Sreenivasu S V N | Intelligent Sensing | Excellence in Research Award

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Excellence in Research Award

Sreenivasu S V N
Affiliation Narasaraopeta Engineering College
Country India
Scopus ID 56565617500
Documents 58
Citations 288
h-index 9
Subject Area Computer Science, Artificial Intelligence, Machine Learning, Intelligent Sensing
Event Global Sensor Awards
ORCID 0000-0002-6049-911X

Sreenivasu S V N is an Indian computer science researcher, professor, academic administrator, and doctoral supervisor affiliated with Narasaraopeta Engineering College, Andhra Pradesh, India. His scholarly work spans artificial intelligence, machine learning, deep learning, cloud computing, Internet of Things (IoT), cybersecurity, data analytics, medical image processing, and distributed computing systems. Through extensive research publications, patents, books, doctoral supervision, and international collaborations, he has contributed to the advancement of intelligent computing and applied engineering research.[1]

Abstract

This article presents an overview of the academic achievements, research profile, scholarly publications, intellectual property contributions, and professional accomplishments of Dr. Sirasanagondla Venkata Naga Sreenivasu. His work demonstrates sustained engagement in advanced computing technologies, particularly in machine learning, artificial intelligence, cloud systems, healthcare analytics, network security, and intelligent decision-support systems. His research output includes peer-reviewed journal articles, conference proceedings, books, patents, and doctoral supervision activities that collectively contribute to the global advancement of computer science and engineering research.[2]

Keywords

Artificial Intelligence, Machine Learning, Deep Learning, Cloud Computing, Internet of Things, Healthcare Analytics, Data Mining, Image Processing, Computer Networks, Cybersecurity, Distributed Systems, Software Engineering.

Introduction

Sreenivasu has established a multidisciplinary research portfolio that integrates theoretical computer science with practical engineering applications. Over more than two decades of academic and administrative service, he has contributed to teaching, institutional leadership, doctoral mentoring, and research innovation. His work frequently addresses real-world challenges through the application of artificial intelligence, predictive analytics, healthcare technologies, and intelligent computing systems.[1]

Research Profile

Sreenivasu earned advanced qualifications in Information Technology, Computer Science and Engineering, and completed a doctoral degree focused on intrusion detection systems and network security. His academic career includes appointments as Professor, Principal, Vice Principal, Director, Associate Professor, and Assistant Professor across multiple higher education institutions in India. He has supervised numerous doctoral scholars and has contributed extensively to postgraduate and undergraduate education in computing disciplines.[1]

Research Contributions

  • Published more than 100 research papers in journals and conference proceedings.
  • Produced significant work in artificial intelligence, healthcare analytics, machine learning, deep learning, IoT, and cloud computing.
  • Guided and supervised multiple Ph.D. scholars across diverse computer science domains.
  • Contributed to international patents, copyrights, and technology-transfer initiatives.
  • Served as conference convener, session chair, reviewer, and research mentor for national and international events.

His research portfolio demonstrates a strong focus on intelligent systems for disease diagnosis, medical imaging, predictive modeling, smart environments, cloud-based healthcare platforms, and advanced optimization algorithms.[3]

Publications

Selected scholarly publications include research on deep neural networks, cardiovascular disease prediction, tongue image disease analytics, healthcare monitoring systems, cloud computing architectures, IoT-enabled smart systems, and machine-learning-based diagnostic platforms. Several works have appeared in Scopus-indexed and internationally recognized journals, including Big Data, BioMed Research International, Electronics, Cybernetics and Systems, and various IEEE conference proceedings.[3]

  • ODQN-Net: Optimized Deep Q Neural Networks for Disease Prediction Through Tongue Image Analysis.
  • Dense Convolutional Neural Network for Detection of Cancer from CT Images.
  • Cloud Based Electric Vehicle Temperature Monitoring System Using IoT.
  • Machine Learning Based Monitoring Systems Using Wearable Sensors.
  • Cardiovascular Disease Prediction Using Deep Variational Auto Encoder Models.

