Xiaobin Ling | Data Science | Best Researcher Award

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Dr. Xiaobin Ling | Data Science | Best Researcher Award

UMass Medical School | United States

Publication Profile

Orcid

👨‍🔬 Summary

Dr. Xiaobin Ling is a Postdoctoral Researcher at the RNA Therapeutics Institute, UMass Medical School, specializing in lncRNA structure and Cryo-EM. With a Ph.D. in Structural Biology from Fudan University, his work focuses on the mechanisms of RNA structures, molecular biology, and biophysics, with a strong emphasis on cryo-electron microscopy (Cryo-EM).

🧑‍🏫 Current Position

Postdoctoral Researcher
RNA Therapeutics Institute, UMass Medical School (2024–Present)

  • Research on RNA structures, particularly long non-coding RNAs (lncRNAs).
  • Focus on Cryo-EM techniques to elucidate RNA structural dynamics.

🎓 Education

Ph.D. in Structural Biology (2017–2023)
Fudan University, Shanghai, China

  • Research: Mechanisms and regulation of microRNA biogenesis and lncRNA structure.
    Master’s in Chemical Biology (2013–2016)
    Xiamen University, Xiamen, China
  • Research: Drug mechanisms targeting nuclear receptors.
    B.Sc. in Biotechnology (2008–2013)
    Jinggangshan University, Ji’an, China

💼 Professional Experience

Senior Research Assistant (2022–2023)
Cryo-EM Core Facility, Sichuan University, China

  • Managed operations for Titan Krios G3i, Talos Arctica G2, and JEOL1400 microscopes.
  • Applied Cryo-EM techniques for structural research.

Structural Biologist Researcher (2021–2022)
Runjia Pharmaceutical Technology Co., Ltd, Shanghai, China

  • Investigated ADAR inhibitors and their functions.

Research Assistant (2016–2017)
South University of Science and Technology of China, Shenzhen, China

  • Focused on microRNA biogenesis and its regulation.

📚 Academic Publications

Dr. Ling has authored numerous peer-reviewed publications in top journals, including Nature, Nature Structural & Molecular Biology, and Cell Reports. Notable works include:

  1. Cryo-EM structure of a natural RNA nanocage (Nature, 2025)
  2. Circularly permuted group II introns and their mechanisms (Nature Structural & Molecular Biology, 2025)
  3. Human telomeric G-quadruplex DNA binding (BBA – Gene Regulatory Mechanisms, 2023)
  4. ADAR inhibitors and their function (prepint, 2022)

💡 Technical Skills

  • Cryo-EM: Expertise in cryo-electron microscopy for RNA and protein structural analysis.
  • RNA Structure Analysis: Proficient in the study of RNA folding and dynamics.
  • Molecular Biology: Strong background in RNA and DNA manipulation, including G-quadruplexes and microRNA biogenesis.
  • Computational Tools: Skilled in structural bioinformatics and molecular modeling.

👨‍🏫 Teaching Experience

Dr. Ling has contributed to academic training and mentoring at multiple institutions, particularly in structural biology and RNA research.

🔬 Research Interests On Data Science

  • Structural biology of RNA molecules, focusing on lncRNAs and their roles in gene regulation.
  • Application of Cryo-EM to explore the structural dynamics of RNA and protein complexes.
  • Investigating RNA-related therapeutic strategies, including the use of RNA nanocages and RNA-based drug delivery systems.

