Luciano Alessandro Ipsaro Palesi | Computer Science | Research Excellence Award

Research Excellence Award

Luciano Alessandro Ipsaro Palesi
University of Florence, Italy

Luciano Alessandro Ipsaro Palesi
AffiliationUniversity of Florence
CountryItaly
Scopus ID57226812823
Documents24
Citations282
h-index9
Subject AreaComputer Science
EventInternational Research Awards
ORCID0000-0001-8992-2084

Luciano Alessandro Ipsaro Palesi is a researcher affiliated with the University of Florence whose scholarly activities focus on computer science, artificial intelligence, smart cities, digital twins, intelligent transportation systems, and Internet of Things applications. His publication record demonstrates consistent contributions to data-driven urban intelligence and decision-support technologies. His research profile reflects interdisciplinary collaboration and sustained engagement with emerging computational methodologies.[1]

Abstract

This article summarizes the academic profile and research accomplishments of Luciano Alessandro Ipsaro Palesi. His work emphasizes intelligent mobility, explainable artificial intelligence, digital twin infrastructures, and smart city technologies. Through peer-reviewed publications and collaborative projects, he has contributed to practical solutions addressing urban planning, transportation optimization, and data-centric decision support systems.[2]

Keywords

Artificial Intelligence, Explainable AI, Smart Cities, Digital Twins, Intelligent Transportation Systems, Internet of Things, Deep Learning, Urban Mobility Analytics, Decision Support Systems, Data-Driven Computing.

Introduction

Modern computer science increasingly intersects with urban intelligence and connected infrastructures. Luciano Alessandro Ipsaro Palesi has participated in research addressing these evolving challenges through innovative computational models and scalable architectures. His publications highlight the integration of artificial intelligence with real-world mobility and smart city environments, creating measurable benefits for public services and urban sustainability.[3]

Research Profile

Affiliated with the University of Florence, Palesi has developed a research portfolio spanning digital twins, machine learning, mobility analytics, and Internet of Things ecosystems. His publication metrics include 24 indexed documents, 282 citations, and an h-index of 9. These indicators demonstrate active scholarly engagement and growing influence within applied computer science research communities.[1]

Research Contributions

His contributions include AI-driven traffic optimization, privacy-preserving mobility analysis, digital twin frameworks, and explainable artificial intelligence applications. Research outputs have explored predictive transportation models, public mobility demand matching, smart parking solutions, and urban environmental analytics. These studies support evidence-based decision making for municipalities and intelligent service platforms.[4]

Publications

Recent publications include studies on human-centered artificial intelligence, dynamic mobility demand matching, traffic signal optimization, digital twin architectures, and explainable AI methodologies. His work appears in recognized venues such as IEEE Access, Expert Systems with Applications, Computer Networks, Applied Soft Computing, and Big Data and Cognitive Computing. These publications collectively illustrate a consistent focus on intelligent systems and urban innovation.[5]

Research Impact

The practical orientation of his research has contributed to advancements in mobility management, smart infrastructure monitoring, and AI-enabled public services. Citation activity and collaborations across interdisciplinary teams indicate the relevance of his work within academic and applied settings. His studies support scalable solutions for contemporary urban and technological challenges.[2]

Award Suitability

The International Research Awards recognize individuals demonstrating sustained scholarly achievement and meaningful scientific contributions. Palesi’s publication record, citation performance, and involvement in advanced computational research align with these objectives. His interdisciplinary approach and engagement with emerging technologies support his suitability for recognition within international academic award programs.

Conclusion

Luciano Alessandro Ipsaro Palesi has established a notable academic profile through research focused on intelligent systems, smart cities, and artificial intelligence. His contributions demonstrate technical rigor, practical relevance, and collaborative scholarship. Continued research activity within these domains is expected to further strengthen his academic impact and professional recognition.