Research Impact

The research contributions of Dr. Sreenivasu have influenced multiple areas of intelligent computing, healthcare informatics, and engineering innovation. His publications have supported the development of machine-learning applications for medical diagnostics, smart healthcare infrastructure, cloud computing environments, and intelligent sensor networks. His patents further demonstrate translational research capabilities that extend beyond academic publication into practical technological implementation.[2]

Award Suitability

Sreenivasu’s scholarly achievements align strongly with criteria commonly used for international academic recognition awards. His record includes extensive peer-reviewed publications, doctoral supervision, book authorship, intellectual property generation, conference leadership, interdisciplinary research collaboration, and contributions to emerging technologies. These accomplishments demonstrate sustained academic productivity and a measurable impact on research, education, and technological innovation.[1]

Conclusion

Sirasanagondla Venkata Naga Sreenivasu represents a distinguished academic profile within the fields of computer science and intelligent systems research. His multidisciplinary contributions, sustained publication record, mentorship activities, and innovation-driven research agenda establish him as a noteworthy candidate for recognition in international research excellence and innovation award programs.[2]

References

  1. Academic Curriculum Vitae of Dr. Sirasanagondla Venkata Naga Sreenivasu, including education, professional experience, doctoral supervision, awards, patents, and academic achievements.
  2. Elsevier. (n.d.). Scopus author details: Dr. Sirasanagondla Venkata Naga Sreenivasu, Author ID 56565617500. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56565617500
  3. Sreenivasu, S.V.N., et al. Selected Scopus-indexed publications in artificial intelligence, machine learning, healthcare analytics, cloud computing, and intelligent systems.
    https://doi.org/10.1089/big.2023.0014

Xiaoming Zou | Solid State Sensors | Best Researcher Award

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Best Researcher Award

Xiaoming Zou
Affiliation Jiangsu Academy of Agricultural Sciences
Country China
Scopus ID 7203047486
Documents 144
Citations 6,086
h-index 43
Subject Area Biogeochemistry, Soil Ecology, Agronomy, Forest Ecology, Global Change Biology, Solid State Sensors
Event Global Sensor Awards
ORCID 0000-0001-9023-3067

Xiaoming Zou,
Jiangsu Academy of Agricultural Sciences, China

Xiaoming Zou is a forest ecologist, soil ecologist, biogeochemist, and agronomist whose scholarly career spans more than four decades across China, Puerto Rico, the United States, and international research collaborations. His work has focused on nutrient cycling, soil carbon dynamics, earthworm ecology, ecosystem functioning, forest restoration, tropical ecology, and the emerging concept of calcium-niche theory. He currently serves as Research Professor at the Jiangsu Academy of Agricultural Sciences, China, following a distinguished academic tenure at the University of Puerto Rico and multiple international research appointments.[1][2]

Abstract

This academic recognition article summarizes the professional achievements, scientific contributions, publication record, and scholarly influence of Xiaoming Zou. His research integrates ecology, soil science, forestry, biogeochemistry, and agricultural sustainability. Through extensive interdisciplinary investigations, he has contributed to the understanding of nutrient cycling, soil biodiversity, ecosystem resilience, carbon sequestration, decomposition processes, tropical forest ecology, and global environmental change. His recent work on calcium-mediated ecological processes has introduced new perspectives for understanding plant productivity, species coexistence, and ecosystem restoration.[1][3]

Keywords

Biogeochemistry; Soil Ecology; Forest Ecology; Agronomy; Carbon Sequestration; Earthworm Ecology; Nutrient Cycling; Calcium-Niche Theory; Global Change Biology; Ecosystem Restoration; Tropical Ecology; Soil Carbon Dynamics.

Introduction

Xiaoming Zou obtained a Bachelor of Agriculture degree in Forestry from Nanjing Forestry University, a Master of Science degree in Natural Resources from the University of Michigan, and a Ph.D. in Forest Ecology and Soil Ecology from Colorado State University. Since the early 1990s, he has maintained a highly productive research career spanning tropical forests, agricultural systems, ecological restoration, soil biodiversity, and ecosystem processes. His academic appointments have included positions at the University of Puerto Rico, Xishuangbanna Tropical Botanical Garden of the Chinese Academy of Sciences, Nanjing Forestry University, and Jiangsu Academy of Agricultural Sciences.[1]

Research Profile

  • Research Professor, Jiangsu Academy of Agricultural Sciences (2025–present).
  • Professor, University of Puerto Rico–Rio Piedras (2004–2025).
  • Affiliated Professor, Nanjing Forestry University.
  • Former Soil Ecology Group Leader, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences.
  • International collaborations across North America, Latin America, Asia, and global ecological networks.

