Rajesh | Biosensor | Best Researcher Award

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Dr. Rajesh | Biosensor | Best Researcher Award

Chief Scientist at NationalPhysical Laboratory, India

Summary:

Dr. Rajesh is a distinguished chemist with over two decades of experience in the fields of Material Science and Biomedical Metrology. His pioneering research on electroactive materials and bioactive nanomaterials has significantly contributed to advancements in diagnostic devices and medical metrology. With international research experience at renowned institutions like the University of Pennsylvania and the University of California, Riverside, Dr. Rajesh has been at the forefront of innovation in biomedical nanotechnology. His commitment to scientific excellence is demonstrated through his multiple fellowships, awards, and membership in esteemed scientific organizations.

Professional Profile:

👩‍🎓Education:

  • Ph.D. in Chemistry – University of Delhi, India (1998)
  • M.Sc. in Materials Chemistry – J.M. University, New Delhi (1994)
  • B.Sc. in Physics, Chemistry, and Mathematics – J.M. University, New Delhi (1991)

🏢 Professional Experience:

Dr. Rajesh is an accomplished researcher and academic specializing in Material Science and Biomedical Metrology. He has significant expertise in electroactive inorganic/organic materials, bioactive nanomaterials, electrochemistry, conducting polymers, and soft materials. His work is centered on applications of these materials in diagnostic devices such as electrochemical, optical, and field-effect transistor nanobiosensors. Additionally, he is well-versed in biomedical metrology, focusing on the development of medical device standards, testing, and calibration. Over his career, Dr. Rajesh has been recognized internationally through prestigious fellowships from ICMR, IUSSTF, and JSPS, allowing him to collaborate with leading institutions in the USA and Japan. His professional affiliations include memberships in key scientific societies and editorial roles in reputable journals.

Research Interests:

  • Material Science, with a focus on electroactive materials, bioactive nanomaterials, electrochemistry, conducting polymers, and soft materials.
  • Biomedical Metrology, emphasizing the development of standards, testing, and calibration for medical devices.
  • Nanobiosensors, specifically in the areas of electrochemical, optical, and field-effect transistor diagnostic devices for biomedical applications.

Honors and Awards:

  • ICMR International Fellowship for Young Biomedical Scientists (2014) – For advanced research on graphene field-effect transistor nano-devices at the University of Pennsylvania, USA.
  • IUSSTF Research Fellowship Award (2010) – For research on nanobiosensors at the University of California, Riverside, USA.
  • JSPS International Postdoctoral Fellowship Award (2002) – For research on conducting polymers at the Kyushu Institute of Technology, Japan.

Professional Affiliations:

  • Member, Materials Research Society of India (MRSI)
  • Elected Member, National Academy of Sciences, India (MNASc) – 2015
  • Member, Asia Pacific Metrology Program (APMP) Medical Device Metrology Focus Group – Since 2015
  • Editorial Board Member, Applied Biochemistry and Biotechnology (Springer) – 2014-2016
  • Editorial Board Member, Frontiers in Chemistry (Swiss Federal Institute of Technology, Lausanne) – 2016-2018

Author Metrics:

Dr. Rajesh has published extensively in high-impact journals within Material Science and Biomedical Metrology. His work on bioactive nanomaterials and conducting polymers for diagnostic devices is widely cited, contributing to advancements in both academic and industrial applications. His Google Scholar profile demonstrates his influence in the scientific community, with numerous citations and h-index reflecting his contributions to electrochemistry and nanobiosensors.

Top Noted Publication:

A label-free liquid-crystal-droplet based optical sensing platform for the detection of Neisseria gonorrhoeae

  • Authors: R. Kumar, G. Sumanaa, S. Sood, S. S. Pandey, H. Tanaka, and Rajesh*
  • Journal: Journal of Molecular Liquids
  • Publisher: Elsevier
  • Impact Factor: 5.3
  • Status: Accepted, in press (2024)
  • Summary: This research introduces a cutting-edge optical sensing platform utilizing liquid-crystal droplets for label-free detection of the Neisseria gonorrhoeae bacterium, potentially improving diagnostic applications in clinical microbiology.

Smectic layer reorientation by surface mode in surface-stabilized ferroelectric liquid crystal

  • Authors: N. Yadav, D. Goel, A. K. Yadav, A. Choudhary, Rajesh, A. M. Biradar, S. P. Singh
  • Journal: Applied Physics A: Materials Sciences & Processing
  • Publisher: Springer
  • Volume: 130
  • Year: 2024
  • Page: 804
  • Summary: This study explores the reorientation mechanisms of smectic layers in ferroelectric liquid crystals through surface modes. The findings are valuable for enhancing alignment control in liquid crystal displays and photonics.

Domain reorientation due to smectic layer instability in high tilt angle-based surface-stabilized ferroelectric liquid crystal cell

  • Authors: N. Yadav, S. Kumar, A. Choudhary, A. K. Thakur, Rajesh, S. P. Singh, A. M. Biradar
  • Journal: Journal of Applied Physics
  • Publisher: AIP
  • Volume: 135
  • Year: 2024
  • Page: 154701
  • Summary: Investigating domain reorientation in ferroelectric liquid crystals, this paper focuses on instability within smectic layers at high tilt angles, with implications for the stability of liquid crystal devices in various technological applications.

Nanozymes: A comprehensive review on emerging applications in cancer diagnosis and therapeutics

  • Authors: A. Deshwal, K. Saxena, G. Sharma, Rajesh, F.A. Sheikh, C. S. Seth, R. M. Tripathi
  • Journal: International Journal of Biological Macromolecules
  • Publisher: Elsevier
  • Impact Factor: 7.7
  • Volume: 256
  • Year: 2024
  • Page: 128272
  • Summary: This comprehensive review covers the application of nanozymes in oncology, emphasizing their diagnostic and therapeutic potential, which highlights nanozymes as transformative agents in cancer treatment strategies.