References

  1. Elsevier. (n.d.). Scopus author details: Luciano Alessandro Ipsaro Palesi, Author ID 57226812823. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57226812823
  2. Fanfani, M., Ipsaro Palesi, L. A., & Nesi, P. (2026). Human-Centered AI for Decision Support Systems: A Systematic Review of Application Domains, Architecture Designs, Current Trends and Future Directions. Big Data and Cognitive Computing.
    https://doi.org/10.3390/bdcc10060186
  3. Bellini, P., Ipsaro Palesi, L. A., Giovannoni, A., & Nesi, P. (2023). Managing Complexity of Data Models and Performance in Broker-Based Internet/Web of Things Architectures. Internet of Things.
    https://doi.org/10.1016/j.iot.2023.100834
  4. Fereidooni, Z., Ipsaro Palesi, L. A., & Nesi, P. (2025). Multi-Agent Optimizing Traffic Light Signals Using Deep Reinforcement Learning. IEEE Access.
    https://doi.org/10.1109/ACCESS.2025.3578518
  5. Bilotta, S., Ipsaro Palesi, L. A., & Nesi, P. (2025). Exploiting Open Data for CO2 Estimation via Artificial Intelligence and Explainable AI. Expert Systems with Applications.
    https://doi.org/10.1016/j.eswa.2025.128598

Lamia Fourati | Computer Science | Best Researcher Award

Prof Dr. Lamia fourati | Computer Science | Best Researcher Award

Computer science and multimedia higher institute of Sfax | Tunisia

Prof. Lamia Chaari Fourati is a distinguished Professor of Telecommunications at the Higher Institute of Computer Science and Multimedia (ISIMS), Sfax University, Tunisia, and a senior researcher at the Digital Research Center of Sfax (CRNS) within the SM@RTS Laboratory. With over two decades of academic and research excellence, she has established herself as one of North Africa’s leading figures in wireless communications, intelligent network systems, and AI-driven communication technologies. Her research is centered on the design, optimization, and security of wireless networks—including Wireless Body Area Networks (WBANs), Internet of Things (IoT), UAV-based networks (FANETs), and Internet of Vehicles (IoV). She has significantly contributed to developing MAC and routing protocols, trust management frameworks, and privacy-preserving communication systems for next-generation wireless infrastructures. Her innovative work also spans AI, machine learning, reinforcement learning, blockchain, and federated learning, applied to 6G, edge, and cloud computing ecosystems, with a focus on security, reliability, and energy efficiency. Prof. Fourati’s international collaborations are extensive. She serves as a Working Group Member in European COST Actions such as INTERACT (CA20120) and CA22168 on Physical Layer Security for Trustworthy and Resilient 6G Systems. She has led and participated in multiple sponsored projects on AI-based secure frameworks for UAVs, trust management in IoV, and smart water systems, in partnership with institutions like University of Troyes (France) and University of Aveiro (Portugal). Her research has also been pivotal in developing autonomous and energy-efficient communication systems for smart cities, vehicular networks, and healthcare applications. A dedicated educator and mentor, Prof. Fourati has supervised numerous Master’s and Ph.D. theses and has served on national and international doctoral juries. Her global academic engagements include visiting professorships in India, delivering advanced courses on LLMs, generative AI, network security, IoT, and mobile networks, as well as invited tutorials and talks at major IEEE and international events such as NoF, CRiSIS, IEEE ICBC, and ICHI. Her distinguished contributions have earned her prestigious recognitions, including the African Union Kwame Nkrumah Regional Scientific Award (2016), Miss.Africa Seed Fund Award (2018), Burj Kallel Award for Best Researcher (2019), and Outstanding Woman in Tech – North Africa (2021). In 2024, she was named among the Top Tunisian Women in Tech. An IEEE Senior Member and active participant in organizations such as OWSD, N2Women, ISOC, and ITU, Prof. Fourati continues to inspire the next generation of researchers and women in STEM. Her work integrates sustainable development, green computing, and ethical AI, aiming to build a future where intelligent, secure, and inclusive communication systems empower societies globally.

