Prof. Dr. Vivek Kumar Sehgal Professor and Head, Fellow IEI, SM-IEEE, SM-ACM ( 91)1792-239251 firstname.lastname@example.org, email@example.com, firstname.lastname@example.org For More Information Click here
Vivek Kumar Sehgal (SM’18) received the B.Tech. degree in Instrumentation Engineering from SantLongowal Institute of Engineering and Technology (Deemed University), in 2000, M.Tech. degree in Process Control Engineering from NetajiSubhash Institute of Technology (Delhi University), in 2002, and the Ph.D. degree in Computer Science and Engineering from Uttrakhand Technical University, Dehradun, in 2007-2010. He is currently Professor with the Department of Information Technology, Jaypee University of Information Technology, Solan, H.P-India. He is member of various technical Societies including IEEE, IEEE Computer Society, Member of IEEE Exe. Com. Delhi Section, Computer Society of India, ACM, SIAM, and IAENG. His areas of interest include embedded processor architecture, hardware software co-design, NoC, Smart MEMS and soft computing for chip design. Dr.Vivek Kumar Sehgal is a member of the technical program committees for several technical conferences, and editorial member of IEEE Access and other reputed journals
Ph.D. Students Supervised:
Ruchi Verma (2017) : Modeling for Crisis Management Occurred during Computer Mediated Communications
Dinesh Kumar (2019) : On Performance of Modified Torus Interconnection Networks
Astha Modgil (2019) : Finding Energy Sustainable Techniques for Computer Memory
Amit Chaurasia (2020) : Application Traffic Modeling and Optimization for NoC Communication
Abhilasha Rangra (2021): Social Internet of Things their Trustworthiness Node Rank and Embeddings Management
Kapil Sharma (2022): Improved and Efficient Optical Networks On Chip Architectures and Designs
Harsuminder Kaur Gill (2022) : Context Aware Recommender Systems using Deep Neural Network
Ph.D. Students Supervising:
Mr. Surjeet Singh : Image Forgery Detection Model using CNN Architecture with SVM Classifier
Ms. Payal Thakur : Neuromorphic Cyber Physical Systems Design
Mr. Arush Kaushal : Intelligent Disaster Management System
M.Tech Students Supervised:
Anubhav Patric : Power optimization in Manycore Processors
Suchi Johari : Comparative Studies of Topologies in 3D NoC
Arvind Kumar : Mapping Algorithms for Networks on Chip
Ravi Shankar Jha : Data Synchronization in M2M Communication Through Cloud
Mukesh Kumar Tripathi : Establishing trust in cloud computing security with the help of inter-clouds
Keshav Kaundle : Network Architecture and System Designing in IoT
Mukesh Sharma : Security and Privacy Mechanism in IoT
Shrishti Kak : Heartbeat Monitoring Using Zigbee Network
Kapil Sharma : Enery Efficiency in Wireless Sensor Networks
Piyush Chauhan : Enery Conservation Using Dinamic Voltage Frequency Scalling
Arush Kaushal : Face mask detection using Machine Learning
M.Tech. Students Supervising:
Open Project Titles:
1. Implementing Model predictive Control reinforcement learning Tasks in Cyber-Physical Systems
The reinforcement learning-based model predictive control can improve the control performance effectively. And the numerical simulations are given to demonstrate the effectiveness of the proposed approach.
2. Smart Grids: A Cyber-Physical Systems Perspective
Smart grids are electric networks that employ advanced monitoring, control, and communication technologies to deliver reliable and secure energy supply, enhance operation efficiency for generators and distributors, and provide flexible choices for prosumers. Smart grids are a combination of complex physical network systems and cyber systems that face many technological challenges.
3. Software-defined digital twins mapping on Networks on Chip
A complex computational task of a physical system is digitally replicated in connected IP cores of Networks on Chip to enhance the performance of system. The complete physical process is divided in small modules and each module is mapped on processing tile of Networks on chip.
4. Probabilistic Graph Models with Kalman Estimator
Bayes filters, such as the Kalman and particle filters, have been used in sensor fusion to integrate two sources of information and obtain the best estimate of unknowns. The efficient integration of multiple sensors requires deep knowledge of their error sources. Some sensors, such as Inertial Measurement Unit (IMU), have complicated error sources.
Undergraduate projects supervised:
2016 Intelligent Stick Navigator for blind persons
2016 Green House Monitoring using IoT
2016 SCADA implementation using IoT
2015 Waste management in smart city using IoT.
2015 Car security using IoT protocol.
2015 IoT based remote sensing.
2015 Electromagnetic lock interface through LTE network.
2014 NoC simulator for diffirent topologies
2014 GALS communication in NoC
2012 Bio Metric Password Protected Mail Server Design.
2012 RF ID Based Toll Tax Charging System.
2012 Mobile Gyroscope Controlled Surveillance Robot.
2012 Job portal with mobile alert.
2011 Piezoelectric generator for street light.
2011 GPS based controlled railway crossing.
2007 Compiler design for 64 bit RISC architecture.
2007 Six Channel Data Acquisition System.
2007 JUIT-Image Based Authentication System.
2006 Voice Coded Stepper Motor Control.
2006 D25 LPT Port based Network Controlled System.
2006 Four Channel Embedded SCADA System.
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