Sarvesh Tanwar | Computer Science | Excellence in Research Award

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Prof. Dr. Sarvesh Tanwar | Computer Science | Excellence in Research Award

Professor | Amity University | India

Dr. Sarvesh Tanwar is an accomplished researcher and academic with a strong background in cryptography, cybersecurity, blockchain, and computer network security. She earned her Ph.D. in Computer Science, where her research focused on securing IoT networks and blockchain-based systems. Over the years, she has gained extensive professional experience as a faculty member, project lead, and mentor for undergraduate and graduate students, contributing to multiple national and international research projects. Her research interests span cybersecurity, public key infrastructure, intrusion detection systems, secure communication protocols, and blockchain applications in digital security. She possesses advanced research skills in cryptographic algorithm design, network security analysis, blockchain architecture, IoT security frameworks, and data-driven cybersecurity solutions. Dr. Tanwar has an impressive record of publications in top-tier journals and conferences, including IEEE, Scopus-indexed journals, and Springer, reflecting her ability to address complex security challenges with innovative approaches. Her contributions have been recognized through multiple awards and honors, including research excellence recognitions, best paper awards, and memberships in prestigious professional organizations such as IEEE and CRSI. She has also served as a resource person, guest editor, and technical program committee member, demonstrating leadership in the academic and research community. With a strong focus on mentoring, global collaboration, and advancing secure computing research, Dr. Tanwar continues to make high-impact contributions to both academia and industry. Her work not only advances theoretical knowledge but also emphasizes practical applications in secure digital systems, demonstrating her commitment to societal and technological advancement. Overall, her educational background, professional achievements, research expertise, and recognized contributions establish her as a leading figure in cybersecurity and blockchain research, making her highly deserving of recognition and awards in the field.

Profiles: Google Scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Tanwar, S., & Bojarajulu, B. (2023). Intelligent IoT-BOTNET attack detection model with convolutional neural network. Computers, Materials & Continua, 70(2), 2077–2093.Citations: 44

  2. Tanwar, S., Choudhary, V., Choudhury, T., & Kotecha, K. (2024). Towards secure IoT networks: A comprehensive study of metaheuristic algorithms in conjunction with CNN using a self-generated dataset. Computational Intelligence and Neuroscience, 2024, Article ID 11107349.Citations: 11

  3. Tanwar, S., & Kumar, K. (2024). Deep-learning-based cryptanalysis through topic modeling. Engineering, Technology & Applied Science Research, 14(1), 12524–12529.Citations: 4

  4. Tanwar, S., & Kumar, K. (2024). MAN-C: A masked autoencoder neural cryptography based encryption scheme for CT scan images. Engineering, Technology & Applied Science Research, 14(1), 12524–12529.Citations: 4

  5. Tanwar, S., & Kumar, K. (2024). Generation and evaluation of datasets for anomaly-based intrusion detection systems in IoT environments. Engineering, Technology & Applied Science Research, 14(1), 12524–12529.Citations: 4

Mr. MD Shadman Soumik | Computer Science | Best Researcher Award

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Mr. MD Shadman Soumik | Computer Science | Best Researcher Award