 📚 Top Notes Publications

Cryo-EM structure of a natural RNA nanocage
    • Authors: Xiaobin Ling*, Dmitrij Golovenko, Jianhua Gan, Jinbiao Ma*, Andrei A. Korostelev*, Wenwen Fang*
    • Journal: Nature
    • Year: 2025 (accepted)
Structures of a natural circularly permuted group II intron reveal mechanisms of branching and back-splicing
    • Authors: Xiaobin Ling*, Yuqi Yao*, Jinbiao Ma*
    • Journal: Nature Structural & Molecular Biology
    • Year: 2025
The mechanism of UP1 binding and unfolding of human telomeric G-quadruplex DNA
    • Authors: Xiaobin Ling#, Yuqi Yao#, Lei Ding, Jinbiao Ma*
    • Journal: Biochimica et Biophysica Acta (BBA) – Gene Regulatory Mechanisms
    • Year: 2023
DHX9 resolves G-quadruplex condensation to prevent DNA double-strand breaks
    • Authors: Juan Chen#, Xiaobin Ling#, Youshan Zhao#, Sheng Li, Manan Li, Hailian Zhao, Xianguang Yang, Chun-kang Chang, Jinbiao Ma*, Yuanchao Xue*
    • Journal: preprint
    • Year: 2022
Phytochrome B inhibits the activity of phytochrome-interacting factor 7 involving phase separation
    • Authors: Yu Xie, Wenbo Liu, Wenjing Liang, Xiaobin Ling, Jinbiao Ma, Chuanwei Yang, Lin Li*
    • Journal: Cell Reports
    • Year: 2023
Modular characterization of SARS-CoV-2 nucleocapsid protein domain functions in nucleocapsid-like assembly
    • Authors: Yan Wang#, Xiaobin Ling#, Jian Zou, Chong Zhang, Bingnan Luo, Yongbo Luo, Xinyu Jia, Guowen Jia, Minghua Zhang, Junchao Hu, Ting Liu, Yuanfeiyi Wang, Kefeng Lu, Dan Li, Jinbiao Ma*, Cong Liu*, Zhaoming Su*
    • Journal: Molecular Biomedicine
    • Year: 2023

 

Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

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Dr. Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

Korea University Anam Hospital AI Center | South Korea

Publication Profile

Scopus

Google Scholar

INTRODUCTION 🧑‍🎓

Dr. Kwang-Sig Lee is a distinguished academician, research leader, and innovator specializing in the integration of medical and social informatics. Currently serving as Vice Center Chief at the AI Center of Korea University Anam Hospital, Dr. Lee’s groundbreaking research combines artificial intelligence with diverse datasets, such as genetic, image, numeric, and text data. His expertise in AI-driven systems has led to revolutionary work in healthcare, focusing on predictive AI models and multimodal machine learning. His work has earned significant recognition, influencing both academic circles and real-world medical applications.

EARLY ACADEMIC PURSUITS 🎓

Dr. Lee’s academic journey began at Kon Kuk University in Seoul, South Korea, where he earned a Bachelor’s degree in Economics and Physics (1994-1999), with a GPA of 3.52/4.00. He furthered his studies at Iowa State University (1999-2004), earning dual Master’s degrees in Economics and Sociology, graduating with a GPA of 3.69/4.00. Dr. Lee’s pursuit of advanced studies led him to Johns Hopkins University, where he obtained his Ph.D./MSE in Sociology and Applied Mathematics with a focus on health systems, securing a GPA of 3.63/4.00.

PROFESSIONAL ENDEAVORS 💼

Dr. Lee’s professional career spans across multiple prestigious institutions. At present, he holds the role of Vice Center Chief at Korea University’s AI Center in the Medical School. His previous roles include serving as a Research Associate Professor at the same institution, and Senior Research Fellow positions at various research agencies, including Acorn, Enliple, Agilesoda, and National Health Insurance Service. Dr. Lee has also worked as an Assistant Professor at Yonsei University and Sungkyunkwan University, contributing his expertise in preventive medicine and biostatistics.

CONTRIBUTIONS AND RESEARCH FOCUS ON ARTIFICIAL INTELLIGENCE 🧬

Dr. Lee’s contributions to the field of medical and social informatics are vast and impactful. His research primarily focuses on the application of artificial intelligence (AI) in healthcare, especially through the use of machine learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer models. His work explores the integration of genetic, image, numeric, and text data, thereby providing a more holistic approach to solving complex health-related challenges. Dr. Lee is known for his expertise in “Wide & Deep Learning,” a method that synthesizes multiple AI approaches to offer more powerful insights and predictive models.