His research program combines theoretical ecology with applied environmental science. Major themes include nutrient interactions, forest ecosystem functioning, climate change responses, decomposition dynamics, microbial ecology, and soil-fauna-mediated ecosystem processes.[1]

Research Contributions

  • Advanced understanding of phosphorus mineralization and nutrient transformation processes in soils.
  • Pioneering investigations into earthworm ecology and ecosystem engineering effects.
  • Major contributions to soil carbon stabilization and carbon sequestration research.
  • Research on ecosystem resistance and resilience to hurricanes and tropical cyclones.
  • Development of calcium-centered ecological frameworks linking nutrient availability, biodiversity, and plant productivity.
  • Global analyses of nitrogen deposition, drought, warming, and ecosystem responses.
  • Extensive work on decomposition, microbial necromass, and forest soil dynamics.

Publications

The curriculum vitae documents more than 169 scholarly outputs, including peer-reviewed journal articles, books, book chapters, review articles, methodological papers, and international collaborative publications. His work has appeared in leading journals such as Science Advances, Proceedings of the National Academy of Sciences, Global Change Biology, New Phytologist, Communications Earth and Environment, Soil Biology and Biochemistry, Geoderma, Forest Ecology and Management, Plant and Soil, and numerous other internationally recognized outlets.[3]

  • 2025: Publications on nitrogen enrichment, calcium dynamics, soil carbon vulnerability, earthworm ecology, and ecosystem responses.
  • 2024–2023: Contributions addressing forest development, soil fauna, drought responses, microbial ecology, and decomposition processes.
  • 2010–2022: Significant advances in tropical forest ecology, nutrient cycling, and ecosystem resilience.
  • 1992–2009: Foundational research in phosphorus transformations, earthworm ecology, forest restoration, and tropical ecosystem processes.

Research Impact

The scientific influence of Xiaoming Zou is reflected through a sustained publication record, international collaborations, graduate mentorship, and contributions to ecological theory and environmental management. His research has informed understanding of tropical ecosystem functioning, nutrient cycling, climate adaptation, and sustainable land management. His studies on soil organisms, decomposition, and nutrient interactions are frequently referenced within soil ecology and ecosystem science literature.[1][2]

Award Suitability

Based on the documented body of work, Xiaoming Zou demonstrates a long-standing record of scholarly achievement characterized by interdisciplinary innovation, international collaboration, publication productivity, and scientific leadership. His research spans fundamental ecological theory and practical environmental applications, making his profile suitable for consideration in academic excellence, lifetime achievement, environmental science, ecological research, and agricultural innovation award categories.[1][3]

Conclusion

Xiaoming Zou has established an extensive international academic career encompassing forest ecology, soil science, agronomy, biogeochemistry, and environmental sustainability. His contributions have advanced scientific understanding of nutrient cycling, ecosystem resilience, biodiversity, and climate-related ecological processes. The breadth of his publication portfolio and the continuity of his scholarly engagement underscore his significance within contemporary ecological and environmental research.[1]

References

  1. ORCID. (n.d.). Xiaoming Zou – ORCID record and academic affiliations. https://orcid.org/0000-0001-9023-3067
  2. Elsevier. (n.d.). Scopus author details: Xiaoming Zou, Author ID 7203047486. Scopus. https://www.scopus.com/authid/detail.uri?authorId=7203047486
  3. Zou, X. (2025). Transpiration as a missing mechanism in latitudinal patterns of leaf phosphorus. Plant, Cell & Environment.DOI: https://doi.org/10.1111/pce.70340
  4. Zou, X. M., Binkley, D., & Doxtader, K. (1992). A new method for estimating gross phosphorus mineralization and immobilization rates in soils. Plant and Soil. https://doi.org/10.1007/BF00029072

Mlungisi Ntombela | Internet of Things (IoT) | Innovative Research Award

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Innovative Research Award

Mlungisi Ntombela
Durban University of Technology (DUT), South Africa

Mlungisi Ntombela
Affiliation Durban University of Technology (DUT)
Country South Africa
Scopus ID 57558503600
Documents 14
Citations 194
h-index 5
Subject Area Electrical Engineering, Artificial Intelligence, Smart Grids, Electric Vehicles, Internet of Things
Event Global Sensor Awards
ORCID 0000-0001-6428-0257

