Neha Vats | Medical Physics | Best Researcher Award

Published on by Life Science

Dr. Neha Vats | Medical Physics | Best Researcher Award

Heidelberg University | Germany

Dr. Neha Vats is a postdoctoral researcher in Medical Imaging and Spectroscopy at the Central Institute of Mental Health, Mannheim, Germany, with a strong research foundation in MRI, CT, and multinuclear MRS. Her expertise lies in quantitative image analysis, medical image processing, and the development of advanced imaging protocols. She has contributed significantly to translational neuroimaging and oncology through the optimization of CT perfusion techniques and neurochemical imaging in psychiatric populations. Her scholarly output includes five peer-reviewed publications in high-impact journals such as Scientific Reports and Magnetic Resonance Imaging, addressing topics like pancreatic CT perfusion standardization, perfusion model development, and machine-learning-based tumor differentiation. According to her Scopus profile, she has 5 documents, an h-index of 4, and 28 citations, reflecting strong research visibility and growing academic impact in biomedical imaging. Dr. Vats’s technical proficiency spans MATLAB, C++, perfusion mathematical modeling, and quantitative neuroimaging, with research interests focusing on advanced spectroscopy methods and metabolic brain characterization. Her ongoing projects on ME/CFS and aggression-related brain changes exemplify her commitment to integrating imaging physics with neuroscience for clinical translation and sustainable advancements in medical diagnostics.

Profiles: Scopus | Orcid | Research Gate 

Featured Publications

Vats, N., Mayer, P., Kortes, F., Klauß, M., Grenacher, L., Stiller, W., Kauczor, H.-U., & Skornitzke, S. Evaluation and timing optimization of CT perfusion first pass analysis in comparison to maximum slope model in pancreatic adenocarcinoma. Scientific Reports, 13, Article 10865.

Skornitzke, S., Vats, N., Mayer, P., Kauczor, H.-U., & Stiller, W. Pancreatic CT perfusion: Quantitative meta-analysis of disease discrimination, protocol development, and effect of CT parameters. Insights into Imaging, 14, Article 1471.

Vats, N., Sengupta, A., Gupta, R. K., Patir, R., Vaishya, S., Ahlawat, S., Saini, J., Agarwal, S., & Singh, A. Differentiation of pilocytic astrocytoma from glioblastoma using a machine-learning framework based upon quantitative T1 perfusion MRI. Magnetic Resonance Imaging, 97, 63–71.

Skornitzke, S., Vats, N., Kopytova, T., Tong, E. W. Y., Hofbauer, T., Weber, T. F., Rehnitz, C., von Stackelberg, O., Maier-Hein, K., & Stiller, W. Asynchronous calibration of quantitative computed tomography bone mineral density assessment for opportunistic osteoporosis screening: Phantom-based validation and parameter influence evaluation. Scientific Reports, 12, Article 20478

Roseline Ogundokun | Diagnostics | Best Researcher Award

Published on by Life Science

Dr. Roseline Ogundokun | Diagnostics | Best Researcher Award 

Dr. Roseline Oluwaseun Ogundokun is a Nigerian computer scientist and researcher specializing in artificial intelligence, deep learning, and medical imaging. She serves as a lecturer and researcher at Landmark University and a postdoctoral fellow in South Africa. With dual doctoral degrees, over a hundred academic contributions, and active roles in international mentorship and editorial boards, she is recognized for her commitment to innovation, education, and sustainable development through cutting-edge research.

Dr. Roseline Ogundokun | Redeemer’s University | Nigeria

Profile

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Education

Roseline Oluwaseun Ogundokun has pursued an extensive academic journey that reflects her passion for computer science and software engineering. She holds a doctoral degree in Computer Science from the University of Ilorin, Nigeria, and is furthering her expertise with another doctoral degree in Software Engineering at Kaunas University of Technology, Lithuania. She has also earned a master’s degree in Computer Science from the University of Ilorin and a bachelor’s degree in Management Information Systems from Covenant University. Her academic development has been enriched through international exposure, including a postdoctoral fellowship at the Tshwane University of Technology in South Africa.