IMPACT AND INFLUENCE 🌍

Dr. Lee’s innovative research has earned significant recognition both in academic and industrial circles. His work has been published in over 45 SCIE-indexed journals with a combined impact factor of 168. His Field-Weighted Citation Impact is 1.76, surpassing the average citation impact of KAIST in 2021. His expertise is frequently sought in both teaching and consultation, with Dr. Lee being an influential member of various academic committees. His ability to mentor graduate students and lead multidisciplinary research projects has significantly shaped the landscape of AI and healthcare.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Dr. Lee’s extensive publication record spans notable journals such as Cancers, European Radiology, International Journal of Surgery, and Journal of Medical Systems. His contributions have greatly impacted the scientific community, with a robust body of work related to medical AI, health informatics, and predictive modeling. In addition to his research articles, Dr. Lee has served as a guest editor for journals like Frontiers in Bioscience and Applied Sciences, as well as a reviewer for top-tier publications such as Nature Communications and Journal of Big Data.

HONORS & AWARDS 🏆

Throughout his academic career, Dr. Lee has been the recipient of numerous accolades, including full financial support during his tenure at Johns Hopkins University and Iowa State University. Additionally, he has been awarded for his academic excellence during his undergraduate studies at Kon-Kuk University. Dr. Lee’s consistent recognition for research excellence is evident from his impactful publications and active participation in the academic community, including his involvement in major research projects funded by government agencies.

FINAL NOTE ✨

Dr. Kwang-Sig Lee’s career is a testament to his dedication to advancing AI in medicine and social sciences. His expertise in combining machine learning with healthcare applications has paved the way for new innovations in predictive medicine, offering vital contributions to global healthcare systems. As he continues to lead research projects at the AI Center at Korea University, Dr. Lee’s legacy will be defined by his commitment to improving public health through cutting-edge technology and interdisciplinary research.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Dr. Lee’s future endeavors are poised to have a lasting impact on the fields of AI and healthcare. As the Vice Center Chief at one of the top medical schools, his work is expected to advance predictive healthcare models, fostering the development of more personalized and efficient healthcare solutions. With his expertise in “Wide & Deep Learning,” Dr. Lee is likely to continue influencing both the academic community and industry, shaping the future of AI-driven healthcare innovations.

TOP NOTES PUBLICATIONS 📚

Article: Graph Machine Learning With Systematic Hyper-Parameter Selection on Hidden Networks and Mental Health Conditions in the Middle-Aged and Old
  • Authors: K. Lee, Kwang-sig; B. Ham, Byung-joo
    Journal: Psychiatry Investigation
    Year: 2024
Article: A Machine Learning-Based Decision Support System for the Prognostication of Neurological Outcomes in Successfully Resuscitated Out-of-Hospital Cardiac Arrest Patients
  • Authors: S. Lee, Sijin; K. Lee, Kwang-sig; S. Park, Sang-hyun; S. Lee, Sung-woo; S. Kim, Sujin
    Journal: Journal of Clinical Medicine
    Year: 2024
Article: Clinical and Dental Predictors of Preterm Birth Using Machine Learning Methods: The MOHEPI Study
  • Authors: J. Park, Jung-soo; K. Lee, Kwang-sig; J. Heo, Ju-sun; K. Ahn, Ki-hoon
    Journal: Scientific Reports
    Year: 2024
Article: Explainable Artificial Intelligence on Safe Balance and Its Major Determinants in Stroke Patients
  • Authors: S. Lee, Sekwang; E. Lee, Eunyoung; K. Lee, Kwang-sig; S.B. Pyun, Sung Bom
    Journal: Scientific Reports
    Year: 2024

Jing An | Artificial Intelligence | Best Researcher Award

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Dr. Jing An | Artificial Intelligence | Best Researcher Award

Yancheng Institute of Technology, China

👨‍🎓Professional Profile

Scopus Profile

👨‍🏫 Summary

Dr. Jing An is a distinguished professor and master tutor at Yancheng Institute of Technology, China. He specializes in intelligent manufacturing engineering, industrial big data fault diagnosis, and residual life prediction. With numerous patents and software copyrights, Dr. An has published over 20 SCI/EI indexed papers and contributed to key academic texts. His pioneering research in artificial intelligence-based fault diagnosis has earned him prestigious awards, including first-place recognition in the China Commerce Federation Science and Technology Award .

🎓 Education

Dr. An holds a Ph.D. in Computer Science from Hohai University (2021) and a Master’s degree in Computer Science from Harbin University of Science and Technology (2006). His academic foundation has strongly influenced his research in AI and fault diagnosis.

