Prabhavathy M | Disease Diagnosis |Best Researcher Award

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Dr. Prabhavathy M | Disease Diagnosis |Best Researcher Award

 Dr.Prabhavathy M,Coimbatore Institute of technology,India

Dr. Prabhavathy M. is a distinguished academic and researcher at the Coimbatore Institute of Technology, India. With extensive expertise in engineering and technology, she is known for her contributions to advanced research and innovation in her field. Dr. Prabhavathy has published numerous papers in renowned journals and actively participates in national and international conferences, where her insights have enriched the academic community. Through her teaching and mentorship, she continues to inspire the next generation of engineers and researchers.

Summary:

Assist. Prof. Dr. Manatee Jitanan is a strong candidate for the Research for Best Researcher Award due to his extensive research in global health, public health education, and the innovative use of technology to promote well-being. His multidisciplinary background, long-standing academic career, and research on contemporary health issues are his key strengths. However, focusing more on specialized topics, enhancing international collaborations, and increasing high-impact journal publications could further bolster his candidacy for global recognition.

Professional Profiles:

Scopus

🎓 Education :

Ph.D. in Instrumentation and Control Engineering (ICE), Anna University (2022)
Awarded with “Highly Commended” honors, the Ph.D. in ICE emphasized innovative control strategies in real-world applications, advancing precision and reliability within engineering systems.,Master of Engineering in Computer Science and Engineering, Anna University, Kumaraguru College of Technology, Coimbatore (2011),Graduated with a CGPA of 8.87, attaining “First Class with Distinction.” Specialized in advanced computer science domains, focusing on algorithm optimization and data management technologies.,Bachelor of Engineering in Computer Science and Engineering, Anna University, Government College of Engineering, Salem (2009),Achieved 79%, securing “First Class with Distinction.” The program emphasized foundational and advanced topics in computer science, developing robust software engineering skills and an analytical mindset.

🏢 Experience:

Associate Professor, Coimbatore Institute of Technology (February 2024 – Present)
As an Associate Professor, responsibilities include curriculum development, leading research projects, and mentoring graduate students. A significant focus has been on integrating real-world applications with academic concepts to enhance student engagement.,Assistant Professor, Coimbatore Institute of Technology (May 2014 – January 2024)
With a decade of service, contributed to curriculum design, research advancements, and student mentorship. Developed instructional strategies that bridge theoretical knowledge with practical, industry-aligned applications.,Assistant Professor, Dhirajlal Gandhi College of Technology, Salem (June 2013 – May 2014),Focused on implementing advanced teaching methods to promote student understanding in key areas of computer science. Collaborated on departmental research initiatives and student assessment innovations

🛠️Skills:

Technical Skills,Proficient in Machine Learning, Artificial Intelligence, Deep Neural Networks, Service-Oriented Architecture, and Data Analytics. Extensive knowledge in the development and application of intelligent systems and data-driven solutions.Instructional Skills
Specialized in Curriculum Design, Technological Instruction, Authentic Assessment Development, and Student Counseling and Motivation. Recognized for an ability to tailor instruction to meet diverse learning needs.Interpersonal Skills
Exhibits strong Interpersonal Communication, Organizational Skills, Time Management, and Problem-Solving abilities. Known for building a collaborative environment that fosters learning and innovation.

Research Focus :

With over 14 years of combined academic and industry experience, research has centered on the practical applications of machine learning and explainable AI. Key projects include:,IoT-Based Health Monitoring in ICUs,Developed a patent-published system for real-time patient monitoring in ICU settings, providing critical insights into patient care and alerting mechanisms for healthcare providers.Automatic Video Summarization Using LSTM Architectures,Conducted pioneering research in video content processing using recurrent neural networks, enhancing the efficiency and effectiveness of media management and data analysis.

🔬Awards:

Outstanding Academic Performance,Graduated with “First Class with Distinction” in both Master’s and Bachelor’s degrees in Computer Science and Engineering, demonstrating a consistent record of academic excellence.,Highly Commended Ph.D. Thesis
Recognized by Anna University for a “Highly Commended” Ph.D. thesis, underscoring the innovative nature and impact of research in Instrumentation and Control Engineering.Published Patents in IoT and AI,Holder of several patents for innovations in IoT, neural network architectures, and AI-driven educational tools, highlighting contributions to technological advancements in education and health monitoring.

Conclusion:

Dr. Jitanan is well-suited for the Research for Best Researcher Award, given his significant contributions to public health and health education, especially in response to current global challenges like COVID-19 and firearm violence. His research has practical applications, particularly in improving the well-being of students and vulnerable populations, which aligns with the criteria of impactful, innovative, and community-driven research. With some areas for growth, particularly in international collaboration and high-impact journal outreach, Dr. Jitanan has the potential to make an even greater mark in his field.

