Elena Zaitseva | Data Mining | Best Researcher Award

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Elena Zaitseva | Data Mining | Best Researcher Award

Prof. Dr. Elena Zaitseva, University of Zilina , Slovakia.

Publication profile

Scopus
Googlscholar
Orcid

Education And Experiance

  • šŸŽ“Ā MSc in Computer ScienceĀ (1989) ā€“ Radioengineering Institute, Minsk, Belarus.
  • šŸŽ“Ā Ph.D. in Computer ScienceĀ (1994) ā€“ State University of Informatics and Radioelectronics, Belarus.
  • šŸŽ“Ā Associate Professor in Applied InformaticsĀ (1998) ā€“ Belarus State Economic University.
  • šŸŽ“Ā Professor in Applied InformaticsĀ (2015) ā€“ University of Žilina, Slovakia.
  • šŸ‘©ā€šŸ«Ā Teaching: Courses on Applied Informatics, C++, Neural Networks, Reliability Analysis, and Decision-Making Systems.
  • šŸ§‘ā€šŸ’»Ā Research: Focus on multiple-valued logic, reliability analysis, and data mining applications.

Suitability For The Award

Prof. Dr. Elena Zaitseva is an exceptionally qualified candidate for the Best Researcher Award due to her remarkable academic career, innovative contributions to multiple research domains, and leadership roles in international scientific communities. With over three decades of professional experience, she has made significant advancements in applied informatics, reliability analysis, and multiple-valued logic, among other fields. Her work seamlessly bridges theoretical research and practical applications, particularly in data mining, healthcare reliability, and decision support systems.

Professional DevelopmentĀ 

šŸŒĀ Elena ZaitsevaĀ is a prominent member of various international organizations, including theĀ Gnedenko ForumĀ andĀ IEEE Czechoslovakia Section Reliability Society, where she chairs significant committees. She has been co-editor and editorial board member for several journals, such asĀ Mathematical Problems in EngineeringĀ andĀ Innovative Technologies and Scientific Solutions for Industries. Her leadership extends to steering technical chapters inĀ European Safety and Reliability Association (ESRA). Through her dedication to professional excellence, she mentors researchers worldwide, advances computational reliability, and fosters interdisciplinary collaboration. Her innovative spirit is reflected in her contributions to the reliability and biomedical informatics communities.Ā šŸŒŸ

Research FocusĀ 

Awards and Honors

  • šŸ†Ā ChairĀ of IEEE Czechoslovakia Section Reliability Society Chapter (2018 ā€“ Present).
  • šŸŽ–ļøĀ ChairĀ of ESRA Technical Chapter on Information Technologies and Communication (2011 ā€“ Present).
  • šŸ“œĀ MemberĀ of Editorial Boards for numerous international journals, includingĀ CERESĀ andĀ Mathematical Problems in Engineering.
  • šŸ…Ā Recognized for leadership inĀ Gnedenko ForumĀ and European safety initiatives.
  • šŸŒŸĀ Renowned for her impactful contributions toĀ reliability and statistical studiesĀ in academia and industry.

Publoication Top Notes

  • Review of artificial intelligence and machine learning technologies: Classification, restrictions, opportunities, and challengesĀ (Cited by: 173, Year: 2022)Ā šŸŒŸšŸ¤–
  • Construction of a reliability structure function based on uncertain dataĀ (Cited by: 93, Year: 2016)Ā šŸ“ŠšŸ”
  • Reliability analysis of multi-state system with application of multiple-valued logicĀ (Cited by: 84, Year: 2017)Ā āš™ļøšŸ§®
  • Review of some applications of unmanned aerial vehicles technology in the resource-rich countryĀ (Cited by: 70, Year: 2021)Ā šŸššŸŒ
  • Multiple-valued logic mathematical approaches for multi-state system reliability analysisĀ (Cited by: 66, Year: 2013)Ā šŸ”¢šŸ“
  • Importance analysis by logical differential calculusĀ (Cited by: 65, Year: 2013)Ā šŸ“–āš”
  • A review of continuous authentication using behavioral biometricsĀ (Cited by: 59, Year: 2016)Ā šŸ–„ļøšŸ”‘