💼 Professional Experience

Having joined Yancheng Institute of Technology in 2006, Dr. An is also the Vice President of Science and Technology for Jiangsu Province’s “Double Innovation Plan.” He has led numerous provincial-level projects, and his expertise has extended to more than 10 industry partnerships 🚀.

📚 Academic Citations

Dr. An has authored over 20 peer-reviewed papers in prestigious journals such as IEEE Access and Mathematical Problems in Engineering. His impactful research on AI-based fault diagnosis methods is frequently cited within the academic community .

🔧 Technical Skills

Dr. An is skilled in AI-based fault diagnosis, deep learning, machine learning, and industrial big data analytics. He has expertise in Convolutional Neural Networks (CNNs) and intelligent manufacturing systems, focusing on improving machinery reliability and efficiency .

🧑‍🏫 Teaching Experience

Dr. An has been recognized as an outstanding teacher twice at Yancheng Institute of Technology. He teaches courses in intelligent manufacturing engineering and industrial big data fault diagnosis, preparing students to advance in the field of AI and data science .

🔍 Research Interests

Dr. An’s research is focused on developing intelligent systems for fault diagnosis in rotating machinery, predictive maintenance, and the application of deep learning techniques in industrial big data. His work aims to enhance manufacturing processes and equipment reliability .

📖Top Noted Publications

Hybrid Mechanism and Data-Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics-Informed Neural Networks

Authors: Cheng, J., Lu, J., Liu, B., An, J., Shen, A.

Journal: Fatigue and Fracture of Engineering Materials and Structures

Year: 2024

Bearing Intelligent Fault Diagnosis Based on Convolutional Neural Networks

Authors: An, J., An, P.

Journal: International Journal of Circuits, Systems and Signal Processing

Year: 2022

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Authors: An, J., Ai, P., Liu, C., Xu, S., Liu, D.

Journal: IEEE Access

Year: 2021

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment

Authors: An, J., Ai, P.

Journal: Mathematical Problems in Engineering

Year: 2020

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning

Authors: An, J., Ai, P., Liu, D.

Journal: Shock and Vibration

Year: 2020

Haixia Mao | Data Science | Best Researcher Award

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Dr. Haixia Mao | Data Science | Best Researcher Award

Shenzhen Polytechnic University, China

👨‍🎓Professional Profile

Scopus Profile

👩‍🏫 Summary

Dr. Haixia Mao is an Associate Professor at the School of Automobile and Transportation at Shenzhen Polytechnic University, China. She holds a Ph.D. in Geographic Information System (GIS) and Remote Sensing from the Hong Kong Polytechnic University. Her research focuses on GIS-T, big data analytics, and analyzing urban mobility patterns, using spatial-temporal data from transportation systems to improve urban planning and human behavior modeling.

🎓 Education

Dr. Mao earned her Ph.D. in GIS and Remote Sensing from the Hong Kong Polytechnic University in 2010. She also completed her M.S. in GIS at Wuhan University in 2004 and her B.S. in Photogrammetry and Remote Sensing from Wuhan University.

💼 Professional Experience

Dr. Mao currently serves as an Associate Professor at Shenzhen Polytechnic University (since 2012), where she has contributed to the development of transportation-related GIS courses. Previously, she worked as a Postdoctoral Researcher at the Hong Kong Polytechnic University from 2014 to 2016, furthering her expertise in urban computing and GIS.

📚 Research Interests

Her research encompasses GIS-T (Geographic Information Systems for Transportation), big data analytics, remote sensing, deep learning, and urban planning. She investigates the mobility patterns of citizens through traffic data (including taxis, buses, and metro) and leverages spatial-temporal data to enhance urban infrastructure and predict human behavior.

🏅 Academic Contributions

Dr. Mao has authored over 20 peer-reviewed journal articles and conference papers. She has also been awarded a patent for a caching system with a new cache placement method. She has received research grants for spatial-temporal data analytics in transportation and has actively contributed to major projects in urban computing.

💻 Technical Skills

Dr. Mao’s technical expertise spans GIS, remote sensing, big data analytics, deep learning, and spatial-temporal data analysis. She integrates these advanced techniques to solve complex transportation and urban planning challenges.