Liquid crystal-assisted optical DNA biosensor for the selective detection of bacterium Neisseria gonorrhoeae

  • Authors: Rohit Kumar, Gajjala Sumana, Amit Choudhary, Seema Sood, Rajesh*
  • Journal: Liquid Crystals
  • Publisher: Taylor & Francis
  • Volume: 51
  • Year: 2024
  • Pages: 857-867
  • Summary: This paper describes a liquid crystal-based DNA biosensor developed for the selective detection of Neisseria gonorrhoeae, providing a robust and precise diagnostic method aimed at improving pathogen detection in medical diagnostics.

Conclusion:

Dr. Rajesh is a highly qualified candidate for the Best Researcher Award, with substantial contributions to material science and biosensor development. His research is both innovative and impactful, with potential applications across multiple fields. Although expanding the practical applications of his work and emphasizing technology transfer could further strengthen his profile, his current achievements make him a strong and deserving candidate for this recognition.

 

Nieshkumar Patel | Cyber Security | Best Researcher Award

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Mr. Nimeshkumar Patel | Cyber Security | Best Researcher Award

Sr Network Engineer at Humana Inc, United States 

Summary:

Nimeshkumar Patel is a seasoned network architect and researcher with a rich background in designing secure network infrastructures and implementing cloud solutions. With a solid technical foundation and a commitment to enhancing cybersecurity practices, he has made significant contributions to the field, particularly in developing secure access service edge (SASE) architectures and exploring the potential of quantum computing in information security. Nimesh is also an active contributor to academic literature, having authored multiple papers addressing critical challenges in network security and smart technology integration.

Professional Profile:

👩‍🎓Education:

  • Bachelor of Engineering in Electronics and Communication
  • Quantum Computing Fundamentals & Quantum Computing Algorithms for Cybersecurity, Chemistry, and Optimization
    Massachusetts Institute of Technology xPro, Cambridge, MA (09-2020 to 12-2020)

🏢 Professional Experience:

Nimeshkumar Patel has over 20 years of extensive hands-on experience in network, security, and cloud administration. He currently serves as a Senior Network Architect at Humana Inc., where he is responsible for designing and implementing solutions in data centers, pharmacies, and clinics, including the deployment of a Data Center with EVPN VXLAN Fabric and the design of SASE architectures. Previously, he worked as a Network Engineer V at Synchronoss Technologies Inc., focusing on SD-WAN solutions and cloud migrations. Nimesh has held significant positions in various companies, including ATOS/McGraw-Hill Education, AXIS Telecom in Indonesia, and BT Global Services with NHS UK. His expertise encompasses Cisco, Juniper, Palo Alto, and cloud platforms (AWS, OCI, Azure), with a proven track record in troubleshooting, network design, and implementation across multi-platform environments.

Research Interests:

Nimesh’s research focuses on the intersection of quantum computing and cybersecurity, exploring the application of advanced technologies in enhancing network security, particularly in healthcare information systems. He is also interested in the development of sustainable smart cities through IoT and data analytics.

Top Noted Publication:

  • SECURE ACCESS SERVICE EDGE (SASE): Evaluating the Impact of Converged Network Security Architectures in Cloud Computing
    • Authors: N. Patel
    • Journal: Journal of Emerging Technologies and Innovative Research
    • Volume: 11
    • Issue: 3
    • Pages: e703-e714
    • Citations: 41
    • Year: 2024
  • QUANTUM CRYPTOGRAPHY IN HEALTHCARE INFORMATION SYSTEMS: Enhancing Security in Medical Data Storage and Communication
    • Authors: N. Patel
    • Journal: Journal of Emerging Technologies and Innovative Research
    • Volume: 9
    • Issue: 8
    • Pages: g193-g202
    • Citations: 33
    • Year: 2022
  • Transforming Incident Responses, Automating Security Measures, and Revolutionizing Defence Strategies through AI-Powered Cybersecurity
    • Authors: H. M. Kumar Shukla, N. Patel
    • Journal: Journal of Emerging Technologies and Innovative Research
    • Volume: 11
    • Issue: 3
    • Citations: 23
    • Year: 2024
  • SUSTAINABLE SMART CITIES: Leveraging IoT and Data Analytics for Energy Efficiency and Urban Development
    • Authors: N. Patel
    • Journal: Journal of Emerging Technologies and Innovative Research
    • Volume: 8
    • Issue: 3
    • Pages: 313-219
    • Citations: 18
    • Year: 2021
  • A COMPARATIVE STUDY OF INTERPRETABLE MACHINE LEARNING MODELS FOR ANALYZING HEALTHCARE DATA
    • Authors: K. Shukla, N. Patel, H. Mistry
    • Journal: International Journal of Emerging Technologies and Innovative Research
    • Citations: 6
    • Year: 2024

Conclusion:

Mr. Nimeshkumar Patel stands out as a strong candidate for the Best Researcher Award due to his extensive experience in network architecture, his pioneering research in cybersecurity, and his contributions to critical areas such as quantum computing and smart technology integration. His solid professional background, combined with significant research contributions, underscores his commitment to enhancing cybersecurity practices.

With a few improvements in publication outreach and diversification of research themes, Mr. Patel has the potential to further enhance his impact on the field. His proactive approach to solving real-world cybersecurity challenges positions him as a valuable contributor to both academia and industry, making him deserving of the Best Researcher Award.

