Himanshi Babbar | Networking | Best Researcher Award

Himanshi Babbar | Networking | Best Researcher Award

Dr . HimanshiBabbar ,Chitkara University Institute of Engineering and Technology , India

Dr. Himanshi Babbar is an accomplished academic with extensive experience in the field of computer science and technology. She currently serves as an Assistant Professor, Research (CURIN) at Chitkara University, where she has been since February 2022. Her prior roles include working as a Full-time Research Scholar at Chitkara University and as an Assistant Professor at the Chandigarh Group of Colleges and Aryans Group of Colleges. Her teaching portfolio spans a range of undergraduate and postgraduate courses, including Computer Networks, Database Management Systems, Web Technologies, and Programming in various languages. Dr. Babbar’s research interests are centered around advanced networking topics such as Software Defined Networking (SDN), Internet of Things (IoT), Intrusion Detection Systems (IDS), and Deep Learning. Her work aims to enhance network efficiency, security, and integration with emerging technologies.

Publication profile

google scholar

Scopus Profile

ORCID

Education

Himanshi Babbar has an extensive and impressive educational background. She completed her Postdoctoral research at Zayed University, a public university in the UAE, from 2021 to 2022. Following this, she earned her PhD from Chitkara University, Punjab, a private university, between 2018 and 2021. Both of these prestigious qualifications were awarded upon completion. Prior to her PhD, Himanshi completed her Master of Computer Applications (MCA) at Chitkara University, Punjab, from 2012 to 2015, achieving a CGPA of 7.91. She also holds a Bachelor of Computer Applications (BCA) from Chitkara Institute of Engineering and Technology, Punjab, under Punjab Technical University, where she graduated with an impressive 83.0% between 2009 and 2012. Her earlier education includes completing Class XII at ICL Public School in Rajpura under the CBSE board in 2009, with a percentage of 72.6%. She also completed her Class X education at the same school in 2007, securing a percentage of 57.8%

Experience

Dr. Himanshi Babbar is currently serving as an Assistant Professor, Research (CURIN) at Chitkara University, Rajpura, Punjab Campus, since February 2022. Before this role, she was a Full-time Research Scholar at the same institution from November 2018 to December 2021. During her tenure as a Research Scholar, she taught several undergraduate courses, including “Computer Networks and Cisco Packet Tracer” at the 1st year level, “Database Management System” at the 2nd year level, and “Introduction to Web Technologies” also at the 2nd year level. Prior to her current position, Dr. Babbar worked as an Assistant Professor at the Chandigarh Group of Colleges, Landran (Mohali) from June 2016 to November 2017. Here, she taught courses such as “Digital Circuit and Logic Design”, “Software Engineering”, “System Analysis and Design (SAD)”, and “Oracle” at the 2nd year undergraduate level. Additionally, she supervised “Minor and Major Projects” at the 3rd year undergraduate level. She is also experienced in teaching “Workshop on Web Development” and “Java” at the 3rd year undergraduate level, as well as “Programming in C” at the 2nd year MBA (IT) level. Earlier in her career, Dr. Babbar held the position of Assistant Professor at the Aryans Group of Colleges, Chandigarh from August 2015 to November 2015. During this period, she taught “Information Technology” at the 1st year postgraduate level, “Digital Circuit and Logic Design” at the 2nd year undergraduate level, and “Programming in Java” at the 3rd year undergraduate level.

 

Research focus

Dr. Himanshi Babbar’s areas of expertise and research interests include Software Defined Networking, Internet of Things, Intrusion Detection Systems, and Deep Learning. These fields reflect her deep engagement with cutting-edge technologies and their applications, showcasing her commitment to advancing knowledge and innovation in these domains

Skills:

Dr. Himanshi Babbar possesses a strong technical skill set, including proficiency in programming languages such as C, C++, and Python. Her software skills include experience with development environments and tools like Eclipse, Turbo C++, Dev C++, Code-Blocks, ORACLE, NetBeans, and Mininet. She is adept at using various operating systems, including Windows 8, Windows 7, Windows XP, and Ubuntu 18.04 LTS. Additionally, Dr. Babbar is skilled in using Overleaf (LATEX) for document preparation, Origin for data analysis, and MS-Office Suite (Word, Excel, PowerPoint) for general office tasks.