Mlungisi Ntombela is a South African electrical engineer, academic researcher, lecturer, and certified engineering professional whose work bridges industrial engineering practice and advanced academic research. His expertise spans electrical power systems, artificial intelligence applications in smart grids, power system optimization, distributed generation integration, electric vehicles, reliability engineering, and project management. Through a combination of engineering leadership, research innovation, and higher education contributions, he has established a multidisciplinary profile that supports both technological advancement and engineering education.[1]

Abstract

This academic recognition article presents the professional achievements, research contributions, and engineering leadership of Dr. Mlungisi Eric Ntombela. His work integrates industrial engineering practice with advanced research in electrical power systems, smart grids, distributed generation, artificial intelligence optimization algorithms, and electric vehicle integration. His contributions include peer-reviewed publications, project engineering leadership, higher education teaching, and the development of innovative methodologies for power loss reduction and voltage profile enhancement in modern electrical networks.[2]

Keywords

Electrical Engineering, Smart Grids, Artificial Intelligence, Optimization Algorithms, Distributed Generation, Electric Vehicles, Power Systems, Reliability Engineering, Power Quality, Energy Systems, Research Innovation, Engineering Education, Project Engineering, Sustainable Energy.

Introduction

Dr. Ntombela’s career demonstrates a balanced integration of industrial engineering experience and academic scholarship. Holding a Doctor of Engineering in Electrical Engineering and a Government Certificate of Competency (Factories), he has contributed significantly to both utility-scale engineering operations and university-level education. His professional experience includes maintenance engineering, reliability management, risk assessment, project execution, research supervision, and curriculum development. These combined experiences have enabled him to address practical engineering challenges while advancing scientific knowledge in electrical power systems.[1]

Research Profile

The research activities of Dr. Ntombela focus primarily on electrical power system optimization, artificial intelligence applications in smart grids, distributed generation placement, electric vehicle integration, power quality improvement, and sustainable energy management. His academic work has investigated advanced hybrid optimization algorithms capable of minimizing network losses while improving voltage stability and operational efficiency in electrical distribution systems.[3]

Beyond research, he actively contributes to engineering education through lecturing, laboratory instruction, curriculum modernization aligned with Fourth Industrial Revolution (4IR) technologies, and mentoring of engineering students. His interdisciplinary perspective supports the integration of industry-driven solutions within academic environments.[4]

Research Contributions

  • Development and evaluation of optimization techniques for power network reconfiguration.
  • Research on distributed generation sizing and placement for power loss minimization.
  • Application of artificial intelligence hybrid algorithms in smart grid optimization.
  • Comprehensive studies on electric vehicle integration into modern power systems.
  • Voltage profile improvement methodologies for sustainable electricity networks.
  • Contributions to battery electric vehicle drive circuit technologies and operational analysis.
  • Research on renewable energy distributed generation and smart grid interoperability.
  • Engineering project management and reliability-centered maintenance methodologies.

Publications

  • Review of Optimization Techniques for Power Network Reconfiguration (SAUPEC 2022).
  • Power Loss Minimization and Voltage Profile Improvement by Distributed Generation Sizing and Placement (PowerAfrica 2022).
  • Power Loss Minimization and Voltage Profile Improvement by System Reconfiguration, DG Sizing, and Placement. Computation, 2022.
  • Artificial Intelligent Hybrid Algorithm Used for System Reconfiguration to Minimize Power Losses in the Distribution System.
  • Load Profile and Load Flow Analysis for a Grid System with Electric Vehicles Using a Hybrid Optimization Algorithm. Sustainability, 2023.
  • Reduction of Power Losses and Voltage Profile Improvement in a Smart Grid Incorporated with Electric Vehicles. Sustainability, 2023.
  • A Comprehensive Review of the Incorporation of Electric Vehicles and Renewable Energy Distributed Generation Regarding Smart Grids. World Electric Vehicle Journal, 2023.
  • A Comprehensive Review for Battery Electric Vehicles (BEV) Drive Circuits Technology, Operations, and Challenges. World Electric Vehicle Journal, 2023.