 

 

SaiTeja Chopparapu | ECE | Best Paper Award

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Mr. SaiTeja Chopparapu | ECE | Best Paper Award

Assistant Professor at St. PETER’S Engineering College, India

Summary:

Mr. SaiTeja Chopparapu is an enthusiastic researcher and educator with expertise in electronics and communication engineering. With a solid academic background and hands-on experience in IoT, sensor systems, and image processing, he is committed to fostering innovation and critical thinking in the field. Known for his dedication and leadership skills, he aims to contribute to technological advancements and create an engaging learning environment for his students.

Professional Profile:

👩‍🎓Education:

Mr. SaiTeja Chopparapu is a dedicated researcher in Electronics and Communication Engineering, currently in the final stages of his Ph.D. at GITAM University, Visakhapatnam, where he submitted his thesis in October 2023. He earned an M.Tech in Sensor System Technology from Vellore Institute of Technology (VIT), Vellore, in 2019 with a CGPA of 8.49, building upon a B.Tech in Electronics and Communication Engineering from Dhanekula Institute of Engineering and Technology, JNTUK, in 2017. His foundational education includes an Intermediate in MPC from Sri Chaitanya Junior College, Kakinada, where he scored 88.4%, and an SSC from Ratnam High School, Dargamitta, with an aggregate of 84.67%.

🏢 Professional Experience:

Mr. Chopparapu is currently an Assistant Professor at St. Peters Engineering College, JNTUH, where he has been teaching since February 2024. His courses include Digital Electronics, IoT Architecture and Protocols, and Image Processing. With a passion for hands-on education, he has served as a lab in-charge for B.Tech students, mentoring them in programming fundamentals and facilitating discussions to deepen their understanding. His research experience includes a 9-month internship at the Research Centre Imarat (RCI), DRDO, where he developed a GUI for a capacitance-to-voltage converter for capacitive-based sensors. He also completed a 30-day internship at Effectronics Pvt. Ltd., where he was involved in testing and analyzing signaling systems. Over his career, Mr. Chopparapu has participated in more than 40 faculty development programs, covering a variety of topics such as MATLAB, Python, IoT, and technical skill enhancement.

Research Interests:

Mr. Chopparapu’s research interests are centered on sensor systems, IoT, and embedded systems, with an emphasis on IoT architecture and image processing. His dedication to advancing electronics and communication engineering is evident in his academic pursuits, professional roles, and active involvement in technical conferences. He has also expressed a keen interest in developing automation technologies and vehicle control systems.

Top Noted Publication:

“A Hybrid Learning Framework for Multi-Modal Facial Prediction and Recognition Using Improvised Non-Linear SVM Classifier”

  • Authors: C. SaiTeja, J.B. Seventline
  • Journal: AIP Advances, Vol. 13, Issue 2, 2023
  • Citations: 9
  • Abstract: This study presents a hybrid framework that integrates multi-modal inputs to enhance the accuracy of facial prediction and recognition systems. The framework leverages an improvised non-linear Support Vector Machine (SVM) classifier, optimizing recognition rates through a synergistic use of varied input sources.

“An Efficient Multi-Modal Facial Gesture-Based Ensemble Classification and Reaction to Sound Framework for Large Video Sequences”

  • Authors: S.T. Chopparapu, J.B. Seventline
  • Journal: Engineering, Technology & Applied Science Research, Vol. 13, Issue 4, Pages 11263-11270, 2023
  • Citations: 5
  • Abstract: This paper introduces a multi-modal ensemble classification framework that combines facial gesture recognition with sound response mechanisms, specifically designed for extensive video sequences. The framework enhances real-time interactions, addressing performance demands in complex multimedia environments.

“Object Detection Using MATLAB, Scilab, and Python”

  • Authors: S. Chopparapu, B. Seventline
  • Journal: Technology, Vol. 11, Issue 6, Pages 101-108, 2020
  • Citations: 5
  • Abstract: This publication compares the efficacy of object detection across three platforms: MATLAB, Scilab, and Python. By analyzing detection rates, computational efficiency, and implementation complexity, the study provides insights into the adaptability of these platforms for real-time applications.

“GUI for Object Detection Using Voila Method in MATLAB”

  • Authors: S.T. Chopparapu, D.B. Seventline J
  • Journal: International Journal of Electrical Engineering and Technology, Vol. 11, Issue 4, 2020
  • Citations: 4
  • Abstract: This work introduces a graphical user interface (GUI) for object detection utilizing the Viola-Jones method in MATLAB. The study highlights the GUI’s design features, ease of use, and effectiveness for beginner-level applications in image processing.

“Enhancing Visual Perception in Real-Time: A Deep Reinforcement Learning Approach to Image Quality Improvement”

  • Authors: S.T. Chopparapu, G. Chopparapu, D. Vasagiri
  • Journal: Engineering, Technology & Applied Science Research, Vol. 14, Issue 3, Pages 14725-14731, 2024
  • Citations: 2
  • Abstract: This paper explores the use of deep reinforcement learning techniques for enhancing real-time image quality. The proposed approach aims to improve visual perception in dynamic environments, with potential applications in surveillance, autonomous vehicles, and other fields requiring high-quality image processing.

Conclusion:

Overall, Mr. SaiTeja Chopparapu presents a strong case for the Best Paper Award. His impactful publications, coupled with his practical experience in IoT and image processing, are aligned with the award’s objective to recognize innovative contributions in ECE. Addressing the suggested areas for improvement could help maximize the visibility and impact of his work in the field. With his impressive background and dedication, he is well-positioned as a competitive candidate for this award.