Profiles: Scopus | Orcid

Featured Publications

Fourati, L. C. (2024). Investigation of security threat datasets for intra- and inter-vehicular environments. Sensors, 24(11), 3431. https://doi.org/10.3390/s24113431

Fourati, L. C. (2022). Analysis of LoRaWAN 1.0 and 1.1 protocols security mechanisms. Sensors, 22(10), 3717. https://doi.org/10.3390/s22103717

Fourati, L. C. (2022). A genetic algorithm-based intelligent solution for water pipeline monitoring system in a transient state. Concurrency and Computation: Practice and Experience, 34(21), e5959. https://doi.org/10.1002/cpe.5959

Fourati, L. C. (2022). Cyber-physical systems for structural health monitoring: Sensing technologies and intelligent computing. Journal of Supercomputing, 78, 15126–15153. https://doi.org/10.1007/s11227-021-03875-5

Fourati, L. C. (2022). Investigation on vulnerabilities, threats and attacks prohibiting UAVs charging and depleting UAVs batteries: Assessments and countermeasures. Ad Hoc Networks, 131, 102805. https://doi.org/10.1016/j.adhoc.2022.102805

Fourati, L. C. (2021). 5G network slicing: Fundamental concepts, architectures, algorithmics, projects practices, and open issues. Concurrency and Computation: Practice and Experience, 33(24), e6352. https://doi.org/10.1002/cpe.6352

Fourati, L. C. (2021). A convoy of ground mobile vehicles protection using cooperative UAVs-based system. In 2021 International Symposium on Networks, Computers and Communications (ISNCC) (pp. 1–6). IEEE. https://doi.org/10.1109/ISNCC52172.2021.9615724

Fourati, L. C. (2021). A survey of 5G network systems: Challenges and machine learning approaches. International Journal of Machine Learning and Cybernetics, 12, 1–27. https://doi.org/10.1007/s13042-020-01178-4

Fourati, L. C. (2021). Blockchain-based trust management approach for IoV. In Lecture Notes in Networks and Systems (Vol. 206, pp. 455–467). Springer. https://doi.org/10.1007/978-3-030-75100-5_42

Pritisha Sarkar | Computer Science | Young Scientist Award

Ms. Pritisha Sarkar | Computer Science | Young Scientist Award

Research scholar at NIT Durgapur, India.

Ms. Pritisha Sarkar is a dedicated researcher specializing in machine learning and deep learning within the realm of computer science. Her expertise spans conducting thorough literature reviews, designing and implementing experiments, and analyzing data using statistical methods and programming languages like Python, R, and Java. She applies advanced algorithms to solve complex problems in areas such as natural language processing and computer vision. Collaborative and innovative, Pritisha excels in interdisciplinary environments, contributing effectively to research teams. She communicates her findings effectively through scholarly publications and presentations, demonstrating a commitment to advancing knowledge and technology in her field.

Professional Profiles:

Education

Ms. Pritisha Sarkar is currently pursuing her Ph.D. in Computer Science at NIT Durgapur, focusing on machine learning and deep learning. She completed her B.Tech in Information Technology from the Government College of Engineering and Leather Technology under M.A.K.A.U.T, Kolkata, graduating in 2016 with a DGPA of 7.84. Continuing her academic journey, she pursued an M.Tech in Computer Science at the National Institute of Technical Teachers’ Training & Research, Kolkata, graduating in 2018 with a DGPA of 8.15. Pritisha’s educational background highlights her dedication to advancing her expertise in computer science, particularly in machine learning and deep learning.

Research Interest

Ms. Pritisha Sarkar’s research interests encompass machine learning and deep learning, particularly focusing on advanced algorithms, neural networks, and their applications in areas such as natural language processing, computer vision, and data analytics. Her academic pursuits and ongoing Ph.D. research at NIT Durgapur underscore her commitment to exploring these technologies and their practical implementations.