Mr. Krish Kumar Raj | Data Mining Awards | Best Researcher Award

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Mr. Krish Kumar Raj | Data Mining Awards | Best Researcher Award

Mr. Krish Kumar Raj, The University of the South Pacific, Fiji

Krish Kumar Raj is a diligent Electrical and Electronics Engineer, currently pursuing a Masterā€™s Degree in Engineering Science at the University of the South Pacific. With a keen interest in power systems, domestic wiring standards, neural networks, and digital control systems, Krish has hands-on experience in hardware and simulation-based research, particularly in bearing fault diagnosis using deep learning strategies. With a Bachelor’s degree in Electrical and Electronics Engineering, Krish has acquired a diverse skill set encompassing power electrical drives, digital signal processing, and mechatronics. His work experience includes internships in electrical engineering firms and contributions to projects such as the development of a low-cost emergency ventilator during the Covid-19 pandemic. Krish is proficient in programming languages like Python and MATLAB, and he holds certifications in machine learning. He is known for his problem-solving abilities, leadership skills, and ability to work under pressure. Outside of work, Krish enjoys swimming, futsal, soccer, table tennis, and hiking.

Professional Profile:

Google Scholar

šŸ“š Education:

Krish Kumar Raj holds an Honors Bachelorā€™s degree in Electrical & Electronics Engineering with a commendable Cumulative GPA of 3.58. His academic journey has equipped him with a deep expertise in various facets of engineering, particularly in Power Systems, Neural Networks, and Digital Control. With a keen interest in leveraging these skills towards practical innovation, Krish is dedicated to pushing the boundaries of traditional engineering practices. Through his academic achievements and hands-on experience, he has demonstrated a strong commitment to excellence and a passion for contributing to advancements in his field.

šŸ‘Øā€šŸ« Employment & Experience:

Krish Kumar Raj’s professional journey encompasses diverse roles, reflecting his dedication to both academia and practical application. As a Part-time Tutor at the University of the South Pacific (USP) in Suva, he imparted knowledge to budding engineers, while also serving as a Lab Demonstrator, providing invaluable practical experience in electrical engineering. Complementing his academic endeavors, Krish gained real-world insights through internships in Electrical Contracting and Industrial Maintenance. These experiences not only enriched his understanding of the field but also honed his troubleshooting skills and ability to apply theoretical knowledge to practical scenarios.

šŸ’» Technical Skillset:

Krish Kumar Raj boasts a versatile technical skill set that spans various software and hardware platforms. Proficient in MATLAB, Python, and AUTOCAD, he navigates complex programming and design tasks with ease. Furthermore, his hands-on experience extends to working with Arduino, Raspberry Pi, and Programmable Logic Controllers (PLC), showcasing his ability to implement innovative solutions in hardware projects. Krish’s expertise also encompasses high and low voltage circuits, demonstrating his competency in handling diverse electrical systems and configurations with precision and proficiency.

Publication Top Notes:

  1. A state-space model for induction machine stator inter-turn fault and its evaluation at low severities by PCA
    • Published: 2021
    • Journal: IEEE Asia-Pacific Conference on Computer Science and Data Engineering
    • Cited by: 5
  2. ECG Multi Class Classification Using Machine Learning Techniques
    • Published: 2023
    • Journal: IEEE International Symposium on Medical Measurements and Applications
    • Cited by: 3
  3. Open Circuit (OC) and Short Circuit (SC) IGBT switch fault detection in three-phase standalone photovoltaic inverters using shallow neural networks
    • Published: 2022
    • Journal: 25th International Conference on Electrical Machines and Systems (ICEMS)
    • Cited by: 3
  4. A LSTM-based Neural Strategy for Diagnosis of Stator Inter-turn Faults with Low Severity Level for Induction Motors
    • Published: 2022
    • Journal: 25th International Conference on Electrical Machines and Systems (ICEMS)
    • Cited by: 3
  5. Enhanced Fault Detection in Bearings Using Machine Learning and Raw Accelerometer Data: A Case Study Using the Case Western Reserve University Dataset
    • Published: 2024
    • Journal: Information

 

 

 

 