 

 

Tarik El Moudden | AI | Best Researcher Award

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Mr. Tarik El Moudden | AI | Best Researcher Award

Tarik El Moudden at Ibn Tofail University, Kenitra, Morocco, Morocco

Summary:

Dr. Tarik El Moudden is a Moroccan-based data scientist and AI specialist, currently serving as a Senior Web Application Developer and Data Analyst at Zenithsoft and a lecturer at Ibn Tofail University. He has extensive experience in neural network frameworks, computer vision, and predictive analytics, leveraging tools such as Python, TensorFlow, and Keras. In addition to his research, he is dedicated to mentoring the next generation of AI professionals and data scientists. He combines a strong academic background with hands-on industry experience, working on complex problems in machine learning, AI integration, and big data analytics.

Professional Profile:

👩‍🎓Education:

Dr. Tarik El Moudden earned his Doctorate in Predictive Modeling using AI and Big Data Analysis from the Computer Science Research Laboratory at Ibn Tofail University, Kenitra, Morocco, in 2024. He holds a DESA (DiplĂ´me d’Études SupĂ©rieures Approfondies) in Advanced Study in Telecommunication and Informatics from the same university, completed in 2008. Dr. El Moudden has also pursued a number of professional certifications, including specialized skills in Power BI, Artificial Intelligence (AI), Python, Data Science, Machine Learning, Deep Learning, and Big Data, powered by IBM Developer Skills Network (2024). He holds certifications from NASA’s Applied Remote Sensing Training (ARSET) program, covering large-scale machine learning applications for agriculture solutions and spectral indices for land and aquatic applications. Additionally, he is certified as a Professional Drone Pilot and in Project Management with AI.

🏢 Professional Experience:

Dr. El Moudden has been a Senior Web Application Developer and Senior Data Analyst and AI Models Integration Specialist at Zenithsoft, Rabat, Morocco, from 2020 to 2024. During his tenure, he developed expertise in neural networks, deep learning, and machine learning models for predictive analytics and data-driven solutions. At Ibn Tofail University, he has taught various modules across different levels, such as Power BI, Data Science, Applied Mathematics, Python Programming, and Machine Learning. He has been involved in teaching these subjects at the Master’s and Professional License levels in fields like Big Data, Artificial Intelligence (AI), Engineering, and Applied Mathematics from 2019 to 2024. His teaching portfolio extends to subjects like Numerical Methods with Python for Master’s students in Partial Differential Equations and Complex Geometry, as well as Applied Mathematics and Optimization for Engineering students.

Research Interests:

Dr. El Moudden’s research primarily focuses on AI integration in predictive modeling, machine learning applications for large-scale agriculture solutions, computer vision, neural networks (CNNs, RNNs, GANs), and data analysis. His work spans image classification, object detection, and image segmentation using Python, TensorFlow, Keras, and PyTorch. He is also passionate about exploring AI’s potential in various industry-specific applications, particularly Big Data, deep learning models, and cloud-based solutions through platforms like Microsoft Azure.

Author Metrics:

  • ORCID: 0000-0002-6963-6686
  • Published Articles: Dr. El Moudden has contributed to scientific publications and is a regular reviewer in the fields of AI, predictive analytics, and machine learning. His research focuses on enhancing AI’s impact on real-world applications, particularly in agriculture and big data. He continues to publish research papers in both local and international conferences.

Top Noted Publication:

Artificial intelligence for assessing the planets’ positions as a precursor to earthquake events

  • Authors: T.E. Moudden, M. Amnai, A. Choukri, Y. Fakhri, G. Noreddine
  • Journal: Journal of Geodynamics, 2024, Volume 162, Article 102057
  • This article explores the use of artificial intelligence to analyze planetary positions in relation to earthquake occurrences, contributing valuable insights into the role of celestial mechanics in earthquake prediction.

New unfreezing strategy of transfer learning in satellite imagery for mapping the diversity of slum areas: A case study in Kenitra city—Morocco

  • Authors: T.E. Moudden, M. Amnai, A. Choukri, Y. Fakhri, G. Noreddine
  • Journal: Scientific African, 2024, Volume 24, Article e02135
  • This open access research focuses on a novel transfer learning approach to analyze satellite imagery for detecting slum areas in Kenitra, Morocco. It highlights advancements in AI and satellite technology for urban mapping.

Building an efficient convolution neural network from scratch: A case study on detecting and localizing slums

  • Authors: T.E. Moudden, M. Amnai
  • Journal: Scientific African, 2023, Volume 20, Article e01612
  • This article presents a case study on developing an effective convolutional neural network (CNN) from scratch, specifically designed for slum detection and localization.

Slum image detection and localization using transfer learning: a case study in Northern Morocco

  • Authors: T. El Moudden, R. Dahmani, M. Amnai, A.A. Fora
  • Journal: International Journal of Electrical and Computer Engineering, 2023, Volume 13(3), Pages 3299–3310
  • This article applies transfer learning techniques to detect and localize slums using satellite imagery, focusing on Northern Morocco as a case study.

Nutrient removal performance within the biological treatment of the Marrakech wastewater treatment plant and characterization of the aeration and non-aeration process

  • Authors: M. Tahri, T. El Moudden, B. Bachiri, M. El Amrani, A. Elmidaoui
  • Journal: Desalination and Water Treatment, 2022, Volume 257, Pages 117–130
  • This article investigates the efficiency of nutrient removal during the biological treatment processes at the Marrakech wastewater treatment plant, providing key insights into water treatment technologies.

Conclusion:

Dr. Tarik El Moudden is a deserving candidate for the Best Researcher Award due to his significant contributions to the field of AI, data science, and machine learning, with a strong focus on practical applications in agriculture, urban development, and disaster prediction. His academic achievements, coupled with his industry expertise, reflect a researcher who is poised to make transformative impacts in the AI landscape. With a bit more focus on expanding his international collaborations and enhancing the visibility of his work, Dr. El Moudden’s research can become even more influential in shaping AI’s future in solving complex, real-world problems.