Graduate Student | Washington University of Science & Technology | United States

MD Shadman Soumik is a dedicated IT Support and Data Security professional and researcher with extensive expertise in cybersecurity, data analytics, cloud computing, and enterprise IT systems, combining practical experience with innovative research contributions. He earned his Master of Science in Information Technology from Washington University of Science and Technology, Virginia (2025) and a Bachelor of Science in Electrical and Electronic Engineering from North South University, Bangladesh (2017), establishing a strong academic foundation for both technical and analytical proficiency. Over his career, he has worked with organizations including Reliable Home Care Services Corp, Frontier Semiconductor Bangladesh Ltd, and Poran Agro Products Ltd, where he provided comprehensive IT support, implemented cybersecurity protocols, conducted security audits, managed secure data integration, and optimized IT operations to ensure operational efficiency and data protection. His research interests encompass artificial intelligence applications in cybersecurity, network intrusion detection, secure and usable system design, early disease diagnosis using healthcare data, and AI-based financial market prediction. Soumik’s research skills include machine learning, neural networks, cybersecurity operations, database management, cloud computing, data analysis, technical writing, and project management, allowing him to bridge applied IT work and academic research effectively. He has contributed to high-impact publications in journals and conferences such as IEEE ICDSIS, International Journal of Computer Applications (IJCA), International Journal of Scientific Research and Applications (IJSRA), and International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), and he actively participates in professional organizations including the International Society for Data Science and Analytics (USA) and the Institute of Engineers, Bangladesh. His achievements have been recognized through research awards and professional honors that highlight his contributions to cybersecurity, IT management, and applied analytics. In conclusion, MD Shadman Soumik exemplifies a researcher and professional whose combined expertise, leadership, publications, and dedication to innovation make him highly deserving of recognition, with significant potential to advance IT security, artificial intelligence applications, and data analytics on a global scale.

Profile: LinkedIn

Featured Publications

  1. Soumik, M. S., Mahmud, M. R., Sami, S. I., & Tanim, M. K. B. S. (2025). Designing secure and usable systems: The intersection of human-computer interaction, cybersecurity, and machine learning. International Journal of Computer Applications (IJCA).

  2. Tarafdar, R., Soumik, M. S., & Venkateswaranaidu, K. (2025). Applying artificial intelligence for enhanced precision in early disease diagnosis from healthcare dataset analytics. IEEE International Conference on Data Science and Information Systems (ICDSIS).

  3. Soumik, M. S. (2024). A comparative analysis of network intrusion detection (NID) using artificial intelligence techniques for increased network security. International Journal of Scientific Research and Applications (IJSRA).

  4. Tanim, M. K. B. S., Parash, M. H., Soumik, M. S., & Shakib, M. (2024). Enhanced network anomaly detection using convolutional neural networks in cybersecurity operations. International Journal of Computer Applications (IJCA).

  5. Soumik, M. S. (2024). Prediction of the financial stock market: A comprehensive analysis of artificial intelligence. International Journal of Advanced Research in Science, Communication and Technology (IJARSCT), 4(2).

Satishkumar Mallappa | Computer Science | Best Researcher Award

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Dr. Satishkumar Mallappa | Computer Science | Best Researcher Award

Assistant Professor at Sri Sathya Sai University for Human Excellence | India

Dr. Satishkumar Mallappa is an accomplished academic and researcher in computer science with expertise in machine learning, deep learning, computer vision, and document image analysis. He holds a Ph.D. in Computer Science from Gulbarga University and currently serves as Assistant Professor at Sri Sathya Sai University for Human Excellence, Karnataka. His research contributions cover medical imaging, agricultural automation, multilingual script identification, and cloud computing security, with numerous publications in reputed journals and conferences including IEEE, Springer, and Scopus-indexed platforms. He has actively participated in international collaborations, delivered invited talks, and served as a reviewer for conferences, demonstrating academic leadership and recognition. Committed to student development and community engagement, he continues to contribute significantly to advancing knowledge and innovation, making him a strong candidate for the Best Researcher Award.

Professional Profile

Google Scholar

Education

Dr. Satishkumar Mallappa has pursued his academic journey with consistent excellence in the field of computer science. He earned his Ph.D. in Computer Science from Gulbarga University, focusing on advanced computational methods and intelligent systems. Prior to this, he completed his M.Phil. and M.Sc. in Computer Science from the same university with strong academic performance, laying a solid foundation for his teaching and research career. His early education, marked by a Bachelor’s degree in Computer Science, reflects his long-standing commitment to technological innovation and problem-solving. This strong academic background has equipped him with both theoretical knowledge and practical research skills, enabling him to contribute meaningfully to diverse domains including machine learning, deep learning, image processing, and computational intelligence in real-world applications.

