals, further solidifying his reputation as a rising star in his field.

🌍 Impact and influence

Through collaborative efforts with international scholars and researchers, Sunday has contributed to several high-impact publications in journals such as Computers in Biology and Medicine and the IEEE Journal of Biomedical and Health Informatics. His work on robust seizure detection and interpretable machine learning models has set a benchmark for researchers in biomedical signal processing. These contributions not only enhance patient diagnostics but also pave the way for more accessible healthcare technologies.

🌟 Legacy and future contributions

Sunday aspires to leave a legacy as a trailblazer in biomedical signal processing and computational sciences. His ongoing research on domain adaptation frameworks promises to address patient-specific challenges, making diagnostic systems more generalized and inclusive. He envisions leveraging his expertise to develop innovative solutions that enhance the quality of life for individuals with neurological disorders, ensuring his work continues to inspire and benefit the global scientific community.

💡 Dedication to innovation

Sunday’s career exemplifies a commitment to innovation, interdisciplinary collaboration, and societal impact. With his technical skills in Python, TensorFlow, and Pytorch, coupled with a deep understanding of signal processing and pattern recognition, he remains at the forefront of research in his field. His dedication to integrating advanced technology with real-world applications underscores his role as a visionary researcher and advocate for progress in medical diagnostics.

📚 Publications

  • Title: Robust Epileptic Seizure Detection Based on Biomedical Signals Using an Advanced Multi-View Deep Feature Learning Approach
    Authors: Ijaz Ahmad, Zhenzhen Liu, Lin Li, Inam Ullah, Sunday Timothy Aboyeji, Xin Wang, Oluwarotimi Williams Samuel, Guanglin Li, Yuan Tao, Yan Chen, et al.
    Year: 2024

 

  • Title: Automatic Detection of Epileptic Seizure Based on One Dimensional Cascaded Convolutional Autoencoder with Adaptive Window-Thresholding
    Authors: Sunday Timothy Aboyeji, Xin Wang, Yan Chen, Ijaz Ahmad, Lin Li, Zhenzhen Liu, Chen Yao, Guoru Zhao, Yu Zhang, Guanglin Li, et al.
    Year: 2024

 

  • Title: Feature Fusion of Gramian Angular Field Deep Learning EEG-Based Epileptic Seizure Classification
    Authors: Sunday Timothy Aboyeji, Xin Wang, Yan Chen, Ijaz Ahmad, Lin Li, Zhenzhen Liu, Chen Yao, Yu Zhang, Guoru Zhao, Guanglin Li, et al.
    Year: 2024

 

  • Title: Modeling of Atmospheric Primary Radioclimatic Variables in Nigeria for Microwave Radio Propagation Applications
    Authors: Falodun, S.E., Ojo, J.S., Aboyeji, S.T.
    Year: 2021

 

Conclusion

Sunday’s journey exemplifies a relentless pursuit of knowledge and innovation. From his academic excellence in Nigeria to his impactful research at the Shenzhen Institute of Advanced Technology, he has made meaningful strides in advancing patient care through computational science. With a clear vision for the future, his contributions promise to continue shaping the landscape of biomedical signal processing and inspire further advancements in medical diagnostics.

 

Chen Wang | neural network application | Best Researcher Award

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Prof Dr.Chen Wang | neural network application | Best Researcher Award

Prof Dr Chen Wang School of Mining, Guizhou University China

Wang Chen is a distinguished professor at Guizhou University, specializing in mining engineering and resources and environment. He holds a PhD from the China University of Mining and Technology and has significant expertise in mining methods, rock mechanics, mining system engineering, and the kinematic behavior of rock layers in karst regions.

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📚 Recruitment Discipline Direction

Mining Engineering, Resources and Environment

🔬 Main Research Fields and Directions

Mining Methods,Rock Mechanics,Mining System Engineering,Roadway Support,Kinematic Mechanisms of Rock Layers in Karst Mountainous Areas.

💼 Key Research Projects (2018 – Present)

National Natural Science Foundation General Project (52174072)“Study on the Mechanisms of Rock Layer Movement under Repeated Mining in Karst Mountainous Areas,” 2022.01-2025.12, 580,000 RMB, Principal Investigator, ongoing. 💰National Natural Science Foundation Youth Science Fund Project (51904081)“Study on the Mechanisms of Instability Induced by Mining in Shallowly Buried Coal Layers in Karst Terrain,” 2020.01-2022.12, 240,000 RMB, Principal Investigator, ongoing. 🔍

✍️ Journal Articles:

Wang Chen et al. “An Expert System for Equipment Selection of Thin Coal Seam Mining.” (2019) .Wang Chen et al. “Optimal Selection of a Longwall Mining Method for a Thin Coal Seam Working Face.” (2016) .Wang Chen, Zhou Jie. “New Advances in Automatic Shearer Cutting Technology.” (2021) ⚙️

🥇 Achievements

Patents: 5 granted invention patents related to coal mining technology. Awards: Multiple research awards for contributions to mining technology. 🏆

📚 Publications

  1. Title: Study on strength prediction and strength change of Phosphogypsum-based composite cementitious backfill based on BP neural network
    Authors: Wu, M., Wang, C., Zuo, Y., Zhang, J., Luo, Y.
    Year: 2024
    Journal: Materials Today Communications
    Volume: 41
    Article Number: 110331

 

  1. Title: Correction: Determination of working resistance of support parameter variation of large mining height support: the case of Caojiatan coal mine
    Authors: Xue, B., Zhang, W., Wang, C.
    Year: 2024
    Journal: Geomechanics and Geophysics for Geo-Energy and Geo-Resources
    Volume: 10
    Issue: 1
    Pages: 14

 

  1. Title: Determination of working resistance of support parameter variation of large mining height support: the case of Caojiatan coal mine
    Authors: Xue, B., Zhang, W., Wang, C.
    Year: 2024
    Journal: Geomechanics and Geophysics for Geo-Energy and Geo-Resources
    Volume: 10
    Issue: 1
    Pages: 1

 

  1. Title: Evolution of Broken Coal’s Permeability Characteristics under Cyclic Loading–Unloading Conditions
    Authors: Luo, L., Zhang, L., Pan, J., Wang, C., Li, S.
    Year: 2024
    Journal: Natural Resources Research
    Volume: 33
    Issue: 5
    Pages: 2279–2297

 

  1. Title: Preparation and characterization of green lignin modified mineral cementitious firefighting materials based on uncalcined coal gangue and coal fly ash
    Authors: Dou, G., Wang, C., Zhong, X., Qin, B.
    Year: 2024
    Journal: Construction and Building Materials
    Volume: 435
    Article Number: 136799

 

  1. Title: Mining Technology Evaluation for Steep Coal Seams Based on a GA-BP Neural Network
    Authors: Li, X., Wang, C., Li, C., Luo, Y., Jiang, S.
    Year: 2024
    Journal: ACS Omega
    Volume: 9
    Issue: 23
    Pages: 25309–25321

 

  1. Title: Capturing rate- and temperature-dependent behavior of concrete using a thermodynamically consistent viscoplastic-damage model
    Authors: Tao, J., Yang, X.-G., Lei, Y., Wang, C.
    Year: 2024
    Journal: Construction and Building Materials
    Volume: 422
    Article Number: 135791

Conclusion

Wang Chen’s extensive research and numerous publications significantly contribute to the field of mining engineering. His focus on the complexities of karst geology and the development of intelligent mining technologies positions him as a leader in advancing mining safety and efficiency. His ongoing projects reflect a commitment to addressing contemporary challenges in the mining sector, particularly in relation to environmental sustainability and resource management.