 

 

Nikhil Suryawanshi | Software Development | Best Researcher Award

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Mr. Nikhil Suryawanshi | Software Development | Best Researcher Award

Principal Software Engineer at ADT, United States
Summary:

Mr. Nikhil Suryawanshi is a seasoned Principal Software Engineer with extensive experience in software development, machine learning, and data analysis. His career spans over a decade, during which he has contributed to numerous high-profile projects across industries, including technology, education, and healthcare. His commitment to quality software solutions, coupled with his passion for research, positions him as a thought leader in his field. Nikhil is also actively engaged in the academic community as a peer reviewer for several international journals, including the Cureus Springer Journal and the International Journal of Innovative Research in Engineering (IJIRE). He continues to contribute to advancements in software engineering and data science.

Professional Profile:

👩‍🎓Education:

He holds two Master’s degrees: an M.S. in Technology Management from Campbellsville University, Kentucky, USA, with a CGPA of 3.5, awarded in 2019, and an M.S. in Computer Science from San Francisco Bay University, California, USA, with a CGPA of 3.94, awarded in 2016. He completed his Bachelor of Engineering in Technology at Sinhgad Academy of Engineering, Pune, India, in 2010, graduating with a CGPA of 3.50.

🏢 Professional Experience:

Nikhil Suryawanshi has amassed over 15 years of experience in the IT industry, currently serving as a Principal Software Engineer at ADT Commercial, CA, USA, since July 2019. He leads a team of eight, providing expertise in software development, project management, and training. His technical proficiencies span across Python, .Net, AngularJS, SQL, and software testing, where he has delivered high-quality software solutions and collaborated in leadership meetings to drive corporate strategy. Previously, he worked as a Senior Software Engineer at the same company, contributing to Python-based software development and network testing.

Earlier in his career, Nikhil was an Analytics Manager at IMRB Abacus, Pune, India (2014–2015), where he led data mining and analysis projects for Unilever brands using SPSS and SQL. Before that, he was an Assistant Professor at Sandip Foundation, Nashik, India (2012–2014), teaching Database Management Systems and Computer Networks, while also guiding students on final-year projects. His industry journey began as a Software Engineer at IMRB Abacus, Mumbai, India (2011–2012), where he designed online surveys and dashboards for statistical analysis.

Research Interests:

Nikhil Suryawanshi’s research interests lie in machine learning, sentiment analysis, and data clustering techniques. He is particularly focused on predictive analytics in healthcare and enhancing diagnostic capabilities using machine learning algorithms. His recent research delves into sentiment analysis with machine learning and deep learning techniques, as well as applications of clustering methods like K-Means and Gaussian Mixture Models in healthcare data.

Author Metrics:

Number of Publications: 6

Significant contributions in fields such as machine learning, healthcare, sentiment analysis, air quality prediction, and consumer behavior.

  • Accurate Prediction of Heart Disease Using Machine Learning: 2024
  • Sentiment Analysis with Machine Learning and Deep Learning: A Survey: 2024
  • Enhancing Breast Cancer Diagnosis Through Clustering: 2023
  • Predicting Mental Health Outcomes Using Wearable Device Data and Machine Learning: 2021 
  • Air Quality Prediction in Urban Environment Using IoT Sensor Data: 2020
  • Predicting Consumer Behavior in E-Commerce Using Recommendation Systems: 2019 

Top Noted Publication:

Accurate Prediction of Heart Disease Using Machine Learning: A Case Study on the Cleveland Dataset

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2024
  • Summary: This paper presents a case study on heart disease prediction using the Cleveland dataset, comparing various machine learning models to assess their accuracy and efficacy in diagnosing heart disease.

Sentiment Analysis with Machine Learning and Deep Learning: A Survey of Techniques and Applications

  • Journal: International Journal of Science and Research Archive
  • Volume: 12
  • Issue: 2
  • Pages: 005-015
  • Year: 2024
  • Summary: The paper provides a comprehensive survey of machine learning and deep learning techniques for sentiment analysis, discussing their applications and performance in various domains such as social media, e-commerce, and customer feedback.

Enhancing Breast Cancer Diagnosis Through Clustering: A Study of K-Means, Agglomerative, and Gaussian Mixture Models

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2023
  • Summary: This research explores clustering algorithms like K-Means, Agglomerative, and Gaussian Mixture Models to enhance the accuracy of breast cancer diagnosis, emphasizing the role of unsupervised learning in medical diagnostics.

Predicting Mental Health Outcomes Using Wearable Device Data and Machine Learning

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2021
  • Summary: The study investigates the application of machine learning on data collected from wearable devices to predict mental health outcomes, focusing on stress, anxiety, and other health indicators.

Air Quality Prediction in Urban Environment Using IoT Sensor Data

  • Journal: International Journal of Innovative Science and Research Technology (IJISRT)
  • Year: 2020
  • Summary: The paper discusses air quality prediction using IoT sensor data in urban areas, applying machine learning models to predict air pollution levels and analyze environmental impacts.

Predicting Consumer Behavior in E-Commerce Using Recommendation Systems

  • Journal: International Journal of Innovative Science and Research Technology
  • Volume: 4
  • Issue: 9
  • Year: 2019
  • Summary: The study focuses on predicting consumer behavior in e-commerce platforms using recommendation systems, highlighting the effectiveness of machine learning in improving customer engagement and personalization.

Conclusion:

Mr. Nikhil Suryawanshi’s strengths in software development, machine learning, and healthcare analytics, combined with his extensive professional experience, make him a solid candidate for the Best Researcher Award. His technical expertise and contributions to the IT and academic communities are commendable. However, expanding his research impact through more collaborative efforts and publishing in top-tier journals could further enhance his candidacy for such an award. Overall, Nikhil is a deserving candidate, particularly given his innovative work in healthcare and predictive analytics.