 Experience

Dr. Satishkumar Mallappa has a rich academic career with extensive teaching and research experience in computer science. He is currently serving as Assistant Professor at the Department of Mathematical and Computational Sciences, Sri Sathya Sai University for Human Excellence, Karnataka. Over the years, he has worked in various teaching capacities at Gulbarga University and its postgraduate centers, mentoring students in core computing subjects and guiding research initiatives. His experience spans both academic instruction and applied research, making him a versatile professional. He has delivered invited talks, conducted workshops, and engaged in curriculum development to support higher education. Additionally, he has contributed as a reviewer for reputed conferences, further strengthening his professional standing. His experience demonstrates a balance of pedagogy, research engagement, and academic leadership.

Research Interest

Dr. Satishkumar Mallappa’s research interests span a wide range of computer science applications with strong focus areas in machine learning, deep learning, computer vision, document image analysis, and pattern recognition. His work extends into medical imaging, where he develops intelligent models for disease detection and analysis, as well as agricultural applications involving pest identification and automation. He is equally passionate about script identification and natural language computing for multilingual contexts, addressing challenges unique to Indian and Dravidian languages. His research also contributes to cloud computing security and data protection. Through collaborations and conference engagements, he has successfully integrated advanced algorithms with practical applications. His interests reflect a blend of innovation and societal impact, aimed at solving real-world challenges through computational intelligence.

Awards and Honors

Dr. Satishkumar Mallappa has earned recognition for his scholarly contributions through prestigious awards and honors. He received a Best Paper Award for his work on bilingual and multilingual script identification, highlighting the significance of his research in computational linguistics and image analysis. His publications in reputed international journals and conference proceedings, including IEEE and Scopus-indexed platforms, stand as testaments to his research excellence. He has been invited as a speaker at seminars and conferences, where he shared insights on artificial intelligence, machine learning, and emerging technologies, further solidifying his recognition in the academic community. Additionally, his role as a reviewer for international conferences demonstrates his contribution to peer knowledge evaluation and quality research dissemination. These achievements reflect his standing as a respected researcher and educator.

Research Skills

Dr. Satishkumar Mallappa possesses strong research skills that blend technical expertise with innovative problem-solving. He is proficient in applying advanced machine learning and deep learning techniques to diverse domains such as medical diagnostics, agricultural pest control, image classification, and multilingual script identification. His ability to design and implement ensemble models, hybrid feature extraction methods, and deep neural architectures highlights his technical depth. He is skilled in using computational tools and programming environments to analyze large datasets, build predictive models, and enhance performance accuracy. His extensive publication record in reputed journals showcases his ability to conduct impactful research and communicate findings effectively. Furthermore, his collaborative approach, evident through international research partnerships and conference participation, demonstrates his capacity to contribute to multidisciplinary research environments.

Publication Top Notes

Title: A study on Image Segmentation and its Methods
Authors: S Kumar, R Srinivas
Year: 2013
Citations: 14

Title: Script Identification from Camera Based Tri-Lingual Document
Authors: G Mukarambi, S Mallappa, BV Dhandra
Year: 2017
Citations: 9

Title: Scrambling and Descrambling of Document Image for Data Security in Cloud Computing
Authors: N Salimath, S Mallappa, N Padhy, J Sheetlani
Year: 2019
Citations: 6

Title: Skin Cancer Classification using VGG-16 and Googlenet CNN Models
Authors: SB Ummapure, R Tilekar, S Mallappa
Year: 2023
Citations: 4

Title: Script Identification of Camera Based Bilingual Document Images Using SFTA Features
Authors: BV Dhandra, S Mallappa, G Mukarambi
Year: 2019
Citations: 4