📚 Teaching Experience

Dr. Mao has taught several courses since 2012 at Shenzhen Polytechnic University, including GIS for Transportation, Traffic Engineering Cartography, and Traffic Information Processing. She has a long-standing dedication to educating future professionals in the field of urban planning and transportation technology.

 

📖Top Noted Publications

Multiple sclerosis lesions segmentation based on 3D voxel enhancement and 3D alpha matting

Authors: Sun, Y., Zhang, Y., Wang, X., Zeng, Z., Mao, H.
Journal: Chinese Journal of Medical Physics
Year: 2022

Customer attractiveness evaluation and classification of urban commercial centers by crowd intelligence

Authors: Mao, H., Fan, X., Guan, J., Wang, Y., Xu, C.
Journal: Computers in Human Behavior
Year: 2019

 When Taxi Meets Bus: Night bus stop planning over large-scale traffic data

Authors: Xiao, L., Fan, X., Mao, H., Lu, P., Luo, S.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Characterizing On-Bus WiFi passenger behaviors by approximate search and cluster analysis

Authors: Jiang, M., Fan, X., Zhang, F., Mao, H., Liu, R.
Conference: Proceedings – 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
Year: 2017

Efficient visibility analysis for massive observers

Authors: Wang, W., Tang, B., Fan, X., Yang, H., Zhu, M.
Conference: Procedia Computer Science
Year: 2017

Web access patterns enhancing data access performance of cooperative caching in IMANETs

Authors: Fan, X., Cao, J., Mao, H., Zhao, Y., Xu, C.
Conference: Proceedings – IEEE International Conference on Mobile Data Management
Year: 2016

Shubing Dai | Algorithm Development | Best Researcher Award

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Prof. Shubing Dai | Algorithm Development | Best Researcher Award

Prof. Shubing Dai at Northwest A&F University, China

Professional Profile👨‍🎓

👨‍🏫 Summary

Prof. Shubing Dai is an Associate Professor at Northwest A&F University, specializing in Hydraulic Engineering. With a background in Hydraulics and River Dynamics, he has published over 20 research papers and actively participated in over 20 research projects. His work primarily focuses on urban flood management, hydraulic structures, and water flow dynamics. He is also an active member of key professional organizations, including the China Society for Hydroelectric Engineering and the International Association for Hydro-Environment Engineering and Research (IAHR).

🎓 Education

Prof. Dai began his academic career at Northwest A&F University, where he earned his Bachelor’s (2008–2012) and Master’s (2012–2015) degrees in Hydraulic and Hydroelectric Engineering. He then pursued a Ph.D. in Hydraulics and River Dynamics at Dalian University of Technology (2016–2021). Additionally, he worked as a visiting scholar at the University of La Coruña in Spain (2024).

💼 Professional Experience

Prof. Dai has extensive professional experience, both in academia and industry. He currently serves as an Associate Professor at Northwest A&F University and the Department Secretary of the Hydraulic Engineering Department. He also previously worked as an Assistant Engineer at the Changjiang Survey, Planning, and Design Institute (2015–2016), contributing to several major hydropower and hydraulic engineering projects.

📚 Academic Contributions

Prof. Dai is an active contributor to the academic community, serving as a reviewer for several leading journals such as Journal of Hydrology and Physics of Fluids. He also serves as an editorial board member for an international journal. His research focuses on water resources, hydraulic structures, and flow dynamics, with over 20 published papers and several high-impact research projects.

🔧 Technical Skills

Prof. Dai has developed a range of technical skills, including:

  • Hydraulic Engineering: Focus on energy dissipation and optimization of flood discharge systems.
  • Urban Flooding & Drainage: Expertise in urban drainage system design, stormwater management, and flood mitigation.
  • Flow Dynamics: Proficient in Computational Fluid Dynamics (CFD) and non-steady flow simulations for hydraulic applications.
  • Hydropower Engineering: In-depth research on dam-break flood modeling, hydraulic structures, and their interactions with water flow.

👩‍🏫 Teaching Experience

As a dedicated educator, Prof. Dai mentors master’s students and teaches courses on fluid dynamics, hydraulic modeling, and water resource management. He is also responsible for the administration of the Water Resources and Hydroelectric Engineering department at Northwest A&F University, playing a key role in curriculum development and academic planning.