 

 

 

Ramana Reddy | Electronics Engineering | Most Cited Article Award

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Dr. K.V. Ramana Reddy | Electronics Engineering | Most Cited Article Award

ASSOCIATE PROFESSOR at MALLA REDDY COLLEGE OF ENGINEERING AND TECHNOLOGY, INDIA

Summary:

Dr. K.V. Ramana Reddy is an accomplished academician and researcher with over 8 years of experience in the field of Electrical Engineering. Currently serving as an Associate Professor at Malla Reddy College of Engineering and Technology (Autonomous), his expertise spans power electronics, electric drives, and renewable energy systems. Dr. Reddy is known for his innovative approach to research, which includes exploring advanced technologies in smart grids and electric vehicles. He has previously held leadership roles, including serving as H.O.D., and has been actively involved in mentoring and guiding students through their academic journeys.

Professional Profile:

👩‍🎓Education:

Ph.D. in Electrical Engineering, VIT University, Vellore (2020)

  • Research Focus: Power Electronics and Electric Drives

M.Tech. in Power Electronics & Electric Drives (PE&ED), Jawaharlal Nehru Technological University Anantapur (JNTU-A), A.P. (2011)

  • Sri Venkateswara College of Engineering and Technology (SVCET), Chittoor
  • Grade: 81%

B.Tech. in Electrical and Electronics Engineering (E.E.E.), Jawaharlal Nehru Technological University Anantapur (JNTU-A), A.P. (2009)

  • Sri Mekapati Raja Mohan Reddy Institute of Technology & Science, Udayagiri
  • Grade: 79%

🏢 Professional Experience:

Associate Professor and IIC Coordinator, Malla Reddy College of Engineering and Technology (Autonomous), January 2023 – Present

Associate Professor, Sri Sai Rajeswari Institute of Technology, Proddatur, March 2022 – January 2023

Associate Professor, Sri Sairam College of Engineering, Bangalore, November 2020 – February 2022

Research Scholar, VIT University, Vellore, December 2016 – August 2020

Assistant Professor & H.O.D (Ratified by JNTU-A), Gouthami Institute of Technology & Management for Women, Proddatur, June 2011 – December 2016

Research Interests:

  • Power Electronics
  • Electric Drives
  • Renewable Energy Systems
  • Smart Grids
  • Electric Vehicle Technologies

Dr. K.V. Ramana Reddy’s research primarily focuses on power electronics, electric drives, and renewable energy systems. His work includes the integration of advanced technologies in smart grids and electric vehicle systems, aiming to contribute to sustainable energy solutions. His dedication to academic research and innovative thinking is reflected in his journal publications and his role in guiding students as an academic leader.

Author Metric:

  • Publications: Several peer-reviewed journal articles in reputed journals.
  • Research Citations: A growing number of citations reflecting the impact of his work in the fields of power electronics and renewable energy systems.

Top Noted Publication:

“A review of swarm-based metaheuristic optimization techniques and their application to doubly fed induction generator”

  • Journal: Heliyon
  • Year: 2022
  • Volume: 8, Issue 10
  • Citations: 17

“A review on grid codes and reactive power management in power grids with WECS”

  • Book Chapter: Advances in Smart Grid and Renewable Energy: Proceedings of ETAEERE-2016
  • Year: 2018
  • Citations: 15

“A heuristic approach to optimal crowbar setting and low voltage ride through of a doubly fed induction generator”

  • Journal: Energies
  • Year: 2022
  • Volume: 15, Issue 24
  • Article ID: 9307
  • Citations: 9

“A modified Whale Optimization Algorithm for exploitation capability and stability enhancement”

  • Journal: Heliyon
  • Year: 2022
  • Volume: 8, Issue 10
  • Citations: 9

“An adaptive neuro-fuzzy logic controller for a two-area load frequency control”

  • Journal: International Journal of Engineering Research and Application
  • Year: 2013
  • Pages: 989-995
  • Citations: 8

E.Laxmi Lydia | Computer Science | Best Researcher Award

Posted on by Best Paper Award

Prof. E.Laxmi Lydia, Computer Science, Best Researcher Award

Professor at Velagapudi Ramakrishna Siddhartha Engineering College, Siddhartha Academy of Higher Education (SAHE), India

Summary:

Dr. E. Laxmi Lydia is a seasoned educator and researcher with over 20 years of experience in teaching, training, and research. Currently serving as a Professor and Dean of R&D at Vignan’s Institute of Information Technology, she has significantly contributed to the academic and research community. Dr. Lydia is recognized for her exceptional interpersonal skills, commitment to student development, and active involvement in curriculum design and institutional accreditation processes. Her extensive expertise and numerous accolades, including the Best Researcher Award for five consecutive years, highlight her dedication to advancing knowledge and fostering innovation in the field of computer science and engineering.

Professional Profile:

👩‍🎓Education:

Ph.D. in Computer Science and Engineering (Year not specified)

Master of Computer Applications (MCA) (Year not specified)

Bachelor of Science (B.Sc.) (Year not specified)

🏢 Professional Experience:

Professor & Dean of R&D Vignan’s Institute of Information Technology (A), July 2019 – Present
Dr. E. Laxmi Lydia leads the Research and Development department, overseeing various research initiatives and fostering collaborations both within and outside the institution. She plays an integral role in curriculum development and significantly contributes to the institution’s growth and academic excellence.

Associate Professor Vignan’s Institute of Information Technology (A), 2015 – 2019
In her tenure as an Associate Professor, Dr. Lydia taught both undergraduate and postgraduate courses, guided numerous research projects, and actively participated in various academic committees. Her efforts were pivotal in advancing the research capabilities and academic standards of the institution.

