Anjan Kumar reddy Ayyadapu | Computer science | Excellence in Research Award

Mr. Anjan Kumar Reddy Ayyadapu | Computer science | Excellence in Research Award

Cloudera | United States

Anjan Kumar Reddy Ayyadapu is a seasoned Cloud Solution Architect specializing in big data, artificial intelligence, and cybersecurity. Currently working at Cloudera, Inc., he brings extensive expertise in Hadoop ecosystems, machine learning, and secure cloud infrastructure. His professional journey includes roles at Amazon Web Services, IBM, and Wipro, where he contributed to enterprise-scale solutions and cloud innovation. He holds a Master’s degree in Electrical Engineering and a Bachelor’s degree in Electronics and Communication Engineering. An active researcher, he has published multiple articles and holds a patent focused on AI-driven cloud security. His work emphasizes integrating machine learning with cryptographic techniques to enhance data protection and optimize incident response in modern cloud environments.

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Featured Publications


Fuzzy Logic and Machine Learning Hybrid Model for Influencing Consumer Purchasing Behavior in E-Commerce


– International Conference on Computing Technologies & Data Communication

AVE Trends in Intelligent Computer Letters


– Research Contribution

Scalable Machine Learning Approaches for Real-Time Big Data Processing in IoT Networks


– AVE Trends in Intelligent Computing Systems

A Hybrid Machine Learning Model for Predictive Analytics in Big Data Frameworks


– AVE Trends in Intelligent Computing Systems

Deep Learning Models for Predictive Maintenance in Industrial IoT with Big Data Support


– FMDB Transactions on Sustainable Intelligent Networks

Abhilash Pati | Computer Science | Research Pioneer Award in Biomedical Sciences | 1881

Dr. Abhilash Pati | Computer Science | Research Pioneer Award in Biomedical Sciences 

Dr. Abhilash Pati, Siksha O Anusandhan University, Bhubaneswar, India

Dr. Abhilash Pati is an accomplished Assistant Professor in the Department of Computer Science and Engineering at Siksha ‘O’ Anusandhan University, Bhubaneswar, India. With over 15 years of academic and research experience, he specializes in Artificial Intelligence, Machine Learning, Blockchain, IoT, and Fog Computing. He has authored three books, published over 60 research articles indexed in Scopus and WoS, and holds three patents, including a granted design utility. His work is widely recognized in high-impact journals such as IEEE Access, Scientific Reports, and PLOS ONE. Dr. Pati is also UGC-NET qualified and actively mentors students and research initiatives.

Profile

Google Scholar

🎓 Early Academic Pursuits

Dr. Abhilash Pati’s academic journey began with a strong passion for technology and computing, which later shaped his extensive career in computer science. From his early days, he exhibited a deep curiosity in how systems work, leading him to pursue higher education in Computer Science and Engineering. His dedication and academic rigor earned him recognition early on, culminating in qualifying the prestigious UGC-NET, a testament to his proficiency and commitment to academic excellence in India. His foundational training not only built his core technical skills but also fostered an analytical mindset that would serve as the cornerstone for his research pursuits in artificial intelligence and emerging technologies.

🧑‍🏫 Professional Endeavors

Dr. Abhilash Pati currently serves as an Assistant Professor in the Department of Computer Science and Engineering at Siksha ‘O’ Anusandhan University, Bhubaneswar, India, a premier institution recognized for academic innovation and research. With over 15 years of experience, Dr. Pati has built a career marked by dedication to teaching, curriculum development, and student mentorship.

Throughout his tenure, he has engaged in the delivery of undergraduate and postgraduate courses, supervised student projects, and contributed to the design of industry-aligned academic programs. His role is not limited to classroom instruction; he is actively involved in research groups and collaborative initiatives that bridge the gap between academia and industry. This dual focus on pedagogy and innovation has made him a respected figure among students and peers alike.

🔬 Contributions and Research Focus

Dr. Pati’s research spans several cutting-edge domains, including Artificial Intelligence (AI), Machine Learning (ML), Blockchain Technology, Internet of Things (IoT), and Fog Computing. These fields represent the frontier of technological advancement, and Dr. Pati’s contributions have helped propel research in these areas, especially in applications related to smart systems and intelligent data processing.

He has authored and co-authored over 60 research publications, many of which are indexed in Scopus and Web of Science (WoS). His work is regularly published in high-impact journals such as IEEE Access, Scientific Reports (Nature Portfolio), and PLOS ONE, reflecting the global recognition of his scholarly output.

Additionally, he has authored three academic books and holds three patents, including a granted design utility patent—further illustrating the practical implications of his research and its potential for technological innovation.

