Madhavi Tota | Computer Science | Best Researcher Award

Mrs. Madhavi Tota | Computer Science | Best Researcher Award

Mrs. Madhavi Tota, G H Raisoni,Β  India.

Mrs. Madhavi Srinivas Sadu, Assistant Professor (Senior Grade) in the Department of Computer Science and Engineering, has over 18 years of teaching experience and a strong academic background in machine learning, big data security, and information privacy. She has authored 28 publications, including 12 international journal papers and 3 book chapters, and holds professional memberships in ISTE, IE, and INSC. Her research focuses on privacy-preserving methods and technological innovation, making her a significant contributor to the academic community.

Profile

ORCID ID

Early Academic Pursuits

Mrs. Madhavi Srinivas Sadu began her academic journey with a Bachelor’s degree in Computer Science and Engineering (B.E. CSE) from Prof. Ram Meghe Institute of Technology & Research, Badnera, affiliated with SGBAU, Amravati University, where she explored native XML databases through her project on Xindices. Her passion for computing led her to pursue M.Tech in Computer Science and Engineering from Vivekananda Institute of Technology & Science, Karimnagar, under JNTU Hyderabad, where she researched performance improvements in parsers using PEG (Parsing Expression Grammar). She has recently submitted her Ph.D. thesis at Raisoni University, Saikheda, focused on Information Security and Privacy Preservation in Big Data using Machine Learning.

Professional Endeavors

With over 18 years of rich teaching experience, Mrs. Madhavi Srinivas has steadily contributed to academia. She began as an Adhoc Lecturer at Kavikulguru Institute of Technology & Science, Ramtek, followed by a brief tenure at Rajiv Gandhi College of Engineering, Research & Technology, Chandrapur, where she later secured a permanent position as an Assistant Professor (Senior Grade). Since 2007, she has been actively involved in nurturing undergraduate students in Computer Science and Engineering, making substantial contributions to the academic ecosystem of her institution.

Contributions and Research Focus On Computer Science

Mrs. Madhavi Srinivas’s research focus lies at the intersection of machine learning, data security, and privacy. Her doctoral research centers on utilizing machine learning algorithms to ensure data privacy in Big Data environments, a pressing concern in today’s digital era. She has authored 28 research publications, including 12 papers in international journals and 3 book chapters, underscoring her commitment to advancing knowledge in her field. Her work bridges foundational computing concepts with emerging technologies, aiming for real-world solutions in information security.

Impact and Influence

Her influence extends beyond classroom teaching into academic administration and curriculum development. As a member of the Board of Studies and Question Paper Moderation Committee at Gondwana University, she has played a pivotal role in shaping the academic policies and examination standards. She has served as an organizer and speaker in national-level programs like AICTE-ISTE workshops and soft computing seminars, disseminating advanced computing knowledge to faculty and students alike. Her involvement in these roles reflects her leadership in academic governance and faculty development.

Research Skills

Mrs. Madhavi brings a diverse and practical skill set to her research. Her expertise includes data mining, algorithm design, parser optimization, and machine learning techniques. She has hands-on experience in developing intelligent systems for data privacy, and her work is grounded in both analytical rigor and software implementation. Her teaching subjects further reflect her technical command over areas like deep learning and computer architecture, making her a valuable resource for interdisciplinary research initiatives.

Awards and Honors

Her professional journey has been marked by multiple accolades and recognitions. Although a separate document details her achievements, it is noteworthy that she is a life member of several esteemed bodies, including the Indian Society for Technical Education (ISTE), Institution of Engineers (IE), and INSC. Her patent filing, participation in 13 national conferences/workshops, and recognized book chapter publications are testaments to her active scholarly involvement.

Academic Citations

While specific citation metrics are not provided, her 28 publications and her longstanding association with recognized academic committees and professional bodies indicate a healthy academic footprint. Her peer-reviewed papers in international journals contribute to the scholarly discourse in Big Data privacy, security frameworks, and parser performance optimization, areas vital to the advancement of secure computing environments.