Research Impact

The research contributions of Dr. Ntombela address critical challenges associated with energy efficiency, renewable energy integration, electrical network optimization, and transportation electrification. His published studies provide analytical frameworks and computational techniques that support the development of resilient and sustainable power systems. These contributions are particularly relevant to emerging smart grid infrastructures and the increasing adoption of electric mobility technologies worldwide.[5]

In addition to scholarly outputs, his industrial experience in project engineering, risk-based inspection, reliability-centered maintenance, and operational management provides practical relevance to his research, strengthening the applicability of his findings in real-world engineering environments.[1]

Award Suitability

Dr. Mlungisi Eric Ntombela demonstrates strong suitability for recognition within engineering, energy systems, smart grid technologies, and applied artificial intelligence award categories. His profile combines advanced academic qualifications, impactful scientific publications, industrial engineering leadership, teaching excellence, and interdisciplinary innovation. His contributions align closely with the objectives of awards recognizing research excellence, technological innovation, sustainability, engineering leadership, and emerging contributions to future energy systems.[2]

Conclusion

Dr. Mlungisi Eric Ntombela represents a new generation of engineering professionals whose expertise spans industry practice, academic scholarship, and technological innovation. Through his work in electrical engineering, artificial intelligence, smart grids, and electric vehicle integration, he has contributed to advancing knowledge while addressing practical challenges facing modern energy systems. His combination of research productivity, engineering leadership, and educational service positions him as a notable contributor within the fields of electrical engineering and sustainable energy development.

References

  1. Ntombela, M. E. Professional Curriculum Vitae and Academic Profile.
  2. Ntombela, M., Musasa, K., & Leoaneka, M.C. (2022). Review of Optimization Techniques for Power Network Reconfiguration.
    https://doi.org/10.1109/SAUPEC55179.2022.9730628
  3. Ntombela, M., Musasa, K., & Leoaneka, M.C. (2022). Power Loss Minimization and Voltage Profile Improvement by System Reconfiguration, DG Sizing, and Placement.
    https://doi.org/10.3390/computation10100180
  4. Durban University of Technology. Academic Teaching and Research Activities.
  5. Ntombela, M., Musasa, K., & Moloi, K. (2023). A Comprehensive Review of the Incorporation of Electric Vehicles and Renewable Energy Distributed Generation Regarding Smart Grids.
    https://doi.org/10.3390/wevj14070176

Santi Maity | Internet of Things (IoT) | Distinguished Scientist Award

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Prof Santi Maity | Internet of Things (IoT) | Distinguished Scientist Award

Indian Institute of Engineering Science and Technology Shibpur | India

Prof. Santi P. Maity is a distinguished academic and researcher in the fields of wireless communications, signal processing, and image processing, currently serving as Professor (HAG) at the Indian Institute of Engineering Science and Technology (IIEST), Shibpur. With a Ph.D. in Computer Science and Technology, his research spans cognitive radio networks, IoT-based healthcare systems, machine learning applications, and secure image watermarking. He has an extensive scholarly output comprising over 130 peer-reviewed journal articles, 186 conference papers, and multiple book chapters, alongside patented innovations in digital image security. Prof. Maity has successfully led and contributed to several funded research projects supported by government agencies, focusing on next-generation communication systems and AI-driven diagnostic tools. He has supervised over 20 Ph.D. scholars and numerous postgraduate and undergraduate students, significantly contributing to academic capacity building. His international collaborations with institutions in France, Spain, Singapore, and beyond reflect his global research engagement. His work demonstrates strong societal impact, particularly in advancing affordable healthcare technologies, secure communications, and energy-efficient wireless systems.

Citation Metrics (Scopus)

3000
2000
1000
500
0

Citations
2,721

h-index
27

Documents
293

Citations

h-index

Documents

Featured Publications

IoMT in Low-Cost Autofluorescence Imaging and Automated Detection at Edge for Cervical Cancer (2026).
IEEE Internet of Things Journal · Journal Article ·

CAE-DCNN Architectures for Image Watermarking and Detection on Edge-IoT Networks (2026).
SN Computer Science · Journal Article ·

Relay Performance in D2D Communications Overlaying Multi-Antenna Cellular Networks (2026).
IEEE Open Journal of the Communications Society · Journal Article ·

Spectrum Prediction: Boosting D2D Communications in CRNs Using POMDP (2025).
Physical Communication · Journal Article ·

Residual Energy Maximization in RIS Aided Cooperative Spectrum Sensing with PUEA: Relative Performance in PS and TS Mode (2025).
IEEE Access · Journal Article ·

Prof. Dr. Carolina Del-Valle-Soto | Internet of Things | Best Researcher Award

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Prof. Dr. Carolina Del-Valle-Soto | Internet of Things | Best Researcher Award 