Publications :

  • Title: Machine Learning-Based Prediction of Cyclic Voltammetry Behavior of Substitution of Zinc and Cobalt in BiFeO3/Bi25FeO40 for Supercapacitor Applications
    Authors: Ravichandran, A., Raman, V., Selvaraj, Y., Mohanraj, P., Kuzhandaivel, H.
    Source: ACS Omega
    Year: 2024
    Citations: 0

 

  • Title: Evolutionary Discriminative Deep Belief Network Based Diabetic Retinopathy Classification
    Authors: Saranya Rubini, S., Sathya, K., Saveeth, R., Prabhavathy, M.
    Source: Lecture Notes in Networks and Systems
    Year: 2024
    Citations: 0

 

  • Title: Stroke Prediction Using ML and IoT Based Wearable Device
    Authors: Kanagaraj, G., Primya, T., Prabhavathy, M., Saranya, P., Senthilkumar, V.
    Source: AIP Conference Proceedings
    Year: 2023
    Citations: 0

 

  • Title: Meat Dish Image Recognizer: Automatic Categorization of Various Meat Dish Images in Malaysia using Deep Learning Techniques
    Authors: Sumari, P., Raman, V., Prabhavathy, M., Sheng, K.W., Han, S.W.
    Source: 14th International Conference on Advances in Computing, Control, and Telecommunication Technologies
    Year: 2023
    Citations: 0

 

  • Title: Detection of Covid 19/Pneumonia by using Machine Learning Techniques
    Authors: Thilagavathi, G., Lavanya, G., Prabhavathy, M., Saranya, R.
    Source: 14th International Conference on Advances in Computing, Control, and Telecommunication Technologies
    Year: 2023
    Citations: 0

 

  • Title: API Calls Based Malware Detection using Behavior Graphs
    Authors: Prabhavathy, M., Raman, V., Thilagavathi, G.
    Source: 14th International Conference on Advances in Computing, Control, and Telecommunication Technologies
    Year: 2023
    Citations: 0

 

  • Title: An Enhanced Deep Learning Technique for Crack Identification in Composite Materials
    Authors: Ramanathan, S., Sankareswaran, U.M., Mohanraj, P.
    Source: Lecture Notes in Networks and Systems
    Year: 2023
    Citations: 0

 

  • Title: A Novel Approach for Detecting Online Malware Detection LSTM-RNN and GRU Based Recurrent Neural Network in Cloud Environment
    Authors: Prabhavathy, M., Uma Maheswari, S., Saveeth, R., Saranya Rubini, S., Surendiran, B.
    Source: Lecture Notes in Networks and Systems
    Year: 2022
    Citations: 3

 

  • Title: Prevention of runtime malware injection attack in cloud using unsupervised learning
    Authors: Prabhavathy, M., Umamaheswari, S.
    Source: Intelligent Automation and Soft Computing
    Year: 2022
    Citations: 6

 

  • Title: Permission and API calls based hybrid machine learning approach for detecting malicious software in android system
    Authors: Prabhavathy, M., Maheswari, S.U., Saveeth, R., Rubini, S.S.
    Source: Journal of Multiple-Valued Logic and Soft Computing
    Year: 2021
    Citations: 2

 

Venkata Lakshmi Dasari| Deep Learning | Best Researcher Award

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Prof Dr. Venkata Lakshmi Dasari| Deep Learning | Best Researcher Award

Prof Dr. Venkata Lakshmi,VIT-AP University, Andhra Pradesh,India

Prof. Dr. Venkata Lakshmi is a distinguished academician and researcher at VIT-AP University in Andhra Pradesh, India. With a strong background in her field, she has made significant contributions to research and education, mentoring students and collaborating on innovative projects. Her work is recognized both nationally and internationally, making her a prominent figure in her academic community.

Summary:

Prof. Dr. Venkata Lakshmi is a highly qualified candidate with a robust academic background, significant teaching experience, and a strong record of mentoring PhD students. Her dual PhDs in CSE and Mathematics, coupled with over 25 years of academic service, make her a strong contender for the Best Researcher Award. She has demonstrated a commitment to both teaching and research, with recognized achievements in both areas.

Professional Profiles:

Orcid

🎓 Education :

With an impressive academic background, the candidate holds two PhDs—one in Computer Science and Engineering (CSE) from Vellore Institute of Technology University, Chennai Campus (2023), and another in Mathematics from Central University of Hyderabad (2008). Additionally, they completed an MTech in CSE from Acharya Nagarjuna University, Guntur (2010), and an M.Phil. in Mathematics from Central University of Hyderabad (1994-1995). Their educational journey began with a B.Sc. in Mathematics, Physics, and Chemistry (M.P.C) from Acharya Nagarjuna University (1988-1991), followed by an M.Sc. in Mathematics, where they secured the University Second Rank (1991-1993).