🏅 Accolades and Recognition

Dr. Pati’s academic and professional excellence has not gone unnoticed. His qualification in UGC-NET speaks volumes about his academic merit. Beyond that, his prolific publication record, patent filings, and scholarly books underscore his status as a thought leader in his field. His articles are frequently cited by researchers worldwide, and he has often been invited as a reviewer and editor for reputed international journals and conferences.

Moreover, his contributions are instrumental in shaping institutional research strategies, leading to enhanced collaborations and interdisciplinary research output within his university and beyond.

🌐 Impact and Influence

Dr. Pati’s influence extends far beyond the lecture hall or laboratory. As a mentor, he has guided numerous students toward academic excellence and research competence. Many of his mentees have gone on to pursue higher education, research careers, or roles in the tech industry, thanks to the foundational skills and inspiration he provided.

His interdisciplinary approach—linking AI with Blockchain, or IoT with Fog Computing—has opened up new research directions for his peers and collaborators. Furthermore, his publications have served as reference points in academia and industry, helping shape conversations around the ethical, scalable, and efficient deployment of smart technologies.

🌟 Legacy and Future Contributions

Dr. Abhilash Pati’s journey is one of sustained growth, intellectual curiosity, and purposeful impact. Looking ahead, he is poised to continue contributing to the evolving technological landscape by focusing on sustainable computing, ethical AI, and decentralized systems. His vision includes building robust academic-industry partnerships and creating innovation hubs that foster student-led research and startups.

His legacy will not just be defined by the number of papers or patents, but by the culture of curiosity, critical thinking, and compassion that he instills in the next generation of computer scientists. Through teaching, mentorship, and research, Dr. Pati is building a future where technology serves humanity more intelligently and equitably.

Publication Top Notes

An IoT-fog-cloud integrated framework for real-time remote cardiovascular disease diagnosis

Author: A Pati, M Parhi, M Alnabhan, BK Pattanayak, AK Habboush, …
Journal: Informatics
Year: 2023

Heartfog: Fog computing enabled ensemble deep learning framework for automatic heart disease diagnosis

Author: A Pati, M Parhi, BK Pattanayak
Journal: Intelligent and Cloud Computing
Year: 2022

COVID-19 pandemic analysis and prediction using machine learning approaches in India

Author: A Pati, M Parhi, BK Pattanayak
Journal: Advances in Intelligent Computing and Communication
Year: 2023

A review on prediction of diabetes using machine learning and data mining classification techniques

Author: A Pati, M Parhi, BK Pattanayak
Journal: International Journal of Biomedical Engineering and Technology
Year: 2021

Nikolay M. Sirakov | Data Science | Excellence in Research Award

Prof. Nikolay M. Sirakov | Data Science | Excellence in Research Award

Prof. Nikolay M. Sirakov, East Texas A&M University, Dept. Mathematics, United States.

Nikolay Metodiev Sirakov is a Professor of Mathematics at East Texas A&M University 🏫, specializing in pattern recognition, machine learning, and mathematical modeling 🔬. With a Ph.D. from the Bulgarian Academy of Sciences 🎓, his research spans image processing, artificial intelligence, and biomedical applications 🧠. He has collaborated with leading global institutions 🌍 and supervised numerous Ph.D. and Master’s students 📚. His contributions to computer vision and AI-driven diagnostics 🤖 have earned him international recognition. ✨

🌟 Professional Profile

🎓 Early Academic Pursuits

Nikolay Metodiev Sirakov’s academic journey began with rigorous training at Bulgaria’s top institutions, including the Bulgarian National High School of Mathematics and CS. He pursued undergraduate studies at Sofia University, earning his B.S. in Mathematics and Computer Science. He went on to complete his Master’s in Coding Theory at Sofia University and later obtained his Ph.D. from the Bulgarian Academy of Sciences, specializing in Pattern Recognition.

💼 Professional Endeavors

Sirakov has held various prestigious academic positions, including professor and associate professor at Texas A&M University-Commerce since 2004. He also served as a senior researcher and invited professor at institutions like Instituto Superior Tecnico, Lisbon, and Northern Arizona University. His leadership includes chairing committees and collaborating with diverse institutions globally.

🔬 Contributions and Research Focus On Data Science 

Sirakov’s research spans machine learning, image processing, and biomedical applications, with significant contributions to skin cancer diagnosis, tracking objects in video, and automatic threat detection. He has led multiple international collaborations, publishing numerous peer-reviewed papers and advancing computational techniques, particularly in sparse representation and neural network

🌍 Impact and Influence

With his vast expertise, Sirakov has influenced fields such as medicine, security, and robotics, making a profound impact on medical imaging and biomechanics. His work in automated melanoma diagnosis has gained recognition in the medical community, while his contributions to video object tracking and image segmentation remain highly influential in computer vision.