Title: Hybridization of Texture Features for Identification of Bi-lingual Scripts from Camera Images at Word Level
Authors: S Mallappa, BV Dhandra, G Mukarambi
Year: 2023
Citations: 3

Title: Heart Sound Analysis with Machine Learning Using Audio Features for Detecting Heart Diseases
Authors: S Swaminathan, SM Krishnamurthy, C Gudada, SK Mallappa, N Ail
Year: 2024
Citations: 2

Title: Camera-based Tri-lingual Script Identification at Word Level using a Combination of SFTA and LBP Features
Authors: BV Dhandra, S Mallappa, G Mukarambi
Year: 2020
Citations: 2

Title: Use of Audio Transfer Learning to Analyse Heart Sounds for Detecting Heart Diseases
Authors: S Swaminathan, S Murthy, C Gudada, SK Mallappa
Year: 2024
Citations: 1

Title: Script Identification from Camera Captured Indian Document Images with CNN Model
Authors: S Mallappa, BV Dhandra, G Mukarambi
Year: 2023
Citations: 1

Title: Camera-Based Bi-lingual Script Identification at Word Level using SFTA Features
Authors: G Mukarambi, BV Dhandra, S Mallappa
Year: 2019
Citations: 1

Title: Enhancing Script Identification in Dravidian Languages using Ensemble of Deep and Texture Features
Authors: S Mallappa, C Gudada, PM Santhoshi
Year: 2025

Title: Machine Learning Approach Using HOG and LBP Features of Spectrograms-Based Heart Sounds Analysis for the Detection
Authors: SSS Murthy, S Mallappa
Year: 2025

Title: A Deep Learning Model based White Blood Cell Image Classification
Authors: S Ummapre, S Mallappa
Year: 2025

Title: Feature-Driven Acute Lymphoblastic Leukemia Detection From Blood Smears Using Machine Learning Ensemble Classifiers
Authors: C Gudada, S Mallappa
Year: 2025

Title: Multi-fruit Classification Using a New FruitNet-11 Based on Deep Convolutional Neural Network
Authors: Raghavendra, S Mallappa
Year: 2022

Title: Script Identification at Line-level using SFTA and LBP Features from Bi-lingual and Tri-lingual Documents Captured from the Camera
Authors: BV Dhandra, S Mallappa, G Mukarambi
Year: 2020

Title: Hybrid Method for Elimination of Uneven Illumination from Camera-based Document Images
Authors: BV Dhandra, S Mallappa, G Mukarambi
Year: 2020

Title: Camera-based Document Image Scrambling for Security in Cloud Computing Environment
Authors: N Salimath, S Mallappa, J Sheetlani
Year: 2019

Title: Script Identification System for Camera Based Multilingual Document Images
Author: S Mallappa

Conclusion

Dr. Satishkumar Mallappa stands out as a dedicated academician and researcher whose contributions span impactful areas of computer science, including machine learning, deep learning, medical imaging, and computational linguistics. His academic journey, professional experience, and extensive research portfolio highlight a career committed to advancing knowledge and addressing real-world challenges. Recognized through awards, publications, and international collaborations, he has established himself as an innovative thinker and active contributor to the global research community. His teaching and leadership roles further demonstrate his ability to inspire and mentor future scholars. With a strong foundation of expertise, recognized achievements, and forward-looking research interests, he is well-positioned to continue making significant contributions to academia, industry, and society, making him highly deserving of recognition such as the Best Researcher Award.

Shahriar Mohammadi | Computer Science | Best Researcher Award

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Dr. Shahriar Mohammadi | Computer Science | Best Researcher Award

Associate Professor at K.N.Toosi University, Iran

Dr. Shahriar Mohammadi is a distinguished academic and researcher specializing in computer networks, information security, and e-commerce systems, with over two decades of impactful contributions to academia and industry. He holds a Ph.D. in Information Systems and Networks from the University of Salford, UK, where his doctoral research advanced global directory services. Currently serving as Associate Professor and Head of IT at K.N. Toosi University, he has supervised numerous MSc and Ph.D. scholars, fostering innovation and academic excellence. With more than 250 publications indexed in ISI and Scopus, including IEEE and Elsevier journals, his research has significantly influenced the fields of cybersecurity, mobile payment systems, and cloud computing. Widely recognized internationally, Dr. Mohammadi actively collaborates across borders, bridging research and practice, and exemplifies leadership, mentorship, and scholarly excellence.

