Jinlei Ma | Digital Transformation | Best Researcher Award

Mr. Jinlei Ma | Digital Transformation | Best Researcher Award

Mr. Jinlei Ma, Harbin Institute of Technology, China

Jinlei Ma is a dynamic and accomplished researcher currently pursuing an MBA at Harbin Institute of Technology (Project 985), with a strong academic background in Vehicle Engineering from China Agricultural University (Project 985). Ranked in the top 10% of his class, he has received numerous prestigious awards including the National Scholarship and Grand Prize Scholarship for Graduate Studies. His multidisciplinary research spans electrowetting of gallium-based liquid metals, flexible thermoelectric generation for wearable devices, and corporate performance in digital transformation contexts. Notably, he has published in top-tier journals such as Materials Horizons (IF=12.2, cited 101 times), Applied Energy (IF=10.1, cited 41 times), and Applied Economics (JCR Q2), and holds a patent for a flexible power generation unit. A recipient of several “Challenge Cup” awards, Jinlei has also presented at international conferences and contributed over 250 hours in volunteer work, reflecting a well-rounded profile of academic excellence, innovation, and social engagement.

Publication Profile

Scopus

Educational Background

Jinlei Ma is currently pursuing his Master of Business Administration at the Harbin Institute of Technology (Project 985), School of Economics and Management (2023.09–2025.06). His coursework includes Advanced Statistics, Technology Innovation Management, and Big Data & AI. He has been recognized with the Grand Prize Scholarship and the National Special Award in the China Undergraduate Research English Speaking Competition. Actively involved in student leadership, he serves as Secretary of the Graduate Party Branch and Vice Class Leader. Jinlei earned his Bachelor’s degree in Vehicle Engineering from China Agricultural University (Project 985) with a GPA of 3.53/4.0, ranking in the top 10%. He received numerous honors such as the National Scholarship, First Prize for Academic Excellence, and was named an Outstanding Graduate. Additionally, he contributed to student welfare as a class counselor and committee member. His volunteer contributions exceed 250 hours, reflecting his strong civic commitment.

Research Contributions

Jinlei Ma has led multiple high-impact research projects across engineering and management disciplines. As project leader, he explored the electrowetting deformation mechanisms of gallium-based liquid metals, resulting in a paper published in Materials Horizons (IF=12.2, cited 101 times) and earned national-level awards in the “Challenge Cup.” He also led the development of flexible thermoelectric power generation technology for wearable devices, culminating in a patent (202010209825.X) and a second-author publication in Applied Energy (IF=10.1, cited 41 times). In a related project, he enhanced energy harvesting through foam copper integration, producing a smart headband system and earning top undergraduate thesis awards. Additionally, his interdisciplinary research on executive equity incentives in the context of digital transformation used Hansen’s threshold regression on data from 1789 Chinese firms, leading to a publication in Applied Economics (JCR Q2). These diverse, data-driven studies showcase his innovation, leadership, and scholarly impact across domains.

Research Focus

Jinlei Ma’s research primarily focuses on advanced functional materials, wearable energy technologies, and interdisciplinary innovation bridging engineering and management sciences. His work in developing high-performance wearable thermoelectric generators reflects a deep interest in energy harvesting systems, emphasizing thermal resistance optimization and voltage conversion for sustainable, human-integrated electronics. He explores the integration of flexible thermoelectric materials, foam copper for enhanced heat dissipation, and smart wearable devices to enable next-generation power solutions. Additionally, his research in liquid metal electrowetting and semiconductor applications showcases an experimental and materials-driven approach to nanotechnology and electronics. Beyond engineering, his interest extends to corporate performance analytics, demonstrated by his econometric study on executive equity incentives during digital transformation. This multidisciplinary blend highlights his unique research niche at the intersection of materials science, wearable technology, renewable energy, and data-driven decision management, making him a forward-thinking researcher in sustainable innovation and smart systems.

Publication Top Notes

📄 “A high-performance wearable thermoelectric generator with comprehensive optimization of thermal resistance and voltage boosting conversion”, Applied Energy, 2022 — Cited by: 38 🔍

K ASHWINI | Computer Science | Best Researcher Award

K ASHWINI | Computer Science | Best Researcher Award

K ASHWINI, National Institute of Technology Rourkela, India

K. Ashwini is a dedicated Ph.D. candidate in Computer Science and Engineering at NIT Rourkela, specializing in deep learning applications for grading diabetic retinopathy. She holds an M.Tech. from VSSUT Burla and a B.Tech. from Synergy Institute of Engineering & Technology, Dhenkanal. Her research includes notable publications, such as her work on CNN-based diabetic retinopathy grading in Biomedical Signal Processing and Control. Skilled in Python, MATLAB, and LaTeX, she has actively participated in workshops on machine learning and signal processing. Ashwini is fluent in Hindi, Telugu, and English.

Publication profile

google scholar

Academic Background

Ms. K. Ashwini is a Research Scholar in Computer Science and Engineering (CSE) at NIT Rourkela, currently pursuing her Ph.D., with her research focused on diabetic retinopathy grading using deep learning techniques. Her advanced studies in deep learning, combined with an M.Tech. in CSE from VSSUT Burla, highlight her dedication to exploring complex topics within biomedical and computational research. She has maintained a strong academic record throughout her studies, underscoring her commitment and expertise in her field.

Research Focus and Publications

Ashwini’s primary research area is in biomedical signal processing, specifically targeting diabetic retinopathy grading using CNNs and soft attention mechanisms. She has contributed a journal article to Biomedical Signal Processing and Control and presented multiple conference papers at reputable IEEE and Springer conferences, indicating her active participation in disseminating her research findings. Notably, her publications demonstrate her capacity to employ and innovate with advanced computational methods for impactful health-related applications, a relevant focus for this award.

Technical Skills and Training

Her technical skill set, including Python, MATLAB, and LaTeX, complements her research competencies. Ashwini’s training in SQL and experience with clustering and fraud detection in mobile networks contribute to a robust and versatile research portfolio. Her academic research skills and fluency in programming languages further solidify her qualifications as a proficient researcher in her domain.

Workshops and Professional Development

Ms. Ashwini has participated in several workshops and short-term training programs across India, including those focused on biomedical signal processing, machine learning, and image processing applications. Her engagement in diverse professional development initiatives, such as faculty development programs and national seminars, showcases her continuous effort to enhance her knowledge base and technical skills.

Publication top notes

Grading diabetic retinopathy using multiresolution based CNN

Soft attention with convolutional neural network for grading diabetic retinopathy

Application of Generalized Possibilistic Fuzzy C-Means Clustering for User Profiling in Mobile Networks

Improving Diabetic Retinopathy grading using Feature Fusion for limited data samples

An intelligent ransomware attack detection and classification using dual vision transformer with Mantis Search Split Attention Network

Check for updates Modified Inception V3 Using Soft Attention for the Grading of Diabetic Retinopathy

Modified InceptionV3 Using Soft Attention for the Grading of Diabetic Retinopathy

Grading of Diabetic Retinopathy using iterative Attentional Feature Fusion (iAFF)

Conclusion

Ms. K. Ashwini exemplifies a suitable candidate for the Research for Best Researcher Award. Her specialized research in diabetic retinopathy grading, supported by a solid academic and technical background, positions her as a promising researcher. Her publications and active participation in workshops further validate her dedication and contributions to biomedical signal processing and computer vision applications, aligning well with the award’s criteria for excellence in research and innovation.