Yohanna Kusuma | Multivariate Statistical Analysis | Best Researcher Award

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Dr. Yohanna Kusuma | Multivariate Statistical Analysis | Best Researcher Award

The Royal Melbourne Hospital-The University of Melbourne | Australia

Dr. Yohanna Kusuma is an Australian-trained, internationally recognised neurologist and academic whose clinical and research work bridges acute stroke, neuroimaging, neurosonology, and movement disorders, with a strong translational focus across the Asia-Pacific region. She obtained her neurology specialist qualification from the University of Indonesia with honours, completed advanced fellowships in neurosonology and stroke at leading institutions in Singapore, and earned a PhD from Deakin University supported by an international scholarship, focusing on advanced CT-perfusion imaging in acute ischaemic stroke and the influence of ethnicity on imaging and clinical outcomes. She holds Fellowship of the Royal Australasian College of Physicians, qualifying her as a Consultant Neurologist in Australia. Dr Kusuma serves as Chief Investigator of the AI-powered SERENA platform for real-time stroke triage and decision support, leads the multinational APEX registry on acute ischaemic stroke with cancer spanning nine Asia–Pacific countries, and co-supervises PhD and honours students at Deakin University. She holds senior appointments in both Australia and Indonesia, including Senior Consultant Neurology at Metropolitan Medical Centre Hospital in Jakarta and Senior Research Fellow at The University of Melbourne. Her professional leadership includes representing Indonesia on the Asia Pacific Stroke Organisation and the Asian Stroke Advisory Panel, serving on the Education Council of the Australian Stroke Academy, and having previously served as a Co-opted Board Member of the World Stroke Organisation. Actively engaged in education and training, she has organised and delivered numerous neurosonology and stroke imaging workshops across the Asia-Pacific. Her research output is extensive, with an h-index of 4 and 144 citations, 13 peer-reviewed publications, book chapters, and international presentations. Dr Kusuma exemplifies a clinician-scientist who integrates cutting-edge imaging, neurosonology, and translational stroke research while advancing global collaborations in academic neurology, clinical innovation, and medical education.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Kuruba Chandrakala | Machine Learning and Statistics | Best Researcher Award

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Dr. Kuruba Chandrakala | Machine Learning and Statistics | Best Researcher Award

Siddhartha Academy of Higher Education | India

Dr. Kuruba Chandrakala is an emerging researcher in the domains of computer vision, deep learning, and medical image processing, currently serving as Assistant Professor (Selection Grade) in the CSE department at Siddhartha Academy of Higher Education, Vijayawada. She earned her Ph.D. from NIT Tiruchirappalli, preceded by M.Tech in Computer Science and Engineering with distinction from JNTU Kakinada and B.Tech in the same discipline from JNTU Anantapur. She has qualified both NET and APSET examinations. Her professional trajectory includes roles as Head of Department (CSE-AIML) at Vignan’s Nirula Institute of Technology & Science for Women and previous teaching appointments at VNITSW and SITAM, along with industry experience as a System Engineer with Tata Consultancy Services. Her publication record comprises five Scopus indexed papers, four of which are in SCIE journals, two IEEE conference papers, and one book chapter; she also holds one patent. Her Scopus metrics include an h-index of 4, 10 documents, and 150 citations. Her research has addressed areas such as diabetic retinopathy segmentation, robust blood vessel detection, and image enhancement through deep learning architectures. She teaches courses including Deep Learning, Machine Learning, Big Data Analytics, Cloud Computing, and programming in C, C++, Java, and Python. She has earned numerous certifications from NPTEL, Coursera, Microsoft, IBM, and Wipro and received awards such as the NPTEL Discipline Star and Wipro Project Excellence Award. Her leadership and mentoring roles include serving as a mentor for Wipro TalentNext, nodal officer for Microsoft Upskilling and APSCHE virtual internship programs, and coordinator for various hackathons. She is a life member of professional bodies such as CSI, ISTE, IAENG, and IET, and has delivered several invited and guest lectures, contributing significantly to academic excellence and research advancement.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Chandrakala, K., & Gopalan, N. P. (2025). 3DECNN: A novel method for segmentation of diabetic retinopathy in retinal fundus images using 3D-edge CNN. Neural Computing and Applications.

Kuruba, C., Sharmila, S. K., Mounika, V., Aswini, D., & Poojitha, G. (2023). Three layered security model to prevent credit card fraud using LBPH and CNN-ResNet architecture. International Conference on Hybrid Intelligent Systems, 422–428.

Dharmaiah, K., Mebarek-Oudina, F., Sreenivasa Kumar, M., & Chandra Kala. (2023). Nuclear reactor application on Jeffrey fluid flow with Falkner-Skan factor, Brownian and thermophoresis, non-linear thermal radiation impacts past a wedge. Journal of the Indian Chemical Society, 100(2), 117.

Kuruba, C., & Gopalan, N. P. (2023). Robust blood vessel detection with image enhancement using relative intensity order transformation and deep learning. Biomedical Signal Processing and Control, 86, 105195.

Kuruba, C., Pushpalatha, N., Ramu, G., Suneetha, I., Kumar, M. R., & Harish, P. (2023). Data mining and deep learning-based hybrid health care application. Applied Nanoscience, 13(3), 2431–2437.