Distributed Computing Systems, Concurrent Algorithms, Mobile Computing
Latest Topic of Interest: Applying AI and Machine Learning Techniques for System and Network Security Other Areas of Interest: Software Defined Networking, Cyber Security, Blockchain, Wireless Sensor Networks, Semantic Web, Cloud Computing, Internet of Things, Operating Systems, Data Structures, Programming (Also refer to our recent book “Security and Privacy Issues in Sensor Networks and IoT” (IGI Global), 2019, DOI: 10.4018/978-1-7998-0373-7).
Teaching Interests: Data Structures, Design & Analysis of Algorithms, Competitive & Efficient Programming, Machine Learning, Programming in C C++, Software Design & Development, Software Engineering & Project Development, Operating Systems, Data Bases, Object Oriented Systems, Software Testing.
My Video Lectures on Data Structures & Algorithms available on YouTube Channel: @JitenderKrChhabraProfCseNITKKR
Data Str Playlist: https://www.youtube.com/watch?v=fjLJwypxLFs&list=PL82bhWqRpcuc4OhxBC0qGB8XTfn4ulrLg
Algo Playlist: https://www.youtube.com/watch?v=c8uhnJOrXiI&list=PL82bhWqRpcud1xDmBZE89Oogm1p21N7Yq
Research Interests: Software Engineering, Soft Computing, Software Metrics, Machine Learning & AI in S/w Engg, Clustering and Mining
Experience : 30 years (Teaching alongwith Research )
Intellectual Property Rights: Patents : Total 9 (3 granted + 6 published) Copyrights: Six granted
Publications : Total 166 (SCI/Scopus indexed International Journals: 61, Others and National Journals: 19, Book Chapters & Procedia, LNCS etc: 24, International Conferences: 46, National Conferences: 16)
Reviewer for Journals : IEEE Transactions, ACM Transactions, Elsevier, Springer, Wiley, Taylor & Francis, Inderscience etc.
Research Project: Project entitled “Design and Development of a Novel Approach (non-cryptographic) for Secure Storage on External Media and Lossless Retrieval”, funded by DRDO Govt of India, completed.
Books Published: Total 3 (Coauthor of World-famous Schaum Series Book from McGraw Hill titled “Programming with C” Byron Gottfired, USA & Jitender Kumar Chhabra. 4th Edition; Another book for learning depth of coding: ”Conceptual Programming Tips for Interviews and Competitive Exams”, McGraw Hill)
Ph.Ds Supervised : Completed: 6 (each with 3 or more SCI publications reputed journals); New Admissions: I will accept 1 candidate for PhD who is sincere, hard-working and ready for quality-work
Speech Processing, Machine Learning, Soft Computing, Quality Life Management, Science & Spirituality
General: Database systems, data mining, information retrieval, big data, requirements engineering.
Specific: Data models, schema design, schema management, data integration, dataspace, sentiment analysis, recommender systems, question answering systems.
Information Security, Computer Networks, Internet of Things, Wireless Sensor Networks, Cyber Security, IoT Security, Adhoc Network Security, WSN Security, Key Management and Distribution Other Areas of Interest: Cyber defense and vulnerability, Cloud Security, Mobile Computing, Digital Forsenics
Speech Processing, Pattern Recognition, Image Processing, Natural Language Processing, Soft Computing, Multimedia Security, Machine Learning, Image and Video Encryption
Teaching Interests: Design & Analysis of Algorithms, Data Structures, Database Management System, Operating system.
Research Interests: Cloud/Fog Computing, IoT, Soft Computing, Machine learning, Security etc
Wireless Adhoc & Sensor Networks | Evolutionary Computations in Computer Networks | Machine Learning Techniques in Networking | Flying Adhoc Sensor Networks (FANeTs) | Security issues in Cloud Computing | Security issues in Internet of Things (IoTs) | Soft Computing techniques for IoT Anaytics | Security Issues in Software Defined Networking | Energy Harvesting in IoT | Internet of Robotics of Things | FoG Computing
Digital Signal Processing, Digital Image Processing, Soft-Computing, Machine Learning
Teaching Interest: Database Systems, Data Mining & Data Warehouse, Information Science (Retrieval & Web Search), Human-Computer Interaction (HCI).
Current Research Activities: Exploratory Data Analytics, Human-Information-Interaction, Neural Models for Interactive Information Search, Large Language Models (LLM), Soft Data Analytics & evaluation (Sentiment, Micro-Emotions/Micro-expression), Social Network Science & Applications, ML/DL & AI for real-world Scenarios.
Access ‘E-content’ (recorded lectures of two courses), ‘Information Retrieval & Web Search‘ and‘ Database Systems‘.
> Prospective PhD aspirants may share their brief bio with ‘Research Interest’ for Session 2023-24, on viks@nitkkr.ac.in.
(last updated: 11 Nov’23)
Distributed Computing, Mobile Computing, Wieless Networks, Cognitive Radio Networks
Cyber and Web Security, Mobile Security, Internet of Things, Machine Learning, DDoS Detection, Online Social Networks Analysis,
C, C++, NS2, Data Structure, Unix and Linux Programming, Wireless Ad hoc Network, Mobile Computing, Distributed Computing, and Cognitive Radio networks.