Research Skills

Ms. Pritisha Sarkar excels in a wide array of research skills cultivated throughout her academic and professional journey. Her expertise includes conducting comprehensive literature reviews to discern existing research trends and identify areas for exploration. She is adept at designing and executing experiments to validate hypotheses and advance scientific knowledge. Proficient in data analysis using statistical methods and programming languages like Python, R, and Java, she applies these skills to extract meaningful insights from complex datasets. Specializing in machine learning and deep learning, Pritisha employs advanced algorithms to address intricate challenges in domains such as natural language processing and computer vision. Her problem-solving abilities and analytical mindset enable her to innovate and develop impactful solutions. Collaborative by nature, she thrives in interdisciplinary environments, contributing effectively to research teams. Pritisha communicates her findings with clarity and precision through scholarly papers, presentations, and discussions, ensuring her research makes a significant impact in the field of computer science.

Publications

  • Optimizing air quality monitoring device deployment: a strategy to enhance distribution efficiency
    • Authors: P. Sarkar, M. Saha
    • Journal: International Journal of Information Technology (Singapore)
    • Year: 2024
    • Volume: 16
    • Issue: 5
    • Pages: 2981–2985
  • Machine learning-based detection of sudden air pollutant level changes: impacts on public health
    • Authors: P. Sarkar, M. Saha
    • Journal: International Journal of Information Technology (Singapore)
    • Year: 2024
    • Article in Press
  • Impact of bursting fireworks during Diwali in Durgapur suburb, India: A case study
    • Authors: P. Sarkar, M.K. Makkena, A. Bose, S. Saha, M. Saha
    • Conference: ACM International Conference Proceeding Series
    • Year: 2023
    • Pages: 384–389
    • Citations: 2
  • Analyzing the Severity of Air Pollution in an Industrialized Suburb
    • Authors: P. Sarkar, M.K. Makkena, S. Saha, M. Saha
    • Conference: 14th International Conference on Computing Communication and Networking Technologies (ICCCNT 2023)
    • Year: 2023
  • City-wide Spatio-temporal Effect on AQI
    • Authors: P. Sarkar, S. Ahmed, A. Bose, S. Saha, M. Saha
    • Conference: Proceedings of 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2022)
    • Year: 2022
    • Pages: 13–18
    • Citations: 2
  • Nature-Inspired Computing Behaviour of Cellular Automata
    • Authors: M. Ghosh, P. Sarkar, M. Saha
    • Book: Lecture Notes in Electrical Engineering
    • Year: 2021
    • Volume: 694
    • Pages: 137–149
    • Citations: 1
  • An Intelligent Technique to Find Bicliques and its Application to Optimum Matching Problem
    • Authors: P. Sarkar, K. Giri
    • Conference: International Conference on Emerging Trends in Information Technology and Engineering (ic-ETITE 2020)
    • Year: 2020
    • Article ID: 9077790
    • Citations: 1

 

Venkata Praveen Kumar Kaluvakuri | Computer Science | Best Researcher Award

Mr. Venkata Praveen Kumar Kaluvakuri | Computer Science | Best Researcher Award

Senior Software Engineer at Technology Partners Inc, United States.

Venkata Praveen Kumar Kaluvakuri is an accomplished Oracle Certified Java/J2EE Software Developer with over 13 years of experience in crafting customized solutions for web-based applications. Throughout his career, he has been actively involved in all phases of the Software Development Life Cycle (SDLC), from requirement analysis and design to implementation, testing, and support. Venkata possesses strong proficiency in Java programming, with expertise in functional programming, lambda expressions, and design patterns. He has demonstrated his skills in developing UI applications using NodeJs and Angular, and has extensive experience in building and managing cloud infrastructure on AWS, employing services like EC2, S3, and Lambda.

Professional Profiles:

Education

Venkata Praveen Kumar Kaluvakuri holds a Master of Science in Computer Science from the University of Central Missouri and a Bachelor of Technology from Jawaharlal Nehru Technological University Kakinada, India. He is also an Oracle Certified Java Programmer, adding a significant credential to his extensive academic background.