Experience

Roseline has built a distinguished academic and professional career in computer science, blending research, teaching, and mentorship. She serves as a lecturer and researcher at Landmark University, where she has made significant contributions to teaching, curriculum development, and student supervision. Her teaching experience also extends to Thomas Adewumi University and the Nigerian Army College of Education, where she has delivered courses in programming, software engineering, databases, and advanced computing concepts. She began her career as a tutor at Chapel Secondary School, where she taught computer science and mentored young learners. She has consistently advanced knowledge transfer while contributing to the growth and development of institutions she has served.

Awards and Recognition

Her contributions to science and academia have earned her recognition in editorial and professional communities. She serves on the editorial boards of respected journals such as PLOS ONE, Humanities and Social Sciences Communications, and Computers, Materials & Continua. Her role as a reviewer and committee member for international conferences, including IEEE events, highlights her reputation within the global research community. Additionally, her involvement in mentorship initiatives, such as the Empowering Female Minds in STEM program and the Deep Learning Indaba, reflects her commitment to academic excellence, gender empowerment, and capacity building in computer science.

Skills and Expertise

Roseline has developed expertise in programming and advanced computational frameworks. She is proficient in Python and has strong working knowledge of frameworks such as TensorFlow and Keras, which she applies in deep learning and artificial intelligence research. Beyond technical skills, she has demonstrated leadership through administrative roles including curriculum development, quality assurance, and conference organization. She has also excelled in mentoring undergraduate and postgraduate students, guiding them in innovative research projects.

Research Focus 

Her research interests cover a wide spectrum of computer science domains, particularly artificial intelligence, machine learning, deep learning, and data science. She is deeply engaged in applying computer vision and medical imaging techniques to solve real-world problems, especially in the health sector. Her work also extends to image processing, data mining, information security, and the Internet of Medical Things. She has focused on using machine learning and artificial intelligence to create impactful solutions aligned with sustainable development, particularly in healthcare, telecommunications, and industry.

Research Projects

Roseline Oluwaseun Ogundokun has actively contributed to innovative research projects at the intersection of artificial intelligence and healthcare. Her work includes applying machine learning and deep learning models to medical image analysis for early disease detection and diagnosis. She has also developed projects in computer vision, focusing on the recognition and classification of complex image datasets. Beyond healthcare, her projects extend to cybersecurity, data privacy, and intelligent systems that leverage big data for sustainable solutions. She has collaborated with international teams to address pressing challenges in telemedicine, the Internet of Medical Things, and predictive analytics, producing outcomes that support both academic advancement and practical real-world applications.

Publications

IoMT-based wearable body sensors network healthcare monitoring system
Authors: E.A. Adeniyi, R.O. Ogundokun, J.B. Awotunde
Journal: IoT in Healthcare and Ambient Assisted Living

Predictive modelling of COVID-19 confirmed cases in Nigeria
Authors: R.O. Ogundokun, A.F. Lukman, G.B.M. Kibria, J.B. Awotunde, B.B. Aladeitan
Journal: Infectious Disease Modelling

Improved CNN based on batch normalization and adam optimizer
Authors: R.O. Ogundokun, R. Maskeliunas, S. Misra, R. Damaševičius
Journal: International Conference on Computational Science and Its Applications

Application of big data with fintech in financial services
Authors: J.B. Awotunde, E.A. Adeniyi, R.O. Ogundokun, F.E. Ayo
Journal: Fintech with Artificial Intelligence, Big Data, and Blockchain

Medical internet-of-things based breast cancer diagnosis using hyperparameter-optimized neural networks
Authors: R.O. Ogundokun, S. Misra, M. Douglas, R. Damaševičius, R. Maskeliūnas
Journal: Future Internet

Conclusion

Dr. Roseline Oluwaseun Ogundokun stands out as an accomplished researcher whose work bridges advanced computer science with real-world applications in healthcare, data science, and artificial intelligence. Her dual doctoral training, extensive publication record, and international collaborations underscore her global academic impact. Beyond her research, she has demonstrated strong leadership, mentorship, and commitment to sustainable development goals, making her a role model in STEM. With her proven ability to advance innovation and inspire future generations, she is highly deserving of recognition.