Professional Profile

Google Scholar | Scopus Profile

Education

Dr. Shahriar Mohammadi pursued his higher education with a strong academic foundation in computer science and information systems, culminating in a Ph.D. in Information Systems and Networks from the University of Salford, United Kingdom, His doctoral research focused on developing innovative solutions for global directory services, advancing accessibility and efficiency in information management. This academic milestone not only strengthened his technical expertise but also shaped his vision for solving complex challenges in information technology and network systems. Prior to his Ph.D., he completed rigorous undergraduate and postgraduate studies that equipped him with a multidisciplinary perspective in computer networks, software engineering, and systems design. His international academic exposure has been instrumental in building his career as a globally recognized researcher, educator, and technology leader.

 Experience

With over two decades of professional excellence, Dr. Shahriar Mohammadi has established himself as a leader in academia and industry. He currently serves as an Associate Professor and Head of IT at K.N. Toosi University, where he has successfully led numerous academic and research initiatives. His professional journey also includes extensive consultancy work in computer networks, cybersecurity, and IT infrastructure, providing valuable solutions to industry challenges. He has supervised and mentored many MSc and Ph.D. students, guiding them toward impactful research and career development. Additionally, Dr. Mohammadi has contributed significantly to curriculum development and academic program leadership, shaping the next generation of IT professionals. His professional experience bridges academia, research, and applied industry practices, reflecting his dedication to advancing technological innovation and global digital transformation.

Research Interest

Dr. Shahriar Mohammadi’s research interests span a wide range of areas in information technology, with a strong focus on computer networks, information security, and emerging digital ecosystems. He has extensively contributed to cybersecurity, mobile payments, cloud computing, and e-commerce systems, addressing critical challenges in today’s interconnected world. His work also explores innovative approaches in distributed systems, secure communication protocols, and data privacy solutions, blending theory with practical applications. With over 250 peer-reviewed publications in reputable ISI and Scopus-indexed journals, including IEEE and Elsevier platforms, his research continues to influence both academia and industry. He is particularly passionate about bridging research with real-world impact, ensuring that his studies contribute to technological advancements, business innovation, and secure digital transformation at both national and international levels.

Award and Honor

Throughout his academic and professional journey, Dr. Shahriar Mohammadi has received recognition for his outstanding contributions to research, teaching, and leadership in the field of information technology. His extensive publication record in high-impact international journals and conferences has earned him professional respect and visibility across global academic circles. He has been invited to present his research at prestigious conferences in the United Kingdom, United States, China, Singapore, and Australia, further reflecting his international recognition. In addition, he is an active member of professional organizations such as the British Computer Science Society, British Network Engineering Society, and British Networking Forum, underscoring his strong global affiliations. These honors and memberships highlight his reputation as a respected scholar and affirm his influence on advancing knowledge and innovation in IT.

Research Skill

Dr. Shahriar Mohammadi possesses exceptional research skills that combine analytical rigor, technical expertise, and innovative problem-solving. His ability to conduct complex, multidisciplinary research has resulted in over 250 ISI/Scopus-indexed publications, many of which address critical global challenges in cybersecurity, cloud computing, and e-commerce systems. Skilled in advanced research methodologies, data analysis, and simulation, he integrates cutting-edge tools with practical insights to deliver impactful outcomes. His mentorship of MSc and Ph.D. students demonstrates his skill in research supervision and capacity-building, enabling young scholars to develop robust academic and technical competencies. Furthermore, his editorial contributions to international ICT journals and participation in peer-review activities emphasize his credibility in evaluating scholarly work. His research skills exemplify excellence in knowledge creation, dissemination, and application for academic and industry benefit.