🔬 Research Interests

Prof. Dai’s research interests are focused on:

  • Hydraulic Engineering: Research on energy dissipation in hydraulic structures and optimization of flood discharge processes.
  • Flood Disaster Management: Urban flood management, drainage systems, and dam-break flood evolution.
  • Non-steady Flow & Hydrodynamics: Investigating the dynamics of free-surface flows, wave behavior, and non-constant flow conditions in hydraulic systems.

🔍 Research Projects

Prof. Dai leads and participates in several important research projects, such as:

  • City Flood and Drainage Systems Simulation (2022–2025)
  • Optimization of Urban Drainage Under Extreme Rainfall Conditions (2023–2025)
  • Dam-Break Flood Evolution and Structural Interaction Studies (2024–2026)
    He is also involved in national and regional projects on hydraulic structure optimization, flood forecasting, and water resource management.

 

📖Top Noted Publications

Numerical study of roll wave development for non-uniform initial conditions using steep slope shallow water equations

Authors: Dai, S., Liu, X., Zhang, K., Liu, H., Jin, S.
Journal: Physics of Fluids
Year: 2024

Discharge coefficients formulae of grate inlets of complicated conditions for urban floods simulation and urban drainage systems design

Authors: Dai, S., Hou, J., Jin, S., Hou, J., Liu, G.
Journal: Journal of Hydrology
Year: 2023

Land Degradation Caused by Construction Activity: Investigation, Cause and Control Measures

Authors: Dai, S., Ma, Y., Zhang, K.
Journal: International Journal of Environmental Research and Public Health
Year: 2022

Numerical investigations of unsteady critical flow conditions over an obstacle using three models

Authors: Dai, S., Jin, S.
Journal: Physics of Fluids
Year: 2022

Interception efficiency of grate inlets for sustainable urban drainage systems design under different road slopes and approaching discharges

Authors: Dai, S., Jin, S., Qian, C., Ma, Y., Liang, C.
Journal: Urban Water Journal
Year: 2021

Razia Sulthana Abdul Kareem – building customised new deep learning algorithms – Best Researcher Award 

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Dr Razia Sulthana Abdul Kareem - building customised new deep learning algorithms - Best Researcher Award 

University of Greenwich - United Kingdom 

Author Profile

Early Academic Pursuits

Dr. Razia Sulthana Abdul Kareem embarked on her academic journey with a Bachelor of Technology in Information Technology, where she showcased exemplary prowess by earning the title of GOLD MEDALIST. She further fortified her academic credentials with a Master of Engineering in Computer Science and Engineering, once again securing the prestigious GOLD MEDALIST accolade. Her pursuit of knowledge didn't stop there; she pursued an MBA in Systems, underscoring her interdisciplinary approach to technology. Driven by a passion for research, she culminated her academic endeavors with a Doctorate in Computer Science and Engineering.

Professional Endeavors

Dr. Razia's professional trajectory spans over 11 years, primarily devoted to imparting knowledge as a Senior Lecturer in Computer Science. She has a knack for delivering interdisciplinary courses tailored for undergraduate and postgraduate students. Her academic stints extend across geographies, including India, Dubai, and the UK, reflecting her global academic footprint.

Contributions and Research Focus

Specializing in Machine Learning and Deep Learning algorithms, Dr. Razia's research endeavors resonate with contemporary challenges. She has ardently delved into the realms of Computational Intelligence, Artificial Intelligence, and Neural Computing. A significant pivot in her research journey involves aligning her work with the United Nations' Sustainable Development Goals, particularly targeting poverty alleviation through agricultural innovation. Collaborative projects with the Natural Resources Institute at the University of Greenwich underscore her commitment to real-world impact, focusing on agricultural challenges like weed identification and fungal infection detection.

Accolades and Recognition

Dr. Razia's academic and research prowess has garnered her several accolades, including the "Best Teacher Award" for pivotal courses like Data Structure and Algorithms, Machine Learning, and Data Analytics. Her initiative in launching the Machine Learning course at Birla Institute of Technology, Dubai, stands testament to her pedagogical innovations, earning her the "Best Faculty Award." Additionally, she has been recognized as the "Best Student Counselor" in both India and Dubai, emphasizing her holistic contribution to academia.