Associate Professor Raghu Engineering College, 2011 – 2015
At Raghu Engineering College, Dr. Lydia conducted lectures, supervised research activities, and contributed significantly to the academic community through her publications and participation in conferences. Her work helped in elevating the research profile and educational quality of the college.

Assistant Professor Ravindra and Rajendra PG College for MCA, 2003 – 2009
During her tenure as an Assistant Professor, Dr. Lydia was responsible for teaching MCA students, developing comprehensive course materials, and mentoring students. Her dedication to teaching and mentorship helped shape the careers of many students in the field of computer science and engineering.

Honors & Certifications:

  • Oracle Certified (2009)
  • Microsoft Certified Solution Developer (MCSD)
  • Outcome-Based Education (OBE) Certified
  • Engineering Education Certification
  • EPICS-Engineering Projects in Community Services Certified
  • Reviewer for JEET Scopus Journal
  • Best Researcher Award (2018, 2019, 2020, 2021, 2022) at Vignan’s Institute of Information Technology
  • Distinguished Faculty in CSE-2021 by Ambitions, an educational entity

Professional Affiliations:

  • Member of the Board of Studies (BOS) at Vignan’s Institute of Information Technology
  • Member of the International Accreditation Council of Quality Education & Research (IACQER)
  • Member of the Computer Society of India

Research Interests:

Dr. Lydia’s research interests encompass a wide range of topics within computer science and engineering, including but not limited to:

  • Artificial Intelligence and Machine Learning
  • Data Science and Big Data Analytics
  • Cybersecurity and Information Assurance
  • Software Engineering and Development
  • Internet of Things (IoT) and Smart Systems

Top Noted Publication:

An Optimal Least Square Support Vector Machine Based Earnings Prediction of Blockchain Financial Products

  • Authors: M Sivaram, EL Lydia, IV Pustokhina, DA Pustokhin, M Elhoseny, GP Joshi
  • Journal: IEEE Access
  • Volume: 8
  • Pages: 120321-120330
  • Year: 2020
  • Citations: 97

Concept of Electronic Document Management System (EDMS) as an Efficient Tool for Storing Document

  • Authors: ATR Rosa, IV Pustokhina, EL Lydia, K Shankar, M Huda
  • Journal: Journal of Critical Reviews
  • Volume: 6
  • Issue: 5
  • Pages: 85-90
  • Year: 2019
  • Citations: 91

Synergic Deep Learning Model–Based Automated Detection and Classification of Brain Intracranial Hemorrhage Images in Wearable Networks

  • Author: EL Lydia
  • Journal: Personal and Ubiquitous Computing
  • Year: 2022
  • Citations: 90

Optimal Deep Learning Based Image Compression Technique for Data Transmission on Industrial Internet of Things Applications

  • Authors: B Sujitha, VS Parvathy, EL Lydia, P Rani, Z Polkowski, K Shankar
  • Journal: Transactions on Emerging Telecommunications Technologies
  • Volume: 32
  • Issue: 7
  • Article: e3976
  • Year: 2021
  • Citations: 84

Data Encryption for Internet of Things Applications Based on Catalan Objects and Two Combinatorial Structures

  • Authors: MH SaraÄŤević, SZ Adamović, VA Miškovic, M Elhoseny, ND MaÄŤek, EL Lydia
  • Journal: IEEE Transactions on Reliability
  • Volume: 70
  • Issue: 2
  • Pages: 819-830
  • Year: 2020
  • Citations: 83

 

Vrushank Mistry | Building Automation Award | Best Researcher Award

Posted on by Best Paper Award

Mr. Vrushank Mistry, Building Automation Award, Best Paper Award

Vrushank Mistry at Air Systems, Inc, United States

Summary:

Mr. Vrushank Mistry is an experienced BAS Field Engineer with a demonstrated history of working in the mechanical or industrial engineering industry. With over six years of professional experience, he specializes in the commissioning and programming of HVAC control systems. Currently employed at Air Systems Inc. in California, Mr. Mistry has played pivotal roles in major projects such as the Google Bayview Campus and multiple buildings on Tasman Drive in San Jose. Prior to his current role, he served as a Controls Project Engineer at ABM Systems Inc. in New York, where he honed his expertise on significant projects including the Newark Airport Terminal 1 and several high-rise buildings in New York. Mr. Mistry holds a Master’s Degree in Mechanical Engineering from the City University of New York and is certified as a Project Management Professional (PMP). His research interests lie in building automation, HVAC control systems, energy efficiency, indoor air quality, IoT technologies, and sensor advancements. Through his work and research, Mr. Mistry is dedicated to advancing sustainable and efficient environmental controls in building operations.

Professional Profile:

Google Scholar Profile

👩‍🎓Education & Qualification:

Professional Experience:  

Mr. Vrushank Mistry has amassed over six years of extensive professional experience in the field of building automation and HVAC control systems. Currently serving as a BAS Field Engineer at Air Systems Inc. in California since September 2021, he specializes in the commissioning and programming of various HVAC control systems. In this capacity, he has played a pivotal role in overseeing key projects such as the Google Bayview Campus and multiple buildings on Tasman Drive in San Jose, CA. His responsibilities encompass a wide range of tasks, including point-to-point checks, DDC programming, BMS database management, and network configuration for HVAC systems. Prior to his current role, Mr. Mistry served as a Controls Project Engineer at ABM Systems Inc. in New York from August 2016 to September 2021. During this tenure, he gained valuable expertise while working on significant projects such as the Newark Airport Terminal 1 and several high-rise buildings in New York. His responsibilities included project management, site commissioning, preventive maintenance, and emergency troubleshooting, highlighting his proactive approach and leadership skills in managing complex projects.