Legacy and Future Contributions

With nearly two decades of service in academia, Mrs. Madhavi Srinivas has built a legacy of academic dedication, technical innovation, and mentorship. Her future ambitions likely include further refining machine learning applications in secure data analytics, expanding her patent portfolio, and potentially guiding doctoral candidates in emerging computing fields. Her continued engagement with curriculum design, student mentorship, and national educational forums promises enduring contributions to both computer science education and technological research in India.

Publications Top Notes

IBMESR: Towards Next-Generation Big Data Security with Integrated Blockchain Model for Efficient, Scalable, and Robust Operations

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 πŸ”¬. With a Ph.D. from the Bulgarian Academy of Sciences πŸŽ“, 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 πŸ“š. His contributions to computer vision and AI-driven diagnostics πŸ€– have earned him international recognition. ✨

🌟 Professional Profile

πŸŽ“ 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.

πŸ’Ό 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.

πŸ”¬ Contributions and Research Focus On Data ScienceΒ 

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.

πŸ† 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. πŸ“š

  • 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. πŸš—

  • 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. πŸ”’

  • 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. πŸŽ–

πŸš€ 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.

πŸ“šPublications Top Notes

  • A system for reconstructing and visualizing three-dimensional objects
    Citations: 70 πŸ“Š
    Year: 2001 πŸ—“οΈ

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

  • A new active convex hull model for image regions
    Citations: 36 πŸ“
    Year: 2006 πŸ”

  • Dermoscopic diagnosis of melanoma in a 4D space constructed by active contour extracted features
    Citations: 35 πŸ’‘
    Year: 2012 πŸ§‘β€βš•οΈ

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

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

  • Efficient segmentation with the convex local-global fuzzy Gaussian distribution active contour for medical applications
    Citations: 26 πŸ’‰
    Year: 2015 πŸ“Š

  • Intelligent shape feature extraction and indexing for efficient content-based medical image retrieval
    Citations: 26 πŸ”
    Year: 2004 πŸ₯

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

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

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

  • Search space partitioning using convex hull and concavity features for fast medical image retrieval
    Citations: 19 πŸ”Ž
    Year: 2004 πŸ₯

  • 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 πŸ₯
    Year: 2015 πŸ”¬

  • Automatic feature extraction and recognition for digital access of books of the Renaissance
    Citations: 15 πŸ“š
    Year: 2000 πŸ”

  • Sparse representation wavelet-based classification
    Citations: 11 πŸ–ΌοΈ
    Year: 2018 πŸ’»

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

  • New accurate automated melanoma diagnosing systems
    Citations: 11 🧬
    Year: 2015 βš•οΈ

  • Weapon ontology annotation using boundary describing sequences
    Citations: 11 πŸ”«
    Year: 2012 πŸ›‘οΈ

  • Active contour directed by the Poisson gradient vector field and edge tracking
    Citations: 10 πŸ–₯️
    Year: 2021 πŸ“‰

  • Comparing 2D borders using regular structures
    Citations: 10 πŸ”
    Year: 1994 πŸ–ΌοΈ

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

  • Poisson equation solution and its gradient vector field to geometric features detection
    Citations: 9 πŸ”¬
    Year: 2018 πŸ”§

  • Integration of low-level and ontology-derived features for automatic weapon recognition and identification
    Citations: 9 πŸ›‘οΈ
    Year: 2011 πŸ’‘

  • Monotonic vector forces and Green’s theorem for automatic area calculation
    Citations: 9 πŸ”
    Year: 2007 πŸ“

  • A new automatic concavity extraction model
    Citations: 9 πŸ”
    Year: 2006 🧠

  • Classification with stochastic learning methods and convolutional neural networks
    Citations: 8 πŸ€–
    Year: 2020 πŸ’»

  • From shape to threat: exploiting the convergence between visual and conceptual organization for weapon identification and threat assessment
    Citations: 8 πŸ”«
    Year: 2013 πŸ›‘οΈ

  • Skin lesion image classification using sparse representation
    Citations: 8 🩺
    Year: 2018 πŸ“Š