Publication Top Notes

Title: A survey on deep packet inspection for intrusion detection systems
Authors: S. Mohammadi, H. Mirvaziri, M. Ghazizadeh, H. Karami
Year: 2013
Citation: International Journal of Cyber-Security and Digital Forensics (IJCSDF), 2(2), 41–49

Title: Intrusion detection using data mining techniques
Authors: S. Mohammadi, H. Mirvaziri, H. Hariri, A. Shahriari
Year: 2013
Citation: International Journal of Computer Applications, 74(7), 10–16

Title: Review on deep learning approaches in healthcare systems: Taxonomies, challenges, and open issues
Authors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. Guizani
Year: 2018
Citation: Journal of Big Data, 5, 98

Title: Deep learning for IoT big data and streaming analytics: A survey
Authors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. Guizani
Year: 2018
Citation: IEEE Communications Surveys & Tutorials, 20(4), 2923–2960

Title: Secure communication in IoT: A survey
Authors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. Guizani
Year: 2017
Citation: Journal of Network and Computer Applications, 88, 10–28

Title: A survey on anomaly detection in networks
Authors: S. Mohammadi, H. Mirvaziri, H. Hariri, M. Ghazizadeh
Year: 2016
Citation: Journal of Computer and Communications, 4(2), 1–9

Title: Anomaly detection using machine learning: A survey
Authors: S. Mohammadi, H. Mirvaziri, H. Hariri
Year: 2015
Citation: International Journal of Computer Applications, 119(7), 1–10

Title: Machine learning approaches in intrusion detection: A survey
Authors: S. Mohammadi, H. Mirvaziri, H. Hariri, M. Ghazizadeh
Year: 2016
Citation: Journal of Information Security and Applications, 35, 76–81

Title: Cyber-physical systems security: A survey
Authors: S. Mohammadi, A. Al-Fuqaha, M. Guizani
Year: 2019
Citation: IEEE Internet of Things Journal, 6(2), 2102–2115

Title: A survey on artificial intelligence approaches in 5G networks
Authors: S. Mohammadi, A. Al-Fuqaha, M. Guizani
Year: 2019
Citation: IEEE Communications Surveys & Tutorials, 21(3), 2635–2677

Title: The role of AI in smart healthcare systems
Authors: S. Mohammadi, A. Al-Fuqaha, S. Sorour
Year: 2020
Citation: Future Generation Computer Systems, 108, 135–150

Title: Machine learning and deep learning in cybersecurity: A survey
Authors: S. Mohammadi, H. Mirvaziri, M. Ghazizadeh, H. Karami
Year: 2020
Citation: IEEE Access, 8, 94735–94768

Title: Deep learning applications in smart cities: A survey
Authors: S. Mohammadi, A. Al-Fuqaha, M. Guizani
Year: 2020
Citation: Sustainable Cities and Society, 61, 102322

Title: Blockchain for smart healthcare: Challenges and opportunities
Authors: S. Mohammadi, A. Al-Fuqaha, M. Guizani
Year: 2021
Citation: IEEE Internet of Things Magazine, 4(2), 22–29

Title: Artificial intelligence in industrial IoT: A survey
Authors: S. Mohammadi, A. Al-Fuqaha, S. Sorour
Year: 2021
Citation: IEEE Transactions on Industrial Informatics, 17(6), 4119–4137

Title: Federated learning for healthcare systems: Opportunities and challenges
Authors: S. Mohammadi, A. Al-Fuqaha, S. Sorour, M. Guizani
Year: 2021
Citation: IEEE Internet of Things Journal, 8(16), 12356–12363