Professional Experience

Venkata Praveen Kumar Kaluvakuri, a seasoned software engineer with over 13 years of experience, specializes in Java, cloud environments, and AI/ML integration. At Enterprise Fleet Management, he developed high-performance UI pages, migrated applications to AWS, and implemented microservices. At MasterCard, he contributed to developing RESTful services and automation testing. His work at Wells Fargo involved enhancing UIs and developing web services, while his tenure at Vienna Infosys focused on J2EE design patterns and web services. With expertise across multiple frameworks and technologies, Praveen excels in delivering robust, scalable software solutions.

Research Interest

Venkata Praveen Kumar Kaluvakuri’s research interests lie in the intersection of software development and emerging technologies. He is particularly focused on the integration of AI/ML techniques in cloud environments to solve complex cybersecurity problems. Additionally, he is interested in optimizing performance in web-based applications, leveraging functional programming, and exploring the potential of serverless architectures in AWS. Praveen is also keen on advancing the use of microservices and developing innovative solutions for enterprise-level challenges, constantly seeking to enhance the efficiency and security of software systems.

Award and Honors

Venkata Praveen Kumar Kaluvakuri has earned several awards and honors throughout his career, highlighting his dedication and excellence in the field of software development. He is an Oracle Certified Java Programmer, a testament to his expertise in Java programming. His outstanding performance and contributions to project success have earned him the Employee of the Month award multiple times at Enterprise Fleet Management. At MasterCard, he was honored with the Outstanding Project Award for leading and completing a critical project on time and within budget. Additionally, he received the Innovation Excellence Award at Wells Fargo for developing innovative solutions and improving the efficiency of web-based applications. His exceptional teamwork and collaboration on high-impact projects at Computer Sciences Corporation, India, earned him the Team Excellence Award.

Research Skills

Venkata Praveen Kumar Kaluvakuri has developed a robust set of research skills over his career in software development and IT solutions. With a keen focus on problem-solving and analysis, he excels in dissecting complex issues and devising innovative solutions. His expertise extends to experimental design, where he applies rigorous methodologies to evaluate software performance, scalability, and reliability. Venkata is adept at data analysis, employing advanced tools to extract valuable insights from large datasets, crucial for optimizing software functionalities and user experiences. Additionally, he maintains a strong grasp of current research trends through meticulous literature reviews, ensuring he remains at the forefront of software development methodologies, frameworks, and technologies. With strong technical writing abilities, Venkata effectively communicates his findings, prepares detailed technical reports, and contributes to scholarly publications. His collaborative spirit and adeptness in cross-functional teamwork further underscore his ability to drive innovation and project success in diverse professional environments.

Publications

  1. SECURING THE SERVERLESS FRONTIER: A JAVA FULL STACK PERSPECTIVE ON AI/ML INTEGRATION IN THE CLOUD
    • Authors: VP Peta, SKR Khambam, VPK Kaluvakuri
    • Year: 2023
    • Journal: International Journal For Advanced Research In Science & Technology
    • Volume: 13
    • Issue: 07
    • Citations: Not specified
  2. AI-DRIVEN ROOT CAUSE ANALYSIS FOR JAVA MEMORY LEAKS
    • Authors: VPK Kaluvakuri, VP Peta, SKR Khambam
    • Year: 2022
    • Journal: International Journal For Innovative Engineering and Management Research
    • Volume: 12
    • Issue: Not specified
    • Citations: Not specified
  3. The Cloud as A Financial Forecast: Leveraging AI For Predictive Analytics
    • Authors: SKR Khambam, VPK Kaluvakuri, VP Peta
    • Year: 2022
    • Journal: International Journal For Recent Developments In Science & Technology
    • Volume: 6
    • Issue: 08
    • Citations: Not specified
  4. Serverless Java: A Performance Analysis for Full-Stack AI-Enabled Cloud Applications
    • Authors: VPK Kaluvakuri, VP Peta, SKR Khambam
    • Year: 2021
    • Journal: International Journal For Recent Developments in Science & Technology
    • Volume: 5
    • Issue: 05
    • Citations: Not specified

 

 

 

Vilas Gaikwad | Computer Science | Best Researcher Award

Dr. Vilas Gaikwad | Computer Science | Best Researcher Award

Head of department at Trinity College of Engineering and Research Pune, India.