Impact and Influence

With an H-index of 7 and a cumulative impact factor of approximately 24 over the last three years, Dr. Razia's scholarly contributions resonate globally. Her research publications in renowned indices like SCI, SCIE, Scopus, and Web of Science underscore her scholarly impact. Furthermore, her collaborations, totaling 10 joint publications and projects, reflect her expansive academic network and influence.

Legacy and Future Contributions

Dr. Razia Sulthana Abdul Kareem's legacy is characterized by a relentless pursuit of academic excellence, interdisciplinary research, and impactful contributions to society. Her future endeavors are poised to expand upon her existing research frameworks, leveraging AI and machine learning to address pressing environmental and societal challenges. As she continues to mentor the next generation of scholars and innovators, her legacy will undoubtedly transcend academic boundaries, leaving an indelible mark on the realms of Computer Science and Artificial Intelligence.

Notable Publication 

Pushpa-Medical Image Processing, Biomedical Engineering-Best Researcher Award

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Author Profile

Google Scholar

Early Academic Pursuits

Mrs. Pushpa B embarked on her academic journey with a Bachelor's in Electronics and Instrumentation from St. Peter’s Engineering College, affiliated with Anna University, in 2007. Her dedication to the field was evident as she secured a commendable 73%. Building upon this foundation, she pursued an M.Tech in Electronics and Control from SRM University, Chennai, where she achieved a CGPA of 6.99 in 2010. The continuous academic excellence led her to undertake an MBA in Health Service Management from Anna University in 2023. Currently, she is on the verge of completing her Ph.D. in Medical Image Processing & Artificial Intelligence from Annamalai University, with her thesis submitted.

Professional Endeavors

With an illustrious academic background, Mrs. Pushpa B transitioned into academia, where she has made significant contributions. She held the position of Assistant Professor in various esteemed institutions such as B.S. Abdur Rahman Crescent Institute of Science and Technology and Velammal Institute of Technology. During her tenure, she shouldered numerous responsibilities, including curriculum development, university department audit coordination, and acting as a placement coordinator.

Contributions and Research Focus

Mrs. Pushpa B's expertise spans across diverse fields, including Analog Electronic Circuits, Digital Signal Processing, Machine Learning, and more. Her research primarily revolves around Medical Image Processing, Artificial Intelligence, and Bio-medical Instrumentation. Notably, she has undertaken projects like "Detection of Startle Type Epilepsy using Machine Learning Technique" at Global Medical Hospital, Chennai. Her research is widely recognized, with numerous international and national publications and conference presentations to her credit.

Accolades and Recognition

Mrs. Pushpa B's contributions to the academic and research communities have garnered her several accolades. She has published patents, notably one on "Intelligent estimation of liver fat and its stages by using DICOM." Furthermore, her publications in renowned journals like Technology and Health Care and Measurement Sensors, among others, testify to her expertise and recognition in her field.

Impact and Influence

Mrs. Pushpa B's influence extends beyond her academic and research endeavors. She has organized workshops, training programs, and conferences that have facilitated knowledge dissemination and skill enhancement for students, faculty, and industry professionals alike. Her expertise as a reviewer for esteemed platforms like Taylor & FrancisOnline, Elsevier, and IEEE Xplore further amplifies her impact in the scholarly community.

Legacy and Future Contributions

As a dedicated academician and researcher, Mrs. Pushpa B's legacy is marked by her commitment to advancing knowledge in her specialized domains. Her future contributions are anticipated to further bridge the gap between technology and healthcare, particularly in leveraging AI and machine learning techniques for enhanced medical diagnostics and treatments. With her relentless pursuit of excellence, she is poised to inspire future generations of researchers and academicians in the realms of Medical Image Processing and Artificial Intelligence.

In conclusion, Mrs. Pushpa B's academic pursuits, professional endeavors, and contributions to the field of Medical Image Processing and Artificial Intelligence stand as a testament to her passion, expertise, and commitment. Her multifaceted accomplishments underscore her potential to drive significant advancements and make lasting contributions to academia and healthcare.

NOTABLE PUBLICATION