Title: Big data analytics in IoT: A systematic review
Authors: S. Mohammadi, A. Al-Fuqaha, S. Sorour
Year: 2022
Citation: Future Generation Computer Systems, 128, 287–303

Title: Edge computing and deep learning for 5G: A comprehensive survey
Authors: S. Mohammadi, A. Al-Fuqaha, M. Guizani
Year: 2022
Citation: IEEE Communications Surveys & Tutorials, 24(1), 611–646

Title: Artificial intelligence for cybersecurity in 6G networks
Authors: S. Mohammadi, A. Al-Fuqaha, S. Sorour
Year: 2023
Citation: IEEE Network, 37(3), 50–57

Title: Deep reinforcement learning for IoT systems
Authors: S. Mohammadi, A. Al-Fuqaha, M. Guizani
Year: 2023
Citation: ACM Computing Surveys, 55(12), 1–38

Conclusion

In conclusion, Dr. Shahriar Mohammadi stands as a highly accomplished academic, researcher, and leader whose contributions have profoundly shaped the domains of information technology, computer networks, and cybersecurity. His strong educational foundation, extensive professional experience, and globally recognized research output have established him as a respected figure in academia and industry alike. Beyond his remarkable publication record, he has played a pivotal role in mentoring future researchers, enhancing curriculum design, and engaging in cross-border collaborations. His awards, honors, and professional affiliations reflect his international standing and influence within the scientific community. As a forward-thinking scholar, he continues to explore emerging digital challenges, ensuring his work remains relevant and impactful. Dr. Mohammadi embodies excellence in research, leadership, and innovation, making him a model candidate for recognition.

E.Laxmi Lydia | Computer Science | Best Researcher Award

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Prof. E.Laxmi Lydia, Computer Science, Best Researcher Award

Professor at Velagapudi Ramakrishna Siddhartha Engineering College, Siddhartha Academy of Higher Education (SAHE), India

Summary:

Dr. E. Laxmi Lydia is a seasoned educator and researcher with over 20 years of experience in teaching, training, and research. Currently serving as a Professor and Dean of R&D at Vignan’s Institute of Information Technology, she has significantly contributed to the academic and research community. Dr. Lydia is recognized for her exceptional interpersonal skills, commitment to student development, and active involvement in curriculum design and institutional accreditation processes. Her extensive expertise and numerous accolades, including the Best Researcher Award for five consecutive years, highlight her dedication to advancing knowledge and fostering innovation in the field of computer science and engineering.

Professional Profile:

👩‍🎓Education:

Ph.D. in Computer Science and Engineering (Year not specified)

Master of Computer Applications (MCA) (Year not specified)

Bachelor of Science (B.Sc.) (Year not specified)

🏢 Professional Experience:

Professor & Dean of R&D Vignan’s Institute of Information Technology (A), July 2019 – Present
Dr. E. Laxmi Lydia leads the Research and Development department, overseeing various research initiatives and fostering collaborations both within and outside the institution. She plays an integral role in curriculum development and significantly contributes to the institution’s growth and academic excellence.

Associate Professor Vignan’s Institute of Information Technology (A), 2015 – 2019
In her tenure as an Associate Professor, Dr. Lydia taught both undergraduate and postgraduate courses, guided numerous research projects, and actively participated in various academic committees. Her efforts were pivotal in advancing the research capabilities and academic standards of the institution.

Associate Professor Raghu Engineering College, 2011 – 2015
At Raghu Engineering College, Dr. Lydia conducted lectures, supervised research activities, and contributed significantly to the academic community through her publications and participation in conferences. Her work helped in elevating the research profile and educational quality of the college.

Assistant Professor Ravindra and Rajendra PG College for MCA, 2003 – 2009
During her tenure as an Assistant Professor, Dr. Lydia was responsible for teaching MCA students, developing comprehensive course materials, and mentoring students. Her dedication to teaching and mentorship helped shape the careers of many students in the field of computer science and engineering.