Prof. Dr. Carolina Del-Valle-Soto, Universidad Panamericana, Mexico

Carolina del Valle Soto is a distinguished researcher and professor in the field of telecommunications, specializing in wireless and wired networks, programming, and security she currently resides in Guadalajara, Mexico. She earned her Ph.D. in Information and Communication Technologies from Tecnológico de Monterrey in 2015, where she was recognized as Valedictorian and received an Excellence Scholarship. Her research focuses on developing protocols for wireless sensor networks. She also holds a Master’s in Electronic Engineering (Telecommunications) from the same institution and a Bachelor’s in Electronic Engineering from Universidad Pontificia Bolivariana. Carolina is a Level 1 Member of the National System of Researchers in Mexico and an active member of IEEE and IEEE Women in Engineering. With extensive experience in academia and research, she has held teaching and research positions at Universidad Panamericana, Universidad del Istmo, and Universidad Tecmilenio. Additionally, she serves as an evaluator for the European Commission in frontier technologies. Her professional expertise includes mathematical modeling, automation, network performance analysis, and cybersecurity, making her a key contributor to technological advancements in telecommunications.

Professional Profile:

ORCID

Suitability of Carolina Del Valle Soto for the Best Researcher Award

Carolina Del Valle Soto is a highly accomplished researcher in Telecommunications, Wireless Networks, and Security. Her Doctorate in Information and Communication Technologies (ICT) from Tecnológico de Monterrey, combined with her prestigious academic achievements, such as her Valedictorian distinction, excellence scholarships, and IEEE leadership roles, highlight her exceptional expertise and commitment to research.

🎓 Education

  • Doctorado en Tecnologías de Información y Comunicaciones (2011 – 2015) – Tecnológico de Monterrey, México

    • 📜 Thesis: Desarrollo de un Protocolo para Redes Inalámbricas de Sensores
    • 🏆 Honors: Valedictorian of postgraduate graduation, IEEE & WIE (Vice President), Excellence Scholarship
    • 📊 Final GPA: 98

  • Maestría en Ciencias en Ingeniería Electrónica (Telecomunicaciones) (2007 – 2009) – Tecnológico de Monterrey, México

    • 📜 Thesis: Desarrollo de una red P2P con la seguridad del DNS
    • 🏆 Honors: Excellence Mention, Excellence Scholarship
    • 📊 Final GPA: 96

  • Ingeniería Electrónica (2002 – 2007) – Universidad Pontificia Bolivariana, Colombia

    • 📜 Thesis: Diseño y Construcción de un Sistema de Conteo de Fotones
    • 🏆 Honors: Proposed for Honors Mention
    • 🔬 Research Group: Optics and Spectroscopy

💼 Work Experience

  • Universidad del Istmo, Guatemala (Julio 2022 – Present)

    • 📡 Teaching Networks, Systems, and Telecommunications Services

  • Comisión Europea (Octubre 2019 – Present)

    • 🔍 Evaluator in the field of Frontier Technologies

  • Universidad Panamericana (Enero 2016 – Present)

    • 💻 Teaching Algorithm Analysis, Advanced C++ Programming, Research Methodology, and Data Science Projects

  • TECNOAP – Ternium (Junio – Diciembre 2015)

    • 🏭 Worked on Automation, Image Processing, and Surface Inspection Systems

  • Universidad TecMilenio (Mayo – Diciembre 2015)

    • 🔐 Taught Telecom Administration, IT Security, and Research Methods in Master’s in IT

  • Politecnico di Torino, Italy (Enero – Junio 2014)

    • 📶 Research on WiFi Direct networks – Performance analysis and implementation

🏅 Awards & Honors

  • 🏆 Valedictorian of Postgraduate Graduation – Tecnológico de Monterrey
  • 📜 IEEE & WIE Vice President (IEEE Women in Engineering)
  • 🎖 Excellence Scholarship (Doctorate & Master’s) – Tecnológico de Monterrey
  • 🏅 Excellence Mention – Master’s in Engineering
  • 🔬 Proposed for Honors Mention – Bachelor’s Thesis in Electronics

Publication Top Notes:

A smart glove to evaluate Parkinson’s disease by flexible piezoelectric and inertial sensors

Emphasizing the Early Phases of the Software Development Process Before Deploying Smart Contracts