🏆 Awards and Honors

  • Best Paper Award – Oluwaseyi Igbasanmi, Nikolay M. Sirakov, and Adam Bowden were recognized for their paper, CNN for Efficient Objects Classification with Embedded Vector Fields, presented at ICCIDA2023 and published in the Springer book series. 📚

  • 2nd Place Winner in Mathematics – Elisha Shachar received recognition for the project on An Artificial Intelligence-Based Driving Environment Descriptor: Voice Alerts to Drivers at the 15th TAMU System Pathway Students Symposium. 🚗

  • 1st Place Winner in Mathematics – Mengzhe Chen, supervised by Nikolay Sirakov, presented Singular Points of the Gradient Field of the Poisson Partial Differential Equation Solution on an Image at the TAMU System Pathway Students Symposium. 🔢

  • Lockheed Martin Best Paper Award – Awarded to a team for their paper, From Shape to Threat: Exploiting the Convergence Between Visual and Conceptual Organization for Weapon Identification and Threat Assessment. 🎖

🚀 Legacy and Future Contributions

Sirakov’s legacy is built on his innovative contributions to computational science and biomedical engineering. Looking ahead, his continued work in machine learning and medical applications promises to influence the next generation of scientific advancements in healthcare technologies and security systems.

📚Publications Top Notes

  • A system for reconstructing and visualizing three-dimensional objects
    Citations: 70 📊
    Year: 2001 🗓️

  • Lesion detection in dermoscopy images with novel density-based and active contour approaches
    Citations: 51 📈
    Year: 2010 🩺

  • A new active convex hull model for image regions
    Citations: 36 📐
    Year: 2006 🔍

  • Dermoscopic diagnosis of melanoma in a 4D space constructed by active contour extracted features
    Citations: 35 💡
    Year: 2012 🧑‍⚕️

  • Interpolation approach for 3D smooth reconstruction of subsurface objects
    Citations: 34 🌍
    Year: 2002 🖥️

  • Automatic boundary detection and symmetry calculation in dermoscopy images of skin lesions
    Citations: 30 🔬
    Year: 2011 🧠

  • Efficient segmentation with the convex local-global fuzzy Gaussian distribution active contour for medical applications
    Citations: 26 💉
    Year: 2015 📊

  • Intelligent shape feature extraction and indexing for efficient content-based medical image retrieval
    Citations: 26 🔍
    Year: 2004 🏥

  • Recognition of emotional states in natural human-computer interaction
    Citations: 23 😐
    Year: 2008 🤖

  • An integral active contour model for convex hull and boundary extraction
    Citations: 22 🏞️
    Year: 2009 🔧

  • Threat assessment using visual hierarchy and conceptual firearms ontology
    Citations: 19 🔫
    Year: 2015 🚨

  • Search space partitioning using convex hull and concavity features for fast medical image retrieval
    Citations: 19 🔎
    Year: 2004 🏥

  • Optimal set of features for accurate skin cancer diagnosis
    Citations: 18 🩺
    Year: 2014 🧬

  • Skin lesion feature vectors classification in models of a Riemannian manifold
    Citations: 17 🏥
    Year: 2015 🔬

  • Automatic feature extraction and recognition for digital access of books of the Renaissance
    Citations: 15 📚
    Year: 2000 🔍

  • Sparse representation wavelet-based classification
    Citations: 11 🖼️
    Year: 2018 💻

  • A novel classification system for dysplastic nevus and malignant melanoma
    Citations: 11 🩺
    Year: 2016 🌟

  • New accurate automated melanoma diagnosing systems
    Citations: 11 🧬
    Year: 2015 ⚕️

  • Weapon ontology annotation using boundary describing sequences
    Citations: 11 🔫
    Year: 2012 🛡️

  • Active contour directed by the Poisson gradient vector field and edge tracking
    Citations: 10 🖥️
    Year: 2021 📉

  • Comparing 2D borders using regular structures
    Citations: 10 🔍
    Year: 1994 🖼️

  • Support vector machine skin lesion classification in Clifford algebra subspaces
    Citations: 9 🩺
    Year: 2019 📈

  • Poisson equation solution and its gradient vector field to geometric features detection
    Citations: 9 🔬
    Year: 2018 🔧

  • Integration of low-level and ontology-derived features for automatic weapon recognition and identification
    Citations: 9 🛡️
    Year: 2011 💡

  • Monotonic vector forces and Green’s theorem for automatic area calculation
    Citations: 9 🔍
    Year: 2007 📐

  • A new automatic concavity extraction model
    Citations: 9 🔍
    Year: 2006 🧠

  • Classification with stochastic learning methods and convolutional neural networks
    Citations: 8 🤖
    Year: 2020 💻

  • From shape to threat: exploiting the convergence between visual and conceptual organization for weapon identification and threat assessment
    Citations: 8 🔫
    Year: 2013 🛡️

  • Skin lesion image classification using sparse representation
    Citations: 8 🩺
    Year: 2018 📊