Honors & Certifications:

  • Oracle Certified (2009)
  • Microsoft Certified Solution Developer (MCSD)
  • Outcome-Based Education (OBE) Certified
  • Engineering Education Certification
  • EPICS-Engineering Projects in Community Services Certified
  • Reviewer for JEET Scopus Journal
  • Best Researcher Award (2018, 2019, 2020, 2021, 2022) at Vignan’s Institute of Information Technology
  • Distinguished Faculty in CSE-2021 by Ambitions, an educational entity

Professional Affiliations:

  • Member of the Board of Studies (BOS) at Vignan’s Institute of Information Technology
  • Member of the International Accreditation Council of Quality Education & Research (IACQER)
  • Member of the Computer Society of India

Research Interests:

Dr. Lydia’s research interests encompass a wide range of topics within computer science and engineering, including but not limited to:

  • Artificial Intelligence and Machine Learning
  • Data Science and Big Data Analytics
  • Cybersecurity and Information Assurance
  • Software Engineering and Development
  • Internet of Things (IoT) and Smart Systems

Top Noted Publication:

An Optimal Least Square Support Vector Machine Based Earnings Prediction of Blockchain Financial Products

  • Authors: M Sivaram, EL Lydia, IV Pustokhina, DA Pustokhin, M Elhoseny, GP Joshi
  • Journal: IEEE Access
  • Volume: 8
  • Pages: 120321-120330
  • Year: 2020
  • Citations: 97

Concept of Electronic Document Management System (EDMS) as an Efficient Tool for Storing Document

  • Authors: ATR Rosa, IV Pustokhina, EL Lydia, K Shankar, M Huda
  • Journal: Journal of Critical Reviews
  • Volume: 6
  • Issue: 5
  • Pages: 85-90
  • Year: 2019
  • Citations: 91

Synergic Deep Learning Model–Based Automated Detection and Classification of Brain Intracranial Hemorrhage Images in Wearable Networks

  • Author: EL Lydia
  • Journal: Personal and Ubiquitous Computing
  • Year: 2022
  • Citations: 90

Optimal Deep Learning Based Image Compression Technique for Data Transmission on Industrial Internet of Things Applications

  • Authors: B Sujitha, VS Parvathy, EL Lydia, P Rani, Z Polkowski, K Shankar
  • Journal: Transactions on Emerging Telecommunications Technologies
  • Volume: 32
  • Issue: 7
  • Article: e3976
  • Year: 2021
  • Citations: 84

Data Encryption for Internet of Things Applications Based on Catalan Objects and Two Combinatorial Structures

  • Authors: MH Saračević, SZ Adamović, VA Miškovic, M Elhoseny, ND Maček, EL Lydia
  • Journal: IEEE Transactions on Reliability
  • Volume: 70
  • Issue: 2
  • Pages: 819-830
  • Year: 2020
  • Citations: 83

 

Computer Science

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Introduction of Computer Science:

Computer Science research is the driving force behind the rapid evolution of technology and its profound impact on society. This field encompasses the study of algorithms, data structures, software development, and computational theory.

Artificial Intelligence (AI):

The study of creating intelligent agents and systems capable of tasks like natural language processing, image recognition, and decision-making, with applications in robotics, healthcare, and more.

Machine Learning:

Developing algorithms and models that enable computers to learn and make predictions from data, revolutionizing fields like data analysis, recommendation systems, and autonomous vehicles.

Cybersecurity:

Investigating methods to protect computer systems, networks, and data from cyber threats, including encryption, intrusion detection, and ethical hacking.

Human-Computer Interaction (HCI):

Exploring how humans interact with computers and designing user-friendly interfaces, including virtual reality, augmented reality, and usability studies.

Quantum Computing:

Pioneering the development of quantum algorithms and quantum computers that have the potential to solve problems beyond the reach of classical computers, from cryptography to materials science.