Environmental odor detection and classification with electronic nose system

Integrated Dynamic Power Management Strategy with a Field Programmable Gate Array-Based Cryptoprocessor System for Secured Internet-of-Medical Things Networks

Innovative Driver Monitoring Systems and On-Board-Vehicle Devices in a Smart-Road Scenario Based on the Internet of Vehicle Paradigm: A Literature and Commercial Solutions Overview

Mr Anandarup Roy | Internet of Things | Best Researcher Award

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Mr Anandarup Roy| Internet of Things | Best Researcher Award

Mr Anandarup Roy,Senior Research Fellow, Indian Statistical Institute, Kolkata,India

Anandarup Roy is a Ph.D. candidate in Computer Science at the Indian Statistical Institute (ISI), Kolkata, specializing in combinatorial secret sharing. His thesis was submitted on July 19, 2024, and he expects to receive his degree by December 2024. He is advised by Prof. Bimal Kumar Roy and co-supervised by Prof. Mridul Nandi, both from the Applied Statistics Unit at ISI.

Professional Profile:

Summary of Suitability for the Best Researcher Award:

Anandarup Roy, a Ph.D. candidate at the Indian Statistical Institute, has made significant contributions to the field of computer science, particularly in combinatorial secret sharing. His research extends previous work in Bayesian incentive-compatible mechanism design and social learning, demonstrating a robust understanding of complex statistical models and their applications.

Education

He Naifeng is pursuing a PhD at the prestigious Nanjing University of Aeronautics and Astronautics, where he has built a strong foundation in automation and robotics. His academic journey reflects a commitment to advancing technology in mobile robotics, demonstrating a keen interest in both theoretical knowledge and practical applications.

Work Experience

From 2016 to 2018, Anandarup worked as a project-linked person at the Economics Research Unit of ISI, where he contributed to a project on Bayesian incentive-compatible mechanism design under the supervision of Prof. Manipushpak Mitra. This research extended his master’s thesis by examining learning processes in a social choice environment with risk-neutral agents.

Skills

Anandarup is proficient in using Linux OS (Ubuntu) and LaTeX. He possesses basic programming knowledge in C, making him well-equipped for computational tasks related to his research.

Research Focus

His research focuses on autonomous navigation for wheel-legged robots, with particular emphasis on reinforcement learning in control systems and intelligent motion control. He aims to develop practical applications that enhance the performance and adaptability of mobile robots in challenging environments.

Publication top Notes:

  • Combining Dynamic Selection and Data Preprocessing for Imbalance Learning
    Year: 2018
    Journal: Neurocomputing
    Volume/Pages: 286, 179-192
  • SVM-based Hierarchical Architectures for Handwritten Bangla Character Recognition
    Year: 2009
    Journal: International Journal on Document Analysis and Recognition (IJDAR)
    Volume/Pages: 12, 97-108
  • Lecithin and Venom Haemolysis
    Year: 1945
    Journal: Nature
    Volume/Pages: 155 (3945), 696-697
  • A Novel Approach to Skew Detection and Character Segmentation for Handwritten Bangla Words
    Year: 2005
    Journal: Digital Image Computing: Techniques and Applications (DICTA’05)
    Pages: 30-30
  • JCLMM: A Finite Mixture Model for Clustering of Circular-Linear Data and Its Application to Psoriatic Plaque Segmentation
    Year: 2017
    Journal: Pattern Recognition
    Volume/Pages: 66, 160-173
  • An HMM Framework Based on Spherical-Linear Features for Online Cursive Handwriting Recognition
    Year: 2018
    Journal: Information Sciences
    Volume/Pages: 441, 133-151
  • Pair-Copula Based Mixture Models and Their Application in Clustering
    Year: 2014
    Journal: Pattern Recognition
    Volume/Pages: 47 (4), 1689-1697
  • Character Segmentation for Handwritten Bangla Words Using Artificial Neural Network
    Year: 2005
    Journal: Proceedings of the 1st IAPR TC3 NNLDAR
  • SWGMM: A Semi-Wrapped Gaussian Mixture Model for Clustering of Circular–Linear Data
    Year: 2016
    Journal: Pattern Analysis and Applications
    Volume/Pages: 19, 631-645
  • Headline Based Text Extraction from Outdoor Images
    Year: Not specified (conference paper)
    Journal: Pattern Recognition and Machine Intelligence: 4th International Conference