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
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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. 📚
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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. 🚗
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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. 🔢
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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
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A system for reconstructing and visualizing three-dimensional objects
Citations: 70 📊
Year: 2001 🗓️
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Lesion detection in dermoscopy images with novel density-based and active contour approaches
Citations: 51 📈
Year: 2010 🩺
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A new active convex hull model for image regions
Citations: 36 📐
Year: 2006 🔍
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Dermoscopic diagnosis of melanoma in a 4D space constructed by active contour extracted features
Citations: 35 💡
Year: 2012 🧑⚕️
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Interpolation approach for 3D smooth reconstruction of subsurface objects
Citations: 34 🌍
Year: 2002 🖥️
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Automatic boundary detection and symmetry calculation in dermoscopy images of skin lesions
Citations: 30 🔬
Year: 2011 🧠
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Efficient segmentation with the convex local-global fuzzy Gaussian distribution active contour for medical applications
Citations: 26 💉
Year: 2015 📊
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Intelligent shape feature extraction and indexing for efficient content-based medical image retrieval
Citations: 26 🔍
Year: 2004 🏥
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Recognition of emotional states in natural human-computer interaction
Citations: 23 😐
Year: 2008 🤖
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An integral active contour model for convex hull and boundary extraction
Citations: 22 🏞️
Year: 2009 🔧
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Threat assessment using visual hierarchy and conceptual firearms ontology
Citations: 19 🔫
Year: 2015 🚨
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Search space partitioning using convex hull and concavity features for fast medical image retrieval
Citations: 19 🔎
Year: 2004 🏥
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Optimal set of features for accurate skin cancer diagnosis
Citations: 18 🩺
Year: 2014 🧬
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Skin lesion feature vectors classification in models of a Riemannian manifold
Citations: 17 🏥
Year: 2015 🔬
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Automatic feature extraction and recognition for digital access of books of the Renaissance
Citations: 15 📚
Year: 2000 🔍
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Sparse representation wavelet-based classification
Citations: 11 🖼️
Year: 2018 💻
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A novel classification system for dysplastic nevus and malignant melanoma
Citations: 11 🩺
Year: 2016 🌟
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New accurate automated melanoma diagnosing systems
Citations: 11 🧬
Year: 2015 ⚕️
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Weapon ontology annotation using boundary describing sequences
Citations: 11 🔫
Year: 2012 🛡️
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Active contour directed by the Poisson gradient vector field and edge tracking
Citations: 10 🖥️
Year: 2021 📉
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Comparing 2D borders using regular structures
Citations: 10 🔍
Year: 1994 🖼️
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Support vector machine skin lesion classification in Clifford algebra subspaces
Citations: 9 🩺
Year: 2019 📈
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Poisson equation solution and its gradient vector field to geometric features detection
Citations: 9 🔬
Year: 2018 🔧
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Integration of low-level and ontology-derived features for automatic weapon recognition and identification
Citations: 9 🛡️
Year: 2011 💡
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Monotonic vector forces and Green’s theorem for automatic area calculation
Citations: 9 🔍
Year: 2007 📐
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A new automatic concavity extraction model
Citations: 9 🔍
Year: 2006 🧠
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Classification with stochastic learning methods and convolutional neural networks
Citations: 8 🤖
Year: 2020 💻
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From shape to threat: exploiting the convergence between visual and conceptual organization for weapon identification and threat assessment
Citations: 8 🔫
Year: 2013 🛡️
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Skin lesion image classification using sparse representation
Citations: 8 🩺
Year: 2018 📊