Publication top notes

  • Security framework for internet-of-things-based software-defined networks using blockchain
    • Year: 2022
    • Journal: IEEE Internet of Things Journal
    • Authors: S Rani, H Babbar, G Srivastava, TR Gadekallu, G Dhiman
    • πŸ“…πŸ”’πŸŒ
  • An optimized approach of dynamic target nodes in wireless sensor network using bio inspired algorithms for maritime rescue
    • Year: 2022
    • Journal: IEEE Transactions on Intelligent Transportation Systems
    • Authors: S Rani, H Babbar, P Kaur, MD Alshehri, SH Shah
    • πŸ“…πŸš’πŸ”„
  • An efficient and lightweight deep learning model for human activity recognition using smartphones
    • Year: 2021
    • Journal: Sensors
    • Authors: Ankita, S Rani, H Babbar, S Coleman, A Singh, HM Aljahdali
    • πŸ“…πŸ“±πŸ§ 
  • Load balancing algorithm for migrating switches in software-defined vehicular networks
    • Year: 2021
    • Journal: Comput. Mater. Contin
    • Authors: H Babbar, S Rani, M Masud, S Verma, D Anand, N Jhanjhi
    • πŸ“…πŸš—πŸ”„
  • Energy‐Efficient Routing Protocol for Next‐Generation Application in the Internet of Things and Wireless Sensor Networks
    • Year: 2022
    • Journal: Wireless Communications and Mobile Computing
    • Authors: R Dogra, S Rani, H Babbar, D Krah
    • πŸ“…πŸ”‹πŸ“‘
  • Intelligent edge load migration in SDN-IIoT for smart healthcare
    • Year: 2022
    • Journal: IEEE Transactions on Industrial Informatics
    • Authors: H Babbar, S Rani, SA AlQahtani
    • πŸ“…πŸ₯πŸ”„
  • A genetic load balancing algorithm to improve the QoS metrics for software defined networking for multimedia applications
    • Year: 2022
    • Journal: Multimedia Tools and Applications
    • Authors: H Babbar, S Parthiban, G Radhakrishnan, S Rani
    • πŸ“…πŸŽ₯πŸ”„
  • Load balancing algorithm on the immense scale of internet of things in SDN for smart cities
    • Year: 2021
    • Journal: Sustainability
    • Authors: H Babbar, S Rani, D Gupta, HM Aljahdali, A Singh, F Al-Turjman
    • πŸ“…πŸ™οΈπŸ”„
  • Cloud based smart city services for industrial internet of things in software-defined networking
    • Year: 2021
    • Journal: Sustainability
    • Authors: H Babbar, S Rani, A Singh, M Abd-Elnaby, BJ Choi
    • πŸ“…β˜οΈπŸ™οΈ
  • Software-defined networking framework securing internet of things
    • Year: 2020
    • Journal: Integration of WSN and IoT for Smart Cities
    • Authors: H Babbar, S Rani
    • πŸ“…πŸ”’πŸ“‘

Prakhar Consul | Computer Science | Best Researcher Award

Prakhar Consul | Computer Science | Best Researcher Award

Mr Prakhar Consul, Bennett University, India

Prakhar Consul is an Assistant Professor and Ph.D. candidate at Bennett University, specializing in Internet-of-Things, Mobile Edge Computing, and Deep Reinforcement Learning. He holds an M.Tech. in Electronics and Communication from Sharda University and a B.Tech. from Shobhit University. With a robust teaching background in subjects like Microprocessors and Embedded Systems, his research focuses on computational offloading and resource allocation for UAV-assisted Mobile Edge Computing in 5G networks. Prakhar has taught at Dewan V S Institute, Neelkanth Group of Institutions, and I A M R Group of Institutions. πŸŽ“πŸ“‘πŸ€–πŸ“˜

Publication profile

google scholar

Education

Dr. Prakhar Consul is a Ph.D. candidate in Computer Science Engineering at Bennett University, India, expected to complete in Nov. 2024. Their thesis focuses on computational offloading and resource allocation in mobile edge computing using machine learning in 5G networks πŸ“‘. They hold an M.Tech in Electronics and Communication from Sharda University (2015) with a thesis on microstrip patch antennas πŸ“Ά. Dr. Prakhar Consul also has a B.Tech in Electronics and Communication from Shobhit University (2013) and completed their senior secondary education at J.A.S. Inter College 🏫. Their academic journey is marked by excellence and innovation in engineering and technology πŸ’‘.

Experience

Dr. Prakhar Consul served as an Assistant Professor in the Department of Electronics and Communication Engineering at Dewan V S Institute of Engineering and Technology (DVSIET), Meerut, India, from January 2020 to October 2021. Prior to this, they worked at Neelkanth Group of Institutions (NGI), Meerut, from August 2018 to January 2020 in the Department of Electronics and Electrical Engineering. From August 2015 to August 2018, they were part of the Department of Electronics and Communication Engineering at I A M R Group of Institutions, Meerut. Their extensive teaching experience highlights their dedication to education and engineering. πŸ“šπŸ”ŒπŸ‘¨β€πŸ«

Research focus

P. Consul’s research focuses on advancing wireless communication systems, with an emphasis on energy efficiency, security, and optimization in emerging technologies. His work includes developing innovative antenna designs, such as microstrip and U-slotted patch antennas, and enhancing energy-efficient schemes for mobile edge computing (MEC) using federated learning and reinforcement learning. He explores security in UAV-assisted systems, with solutions for secure computation and resource allocation in blockchain-assisted cyber-physical systems. His research also covers dual and triple band gap antennas and resource optimization strategies for digital twin-empowered UAV networks. πŸš€πŸ“‘πŸ”

Publication top notes

Triple band gap coupled microstrip U-slotted patch antenna using L-slot DGS for wireless applications

Federated learning based energy efficient scheme for MEC with NOMA underlaying UAV

Power allocation scheme based on DRL for CF massive MIMO network with UAV

Security reassessing in UAV-assisted cyber-physical systems based on federated learning

Deep reinforcement learning based energy consumption minimization for intelligent reflecting surfaces assisted D2D users underlaying UAV network

FLBCPS: federated learning based secured computation offloading in blockchain-assisted cyber-physical systems

A review of different vulnerabilities of security in a layered network

A hybrid secure resource allocation and trajectory optimization approach for mobile edge computing using federated learning based on WEB 3.0

A Hybrid Task Offloading and Resource Allocation Approach For Digital Twin-Empowered UAV-Assisted MEC Network Using Federated Reinforcement Learning For Future Wireless Network

Federated reinforcement learning based task offloading approach for MEC-assisted WBAN-enabled IoMT