Research Interest:

Mr. Vrushank Mistry’s research interests primarily revolve around building automation and HVAC control systems. He is particularly interested in exploring innovative technologies and strategies to enhance energy efficiency, optimize indoor air quality, and improve overall environmental sustainability in building operations. Additionally, he is interested in researching the integration of IoT technologies, sensor advancements, and data analytics to further enhance the performance and functionality of building management systems.

Publication Top Noted:

Title: Demand Response and HVAC Controls in Smart Grid Integration

  • Author: V. Mistry
  • Journal: Journal of Biosensors and Bioelectronics Research
  • Volume: 4
  • Issue: 4
  • Pages: 1-5
  • Year: 2022

Title: Use of Artificial Intelligence in Optimizing HVAC

  • Author: V. Mistry
  • Journal: International Journal of Science and Research (IJSR)
  • Volume: 10
  • Issue: 4
  • Pages: 1372-1378
  • Year: 2021

Title: Integrating Renewable Energy Sources with HVAC Control Systems

  • Author: V. Mistry
  • Journal: International Journal of Science and Research (IJSR)
  • Volume: 9
  • Issue: 12
  • Pages: 1830-1835
  • Year: 2020

Title: Environmental Impact of HVAC Systems and Mitigation through Automation

  • Author: V. Mistry
  • Journal: International Journal of Science and Research (IJSR)
  • Volume: 9
  • Issue: 11
  • Pages: 1701-1706
  • Year: 2020

Title: Role of Big Data in Enhancing HVAC Operational

  • Author: V. Mistry
  • Journal: International Journal of Science and Research (IJSR)
  • Volume: 9
  • Issue: 4
  • Pages: 1791-1795
  • Year: 2020

 

 

Wadha Abdullah Al-Khater | Computer Science | Best Researcher Award

Posted on by Best Paper Award

Dr. Wadha Abdullah Al-Khater, Computer Science, Best Researcher Award

Doctorate at Qatar University, Saudi Arabia

Summary:

Dr. Wadha Abdullah Al-Khater is a prominent researcher in the field of cybersecurity. She has contributed significantly to the development of malware detection techniques using deep learning models and innovative methodologies. With expertise in cybercrime detection and radio frequency identification methods, Dr. Al-Khater has published several articles and conference papers that have garnered considerable attention in the academic community. Her work has been recognized for its comprehensive review of cybercrime detection techniques, providing valuable insights into addressing contemporary challenges in cybersecurity.

Professional Profile:

Scopus Profile

👩‍🎓Education & Qualification:

PhD in Cyber Security (In Progress)

  • Qatar University
  • Start Date: January 29, 2024

Master’s Degree in Computer Science

  • King Saud University
  • Graduation Date: February 25, 2014
  • GPA: 4.62

Bachelor’s Degree in Computer Science

  • College of Education for Girls at Jubail City, King Faisal University
  • Graduation Date: July 2006
  • Honors: Excellent with Honors

Professional Experience:         

Dr. Wadha Abdullah Al-Khater has amassed a rich academic background with diverse roles across various institutions:

Lecturer at CCQ

  • Duration: August 30, 2016 – Present

Graduate Assistantship at Qatar University

  • Duration: March 31, 2016 – August 31, 2016

Lecturer at University Of Dammam

  • Duration: Since October 2008 (corresponding to 1429 H in the Hijri calendar) until present

Teaching Assistant at University Of Dammam

  • Duration: August 16, 2006 (corresponding to 8/1427 H) – June 13, 2008 (corresponding to 6/1429 H in the Hijri calendar)

IT Instructor

  • Conducted a summer course in the Prince Mohammad Bin Fahd Bin Abdul-Aziz Al Sa’ud program aimed at qualifying and employing Saudi youth from May 21, 2007 to July 1, 2007 (corresponding to 21/5/1427 H – 1/7/1427 H).
  • Taught ICDL Certification at Eqra school in Jubail in 1427 H.
  • Compiled a one-month course at University Of Dammam on combining database with Visual Basic in 1430 H.
  • Compiled courses at University Of Dammam in Photoshop and Successful Strategies for Students Studying aimed at preparatory year students.

Honors and awards:

Dr. Wadha Abdullah Al-Khater’s academic excellence was recognized with First Class Honors in the B.Sc. Program at the College of Education for Girls in Jubail City, which is affiliated with King Faisal University. This achievement underscores her dedication and exceptional performance in her academic pursuits.

 Research Interest:
  • Cybersecurity
  • Information Technology
  • Educational Technology
  • Computer Science Education
  • Digital Learning
  • E-Learning
  • Database Systems
  • Visual Basic Programming
  • Multimedia Technology
  • Educational Strategies and Methods

Publication Top Noted:

Using 3D-VGG-16 and 3D-Resnet-18 deep learning models and FABEMD techniques in the detection of malware

  • Authors: W. Al-Khater, S. Al-Madeed
  • Journal: Alexandria Engineering Journal
  • Year: 2024
  • Volume: 89
  • Pages: 39–52

Comprehensive review of cybercrime detection techniques

  • Authors: W.A. Al-Khater, S. Al-Maadeed, A.A. Ahmed, A.S. Sadiq, M.K. Khan
  • Journal: IEEE Access
  • Year: 2020
  • Volume: 8
  • Pages: 137293–137311
  • Paper ID: 9146148
  • Citation count: 54

A review on Radio Frequency Identification methods

  • Authors: W. Al-Khater, S. Kunhoth, S. Al-Maadeed
  • Conference: 2017 13th International Wireless Communications and Mobile Computing Conference, IWCMC 2017
  • Year: 2017
  • Pages: 1751–1758
  • Paper ID: 7986549
  • Citation count: 5