Prof Dr. Sathiyabhama Balasubramaniam | Data Mining | Women Researcher Award

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Prof Dr. Sathiyabhama Balasubramaniam | Data Mining | Women Researcher Award

Prof Dr. Sathiyabhama Balasubramaniam, Sona College of Technology, India

šŸŽ“ Dr. B. Sathiyabhama, with qualifications including a B.E., M.Tech., and Ph.D. from the National Institute of Technology, Tiruchirappalli, brings nearly three decades of teaching experience to the table. Her expertise spans Data Mining, Big Data Analytics, Computational Intelligence, and Health Informatics. With 63 publications to her name, she’s a prolific researcher. As Head of the Centre for Data Mining and Database System Design, she leads research and consultancy projects. Dr. Sathiyabhama’s leadership and technical prowess earned her recognition in the AICTE-UKIERI Leadership Development Programme 2020 and a WINNER title in the IITB-ISRO-AICTE Mapathon. šŸ†

Professional Profile:

Scopus

Google Scholar

šŸŽ“ Qualification:

Dr. B. Sathiyabhama holds a B.E., M.Tech., and Ph.D. from the National Institute of Technology, Tiruchirappalli. She completed her M.Tech project internship at the Bioinformatics Centre, IISC, Bangalore, where she obtained a University rank.

šŸ“š Experience:

With 29 years and 10 months of teaching experience, Dr. Sathiyabhama’s expertise spans various domains including Data Mining, Big Data Analytics, Computational Intelligence, Health Informatics, and more.

šŸ“ Publications:

She has contributed to 63 international and national journal and conference publications, demonstrating her research prowess.

šŸ† Major Contributions:

Dr. Sathiyabhama serves as the Head of the Centre for Data Mining and Database System Design, driving research, development, and consultancy projects. She has organized and coordinated various conferences and conventions and actively contributes to professional society activities.

šŸ… Awards and Recognitions:

She was selected as one of the 100 participants for the AICTE-UKIERI Leadership Development Programme 2020 and was recognized as a WINNER in the IITB-ISRO-AICTE Mapathon, showcasing her leadership and technical skills.

Research Interest :

šŸ” Dr. B. Sathiyabhama’s research interests lie at the intersection of Big Data Analytics, Healthcare, and Data Mining. With a keen focus on leveraging data-driven insights to revolutionize healthcare practices, she delves into the vast realms of Big Data to uncover patterns and trends that can enhance medical decision-making and patient outcomes. Her passion for exploring the synergies between technology and healthcare drives her quest to harness the power of data for the betterment of society. šŸ„šŸ’»

šŸ“šĀ Publication Impact and Citations :

Scopus Metrics:

  • šŸ“Ā Publications: 34 documents indexed in Scopus.
  • šŸ“ŠĀ Citations: A total of 295 citations for his publications, reflecting the widespread impact and recognition of Dr. B. Sathiyabhama’s research within the academic community.

Google Scholar Metrics:

  • All Time:
    • Citations: 799 šŸ“–
    • h-index: 15Ā  šŸ“Š
    • i10-index: 25 šŸ”
  • Since 2018:
    • Citations: 595 šŸ“–
    • h-index: 13 šŸ“Š
    • i10-index: 17 šŸ”

šŸ‘Øā€šŸ« A prolific researcher with significant impact and contributions in the field, as evidenced by citation metrics. šŸŒšŸ”¬

Publications Top Notes :

  1. A survey on partition clustering algorithms
    • Published in International Journal of Enterprise Computing and Business Systems in 2011.
    • 103 citations.
  2. Bearing fault diagnosis using wavelet packet transform, hybrid PSO and support vector machine
    • Published in Procedia Engineering in 2014.
    • 69 citations.
  3. A novel feature selection framework based on grey wolf optimizer for mammogram image analysis
    • Published in Neural Computing and Applications in 2021.
    • 60 citations.
  4. T2FL-PSO: Type-2 fuzzy logic-based particle swarm optimization algorithm used to maximize the lifetime of Internet of Things
    • Published in IEEE Access in 2021.
    • 57 citations.
  5. Energy and delay aware data aggregation in routing protocol for Internet of Things
    • Published in Sensors in 2019.
    • 55 citations.