🏢Teaching Experience:

The candidate has accumulated over two decades of teaching experience in various academic roles. They began their teaching career as a Lecturer in the Department of Mathematics at Bapatla College for Women (1993-1994) and Bapatla College of Arts and Sciences (1995-1996). They then served at Bapatla Engineering College, first as a Lecturer (1996-2008) and later as an Associate Professor (2008-2009). From 2009 to 2019, they held the position of Vice-Principal at Bapatla Women’s Engineering College, while on deputation from Bapatla Engineering College. The candidate returned to Bapatla Engineering College as an Associate Professor (2019-2021) before transitioning to their current role as a Professor at the School of Computer Science and Engineering, VIT AP University, Andhra Pradesh, since June 2021.

🛠️Skills:

The candidate possesses a diverse skill set, including expertise in Functional Analysis, Harmonic Analysis, Theory of Computation, Machine Learning, and Deep Learning. Their research and teaching proficiency span both Mathematics and Computer Science, with a strong foundation in both theoretical and applied aspects of these fields.

🔬Awards and Achievements:

Throughout their career, the candidate has been recognized for their academic excellence and contributions to research. Notably, they received the Research Award for Publications in Engineering & Advanced Sciences in the academic year 2023-24. Their achievements also include a Silver Medal for outstanding performance in Mathematics during their B.Sc., the Mathematical Sciences Trust Society Prize for securing the top position in M.Sc. (Pure Mathematics) at the University of Hyderabad in 1992, and a Silver Medal for securing the third rank in the Mathematical Olympiad at the postgraduate level, sponsored by the Andhra Pradesh Association of Mathematics Teachers in 1992.

Research Focus:

The candidate’s research focus spans across multiple areas, including Functional Analysis, Harmonic Analysis, Theory of Computation, Machine Learning, and Deep Learning. Their PhD dissertations reflect their deep engagement with these subjects, with their Mathematics dissertation titled “On Vector Valued Amalgam Spaces” and their CSE dissertation titled “Self-replicability of Graphs through Graph Reproduction System.”

Conclusion:

Prof. Dr. Venkata Lakshmi is well-suited for the Best Researcher Award, particularly given her multidisciplinary expertise and extensive teaching and mentorship experience. However, enhancing her publication record with more detailed metrics, expanding interdisciplinary research efforts, and increasing international exposure could further solidify her standing as an outstanding researcher. With these improvements, she would not only be a deserving recipient but also a model researcher with global impact.

Publications :

  • Title: Label-guided Low-rank Approximation for Functional Brain Network Learning in Identifying Subcortical Vascular Cognitive Impairment
    Authors: Jiang, X., Wang, G., Zhang, L., Leone, R.D., Qiao, L.
    Source: Biomedical Signal Processing and Control
    Year: 2024

 

  • Title: Joint Selection of Brain Network Nodes and Edges for MCI Identification
    Authors: Jiang, X., Qiao, L., De Leone, R., Shen, D.
    Source: Computer Methods and Programs in Biomedicine
    Year: 2022

 

  • Title: Estimating High-Order Brain Functional Networks in Bayesian View for Autism Spectrum Disorder Identification
    Authors: Jiang, X., Zhou, Y., Zhang, Y., Qiao, L., De Leone, R.
    Source: Frontiers in Neuroscience
    Year: 2022

 

  • Title: Extracting BOLD Signals Based on Time-Constrained Multiset Canonical Correlation Analysis for Brain Functional Network Estimation and Classification
    Authors: Wang, H., Jiang, X., De Leone, R., Qiao, L., Zhang, L.
    Source: Brain Research
    Year: 2022

 

  • Title: Modularity-Guided Functional Brain Network Analysis for Early-Stage Dementia Identification
    Authors: Zhang, Y., Jiang, X., Qiao, L., Liu, M.
    Source: Frontiers in Neuroscience
    Year: 2021

 

  • Title: Estimating Functional Connectivity Networks via Low-Rank Tensor Approximation with Applications to MCI Identification
    Authors: Jiang, X., Zhang, L., Qiao, L., Shen, D.
    Source: IEEE Transactions on Biomedical Engineering
    Year: 2020

 

  • Title: Completing Missing Exam Scores with Structural Information and Beyond
    Authors: Jiang, X., Zhang, L., Qiao, L.
    Source: Journal of Applied Remote Sensing
    Year: 2019

 

 

 

Xiao Jiang | Medical | Best Researcher Award

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 Dr.Xiao Jiang | Medical | Best Researcher Award

 Dr. Xiao Jiang, Liaocheng University,China

Dr. Xiao Jiang is a distinguished academic at Liaocheng University, China, where he specializes in With a robustDr. Jiang has made significant contributions to [mention notable research, publications, or projects]. His work is recognized for advancing understanding in His research continues to influence

Summary:

Dr. Xiao Jiang is a promising candidate for the Best Researcher Award, with a strong academic background and an impressive portfolio of research achievements. His work in developing innovative methods for brain network analysis and cognitive impairment identification stands out for its technical sophistication and contribution to the field. His leadership in securing and managing significant research projects further demonstrates his capabilities as a researcher.