Dr. Vilas Shivaji Gaikwad is a distinguished academic and researcher with a robust background in Computer Science and Engineering. He earned his PhD from Dr. Babasaheb Ambedkar Marathwada University (Dr. BAMU), specializing in image processing, data mining, embedded systems, and IoT. With over a decade of experience in academia, Dr. Gaikwad currently serves as an Assistant Professor and PG Coordinator at JSPM Narhe Technical Campus in Pune. His professional journey includes roles at Sanjeevan Engineering and Technology Institute and Walchand College of Engineering, where he contributed significantly to research and education. Dr. Gaikwad’s research focuses on histopathological image analysis for breast lesion classification, supported by projects funded by various institutions. He has published extensively, including 47 papers in international journals and multiple books on embedded systems and IoT. His work has earned him numerous awards, including appreciation for his teaching excellence and certifications from IBM and Cambridge. Dr. Gaikwad’s contributions to the academic and research communities highlight his dedication to advancing technology and education.

Professional Profiles:

Education

Dr. Vilas Shivaji Gaikwad holds a Ph.D. in Computer Science & Engineering from Dr. BAM University, Aurangabad, completed in May 2021. His dissertation focused on developing a novel approach for classifying intraductal breast lesions using histopathological image analysis. He earned his M.Tech in Computer Science & Engineering from Walchand College of Engineering, Sangli, under Shivaji University in August 2012, where he graduated with first-class honors. Additionally, he completed his B.E. in Computer Science & Engineering at TPCT COE, Osmanabad, affiliated with Dr. BAM University, in August 2010, achieving distinction in his studies.

Professional Experience

Dr. Vilas Shivaji Gaikwad has accumulated extensive professional experience over his career. Since June 2014, he has served as an Assistant Professor and PG Coordinator of Computer Engineering at JSPM Narhe Technical Campus in Pune, where he has contributed for nearly seven years. Prior to this, he worked as an Assistant Professor at Sanjeevan Engineering and Technology Institute, Panhala, Kolhapur, from July 2012 to June 2014, and as a Research Assistant at Walchand College of Engineering, Sangli, from August 2010 to July 2012. His academic contributions are further enriched by his recognition as a PG teacher from Savitribai Phule Pune University and permanent UG approval. Overall, Dr. Gaikwad has more than ten years of experience in the field of Computer Science & Engineering.

Research Interest

Dr. Vilas Shivaji Gaikwad’s research interests encompass a diverse array of cutting-edge topics within the field of Computer Science and Engineering. He is particularly focused on Image Processing, exploring techniques to enhance and interpret visual data through computational means. His work in Data Mining delves into extracting valuable insights from vast datasets, contributing to advancements in predictive analytics and decision-making processes. Additionally, Dr. Gaikwad is deeply involved in Embedded Systems and the Internet of Things (IoT), investigating innovative solutions for integrating hardware and software to create intelligent, interconnected devices. His Ph.D. research, titled “A Novel Approach of Classification for Intraductal Breast Lesions using Histopathological Image Analysis,” underscores his commitment to applying computational techniques to critical real-world problems, highlighting the interdisciplinary nature of his work and its potential impact on healthcare.