Cloud Computing, Distributed Systems
Machine Learning Image Processing Medical Imaging Algorithms and Data Structure Computational theory
Information Security Cloud Security Privacy Preserving in Data Publishing Computer Networks Network Security
Data Mining, Recommender Systems, and Java Technology
Pattern Recognition and Machine Learning, Biometric, Computer Vision, Deep Learning
Multimedia Analysis, Machine Learning, Deep Learning, Natural Language Processing, Cloud Security
Artificial Intelligence for social good, Knowledge Engineering and Semantic Web, Applications of Machine/Deep Learning in Text Processing
Experience : Worked as an Assistant Professor in the Department of Computer Science & Engineering of NIT Warangal. (From 09-April-2018 to 21-Nov-2022)
Working on nature inspired intelligent algorithms. Applications in machine learning and image processing.
Software Engineering, Natural Language Processing, Applied Machine Learning, Big Data Analytics, Software Security
– Erdos Number: 4 (Kuldeep Kumar – Stanislaw Jarzabek – Tomasz Krawczyk – William T. Trotter – Jr-Paul Erdos).
– PhD Thesis listed in PhD Dissertations in the Area of Software Engineering repository maintained by ACM.
– Recipient of the Early Adopter Award by CDER USA and the Early Career Research Award by DST, Govt of India.
– Involved in the development of tools and techniques in-use by Software Industry.
Data Science with a focus on Biological Data Analysis and Drug discovery, Text Data Mining
Dr. Lov Kumar is currently working as Assistant professor in the Department of Computer Engineering , NIT Kurukshetra . He received his Ph.D. in Computer Science and Engineering from NIT Rourkela, under the supervision of Prof. S. K. Rath. His current research interests are in the area of Mining Software Repositories, Software Analytics, and Social Media Analytics. His thesis is titled “Predicting Software Quality Parameters using Artificial Intelligence Techniques and Source Code Metrics”. He was a Faculty Member (at Thapar University) from Aug 2017 to Dec 2017 and BITS Pilani from Jan 2018 to Jan 2023. He has delivered over 60 invited talks, over 100 international refereed publications in international conferences and journals, and four published book chapter to his credit. He has won several other awards including the Young Scientist Award, Best Researcher Award, and best paper Award. He has a broad range of interests and hobbies. He loves to play cricket, read books, play chess, and solve Sudoku puzzles.
Research Area: Software Engineering, Machine Learning, Mining Software Repositories, Software Analytics, and Social Media Analytics
Teaching Experience
Research Areas: Computer Vision, Machine Learning, Artificial Intelligence, Image Processing, NLP, Surplus Food Distribution, Smart City
Teaching Experience: Assistant Professor, KIIT University, Bhubaneswar, Odisha (January ’22 to Aug ’23)
Publications:
Journals (SCI): 5, International Conferences: 5, Book Chapters: 2
Google Scholar Profile:
Machine Learning, Deep Learning, Image processing and NLP.
Image Processing
Software Engineering, Machine Learning, Artificial Intelligence, Optimization Algorithms.
Machine Learning, Deep Learning, Bioinformatics
Cyber Security, Malware Analysis, Malware Detection, Phishing Detection, IoT, Machine Learning, Deep Learning
Machine Learning, Deep Learning, Internet of Things, Wireless Sensor Networks, Ad-hoc Networks, Cyber-Physical Systems
Publications:
1. V. Agarwal, S. Tapaswi, P. Chanak and N. Kumar, Intelligent Emergency Evacuation System for Industrial Environments Using IoT-Enabled WSNs,” in IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1-12, 2023, Art no. 9514612, doi:10.1109/TIM.2023.3328071.
2. V. Agarwal, S. Tapaswi and P. Chanak, “Intelligent Fault-Tolerance Data Routing Scheme for IoT-Enabled WSNs,” in IEEE Internet of Things Journal, vol. 9, no. 17, pp. 16332-16342, 1 Sept., 2022, doi: 10.1109/JIOT.2022.3151501.
3. A. Jindal, V. Agarwal and P. Chanak, “Emergency Evacuation System for Clogging-Free and Shortest-Safe Path Navigation With IoT-Enabled WSNs,” in IEEE Internet of Things Journal, vol. 9, no. 13, pp. 10424-10433, 1 July, 2022, doi: 10.1109/JIOT.2021.3123189.
4. V. Agarwal, S. Tapaswi and P. Chanak, “Energy-Efficient Mobile Sink-Based Intelligent Data Routing Scheme for Wireless Sensor Networks,” in IEEE Sensors Journal, vol. 22, no. 10, pp. 9881-9891, 15 May, 2022, doi: 10.1109/JSEN.2022.3164944.
5. V. Agarwal, S. Tapaswi, and P. Chanak, “A Survey on Path Planning Techniques for Mobile Sink in IoT-Enabled Wireless Sensor Networks”, Wireless Personal Communication 119, 211–238 (2021). https://doi.org/10.1007/s11277-021-08204-w.
6. Dheeraj Pal, Alok Jain, Aradhana Saxena, Vaibhav Agarwal (2016). Comparing Various Classifier Techniques for Efficient Mining of Data. In: Proceedings of the International Congress on Information and Communication Technology. Advances in Intelligent Systems and Computing, vol 439. Springer, Singapore. https://doi.org/10.1007/978-981-10-0755-2_21.
Social Network Analysis, Natural Language Processing, Graph Mining, Machine Learning
Computer Vision, Image Forensics, Image Processing, Multispectral Imaging, Applied Deep Learning, and Machine Learning
Machine Learning, Active Machine Learning, Deep Learning, Active Deep Learning,