Professional Profiles:

Scopus

🎓 Education :

Xiao Jiang earned his Ph.D. in Computer Science and Mathematics from the University of Camerino, Italy (October 2020 – June 2024). Prior to that, he completed his Master’s in System Science at Liaocheng University (September 2016 – June 2019) and his Bachelor’s in Mathematics and Applied Mathematics at the same institution (September 2012 – June 2016).

🏢Research Projects:

Brain Function Data Visualization and Classification Learning: Funded by the National Natural Science Foundation of China (Project Approval Number: 62176112, January 2022 – December 2025).,High-Order Regularization Framework for Functional Brain Image Learning and Its Application Research: Funded by the National Natural Science Foundation of China (Project Approval Number: 61976110, January 2020 – December 2023).

🛠️Research Achievements:

Jiang, X., Zhang, L., Qiao, L., Shen, D. (2020). “Estimating Functional Connectivity Networks via Low-rank Tensor Approximation with Applications to MCI Identification.” IEEE Transactions on Biomedical Engineering, 67(7), 1912-1920.,Jiang, X., Qiao, L., De Leone, R., Shen, D. (2022). “Joint Selection of Brain Network Nodes and Edges for MCI Identification.” Computer Methods and Programs in Biomedicine, 225, 107082.,Jiang, X., Wang, G., Zhang, L., Xi, X., De Leone, R., Qiao, L. (2024). “Label-guided Low-rank Approximation for Functional Brain Network Learning in Identifying Subcortical Vascular Cognitive Impairment.” Biomedical Signal Processing and Control, 98, 106766.,Jiang, X., Zhou, Y., Zhang, Y., Zhang, L., Qiao, L., De Leone, R. (2022). “Estimating High-Order Brain Functional Networks in Bayesian View for Autism Spectrum Disorder Identification.” Frontiers in Neuroscience, 16, 872848.

🔬 Research Focus:

Xiao Jiang’s research interests lie at the intersection of Medical Image Analysis, Graph Data Mining, and Machine Learning Applications. His work predominantly explores innovative approaches to functional connectivity networks, brain network analysis, and cognitive impairment identification. Notable projects include estimating functional brain networks for MCI identification and developing label-guided low-rank approximations for brain network learning.

Conclusion:

Given Dr. Jiang’s outstanding research achievements, his technical expertise, and his contribution to advancing the understanding of brain functionality and cognitive disorders, he is a strong candidate for the Best Researcher Award. However, to further strengthen his candidacy, expanding the interdisciplinary and practical applications of his research would enhance his impact in both the academic and clinical communities.

Publications :

  • Title: Label-guided Low-rank Approximation for Functional Brain Network Learning in Identifying Subcortical Vascular Cognitive Impairment
    Authors: Jiang, X., Wang, G., Zhang, L., Leone, R.D., Qiao, L.
    Source: Biomedical Signal Processing and Control
    Year: 2024

 

  • Title: Joint Selection of Brain Network Nodes and Edges for MCI Identification
    Authors: Jiang, X., Qiao, L., De Leone, R., Shen, D.
    Source: Computer Methods and Programs in Biomedicine
    Year: 2022

 

  • Title: Estimating High-Order Brain Functional Networks in Bayesian View for Autism Spectrum Disorder Identification
    Authors: Jiang, X., Zhou, Y., Zhang, Y., Qiao, L., De Leone, R.
    Source: Frontiers in Neuroscience
    Year: 2022

 

  • Title: Extracting BOLD Signals Based on Time-Constrained Multiset Canonical Correlation Analysis for Brain Functional Network Estimation and Classification
    Authors: Wang, H., Jiang, X., De Leone, R., Qiao, L., Zhang, L.
    Source: Brain Research
    Year: 2022

 

  • Title: Modularity-Guided Functional Brain Network Analysis for Early-Stage Dementia Identification
    Authors: Zhang, Y., Jiang, X., Qiao, L., Liu, M.
    Source: Frontiers in Neuroscience
    Year: 2021

 

  • Title: Estimating Functional Connectivity Networks via Low-Rank Tensor Approximation with Applications to MCI Identification
    Authors: Jiang, X., Zhang, L., Qiao, L., Shen, D.
    Source: IEEE Transactions on Biomedical Engineering
    Year: 2020

 

  • Title: Completing Missing Exam Scores with Structural Information and Beyond
    Authors: Jiang, X., Zhang, L., Qiao, L.
    Source: Journal of Applied Remote Sensing
    Year: 2019