Dr. Srikanth Yadav moraboena
Vignan's Foundation for Science Technology and Research, Tirumala Engineering College, Pondicherry University, Guru Nanak Engineering College, Malineni Lakshmaiah Engineering College
About
Dr. M. Srikanth Yadav was born in India on June 10, 1980. He received his Bachelor of Technology and Master of Technology degrees in Information Technology from JNTUH University, Hyderabad, Telangana, India, in 2003 and 2010, respectively. He completed his PhD in Computer Science and Engineering in March 2024 at Pondicherry University, Puducherry, India. With a total of 22 years of teaching experience, he is currently working as Officiating Associate Professor in the Department of IT at Vignan's Foundation for Science, Technology & Research (Deemed to be University) in the Guntur district of Andhra Pradesh, India. He has many peer-reviewed publications, and his research interests include machine learning, deep learning, and intrusion detection systems.
Employment
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Vignan's Foundation for Science Technology and Research Associate Professor2020 - Present
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Tirumala Engineering College Associate Professor2013 - 2020
Education
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Pondicherry University Ph.D2018 - 2024
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Guru Nanak Engineering College M.Tech2007 - 2010
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Malineni Lakshmaiah Engineering College B.Tech1999 - 2003
Projects & Funding
Projects & funding information is unavailable.
Publications (37)
- Spatial–Temporal Intrusion Detection Framework for Enhanced Network Security in Distributed Systems Save
- Real-Time Smart Energy Consumption Analysis Using Edge AI and Secure IoT Frameworks Save
- Intelligent Intrusion Detection Systems for Enhancing Security in IoT and Cyber-Physical Networks Save
- Enhancing Institutional Resilience Through Inclusive Blended Learning in Crisis Contexts Save
- AI-Driven Adaptive Framework for Real-Time Data Quality Enhancement in Dynamic Social Media Streams Save
- Low-cost wireless EMG-controlled prosthetic arm using 3D printing Save
- Blockchain for ethical AI model Validation Save
- AI-driven big data analytics: Unveiling insights for next-gen intelligent systems Save
- A hybrid neuro-fusion model for network intrusion detection using non-symmetric deep autoencoders and transformer-augmented gradient boosting Save
- Enhancing Institutional Resilience Through Inclusive Blended Learning in Crisis Contexts Save