About
Dr. Sunil Kumar is an Associate Head & Associate Professor in the Department of Computer Engineering and Applications, GLA University, Greater Noida (India). He received a B. Tech (CSE) from Kurukshetra University, Kurukshetra, an M.Tech (CSE) from MMU, Ambala, and a Ph.D. (CSE) from UPES, Dehradun, India. He has more than 20+ years of teaching and industry experience. Before joining GLA University, he worked with reputed NAAC-accredited universities such as UPES, Dehradun, Amity University Madhya Pradesh, Chitkara University, Rajpura, Punjab, etc. He has published 30 SCI papers, has an H-Index of 26 & i10 indexing of 36. He has published 70+ research articles (including Scopus- and SCI-indexed publications), 2 research patents, and 1 authored book, and has served as an editor/reviewer for various SCI/Scopus journals. His research areas are IoT, Metaheuristic Optimization, and Data Mining. Connect with me at [email protected] (+91-81268-81868).
Employment
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University of Petroleum and Energy Studies Associate Professor2012 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (48)
- Fire Detection in Urban Areas Using Multimodal Data and Federated Learning Save
- Risk of Infection and Colonization of Symptomatic Urinary Tract Bacteriuria in Type-1 and Type-2 Diabetic Patients Save
- Securing Vehicular Internet of Things (V-IoT) Communication in Smart VANET Infrastructure using Multi-layered Communication Framework and Novel Threat Detection Algorithm Save
- Smart Job Scheduling Model for Cloud Computing Network Application Save
- EDSSR: a secure and power-aware opportunistic routing scheme for WSNs Save
- Comparative analysis of maximum fluid film pressure for journal bearing compensated with different flow control devices Save
- Novel Optimized Feature Selection Using Metaheuristics Applied to Physical Benchmark Datasets Save
- Hybrid Dynamic Optimization for Multilevel Security System in Disseminating Confidential Information Save
- Deep-Drilling of SS-316L on Orbital EDM with Copper Electrode Tube Save
- An improved deep reinforcement learning routing technique for collision-free VANET Save