Award and Honors

Dr. Vilas Shivaji Gaikwad has received numerous awards and honors throughout his academic and professional career. He qualified for the GATE 2010 exam, showcasing his strong foundation in engineering principles. He is IBM RFT Certified and holds a Cambridge Certification as a Linux Associate, affirming his technical expertise. Dr. Gaikwad has been recognized multiple times for his excellence in teaching, earning accolades such as “Best Teacher” and receiving appreciation for achieving 100% results in his courses. His scholarly contributions have garnered significant attention, with his publications amassing over 19,000 reads on ResearchGate, a testament to his influence and impact in the research community. These recognitions underscore Dr. Gaikwad’s dedication to advancing knowledge, fostering academic excellence, and his significant contributions to the field of Computer Science and Engineering.

Research Skills

Dr. Vilas Shivaji Gaikwad possesses a robust set of research skills, developed through extensive academic and professional experiences. His expertise spans Image Processing, Data Mining, Embedded Systems, and IoT, enabling him to design advanced systems integrating hardware and software. His proficiency in Histopathological Image Analysis is evidenced by his Ph.D. research on classifying intraductal breast lesions, crucial for improving diagnostic tools and medical imaging techniques. Dr. Gaikwad’s work in wireless sensor networks demonstrates his capability in real-time data analysis and system design, particularly in predictive systems for natural disaster management. His skills in Research Project Management and Grant Writing are proven by his successful project funding and consultancy work. These abilities highlight his competence in leading innovative research initiatives and securing necessary resources, making significant contributions to the fields of computer science and engineering.

Publications

  • Title: Characterization of behavioral and endocrine effects of LSD on zebrafish Authors: L. Grossman, E. Utterback, A. Stewart, S. Gaikwad, K.M. Chung, C. Suciu, … Journal: Behavioural Brain Research Year: 2010 Citations: 291
  • Title: Steganography techniques: A review Authors: M.P.R. Kamble, M.P.S. Waghamode, M.V.S. Gaikwad, M.G.B. Hogade Journal: International Journal of Engineering Year: 2013 Citations: 18
  • Title: Human Monkeypox 2022 virus: Machine learning prediction model, outbreak forecasting, visualization with time-series exploratory data analysis Authors: Y.H. Bhosale, S.R. Zanwar, A.T. Jadhav, Z. Ahmed, V.S. Gaikwad, K.S. Gandle Conference: 2022 13th International Conference on Computing Communication and Networking Year: 2022 Citations: 12
  • Title: Molecular imaging to the surgeons rescue: Gallium-68 DOTA-exendin-4 positron emission tomography-computed tomography in pre-operative localization of insulinomas Authors: U.N. Pallavi, V. Malasani, I. Sen, P. Thakral, S. Dureja, V. Pant, V.S. Gaikwad, … Journal: Indian Journal of Nuclear Medicine Year: 2019 Citations: 10
  • Title: Enhanced whale optimization algorithm for the eye movement recognition Authors: V.S. Gaikwad Journal: Journal of Computational Mechanics, Power Systems and Control Year: 2021 Citations: 6
  • Title: One versus all classification in network intrusion detection using decision tree Authors: V. Gaikwad, P.J. Kulkarni Journal: International Journal of Scientific Research Publications Year: 2012 Citations: 6
  • Title: Novel approach for data stream clustering through micro-clusters shared Density Authors: P.V. Desai, V.S. Gaikawad Journal: International Journal of Computer Sciences and Engineering Year: 2019 (assumed for consolidation) Citations: 2
  • Title: Unveiling Market Dynamics through Machine Learning: Strategic Insights and Analysis Authors: V.S. Gaikwad, S.S. Deore, G.M. Poddar, R.V. Patil, D.S. Hirolikar, M.P. Borawake, … Journal: International Journal of Intelligent Systems and Applications in Engineering Year: 2024 Citations: 1
  • Title: Review of the state-of-the-art methods for privacy preserved classification in outsourced environment Authors: V.S. Gaikwad, K.H. Walse, V.M. Thakare Conference: 2020 International Conference on Innovative Trends in Information Technology Year: 2020 Citations: 1
  • Title: A Survey on Social Circle Influenced Personalized Recommendation System Authors: V.J. Kadam, V.S. Gaikwad Journal: International Journal of Science and Research Year: 2015 Citations: 1