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 : 31 years (Teaching alongwith Research )

Books Published: Total 3 (Coauthor of World-famous Schaum Series Book from McGraw Hill titled “Programming with C” Byron Gottfried, USA & Jitender Kumar Chhabra. 4th Edition; Another book for learning depth of coding: ”Conceptual Programming Tips for Interviews and Competitive Exams”, McGraw Hill)

Intellectual Property Rights: Patents : Total 10 (6 granted + 4 published) Copyrights: Six granted

Publications : Total 174 (SCI/Scopus indexed International Journals: 68, Others and National Journals: 20, 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.

Ph.Ds Supervised : Completed: 8 (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

Research Project: Total 3: One funded by DRDO Govt of India, completed; 2nd funded by ISRO Govt of India, completed; 3rd funded by ISRO Govt of India, in-progress.

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, satellite communication, 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

‪Priyanka Ahlawat‬ – ‪Google Scholar‬

Experience: 18.5 years (Teaching along with Research)

Publications: SCI/Scopus indexed International Journals: 24, Journals (Non-Scopus): 04, Book Chapters: 12, International Conferences: 54

Externally Sponsored R&D Projects Ongoing: ISRO funded three-year project on “Key management for secure multicast applications in Space Terrestrial Integrated Network” starting from 2022

Ph.Ds Supervised and Under Supervision: 01(submitted) 04(ongoing)

M.Tech Supervised and Under Supervision: 30 (awarded) 01(ongoing)

Others:

Workshops/STCs/Conferences Organized: 06 STCs, 0 3 Conference

Keynote Speaker in Workshops/STCs: 10

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, Advance data structure and algorithms, IoT and Cloud computing

Research Interests: Cloud/Fog Computing, IoT, Soft Computing, Machine learning, Security etc

Google scholar

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), Big Data Analytics.

Current Research Activities: Cross-Domain Recommendation System Design, Neural Models for Interactive Information Search, Human-Information Interaction, Sentiment & Micro-Emotions/Micro-Expressions Analytics & Use Cases, Applications of Generative AI, LLMs, & ML/DL for Real-World Scenarios.

Recent Publications (Best-5 Journal/Conference Publications, out of a total of 82):

– Mehta, S., Kumar, L., Misra, S., Patnaik, K. S., & Singh, V. (2025). Nested Deep Learning with Learned Network Embeddings for Software Defect Prediction. Applied Soft Computing, 113057. (SCI, 7.2)

– Kumar, L., Singh, V., Murthy, L. B., Krishna, A., & Misra, S. (2025). MLAPW: A framework to assess the impact of feature selection and sampling techniques on anti-pattern prediction using WSDL metrics. Journal of Computer Languages, 101322. (SCOPUS, IF 1.7)

– Kumar, L., Singh, V., Patel, S., & Mishra, P. (2024, December). Empowering SW Security: CodeBERT and Machine Learning Approaches to Vulnerability Detection. In Proceedings of the 21st International Conference on Natural Language Processing (ICON) (pp. 399-407).

– Mishra, P., Singh, V., Krishna, A., & Kumar, L. (2024, April). An Empirical Analysis on Leveraging User Reviews with NLP-Enhanced Word Embeddings for App Rating Prediction. In International Conference on Advanced Information Networking and Applications (pp. 234-244). Cham: Springer Nature Switzerland.

– Kumar, L., Singh, V., & Mishra, P. (2024, December). Mocktails of Translation, Ensemble Learning and Embeddings to tackle Hinglish NLP challenges. In Proceedings of the 21st International Conference on Natural Language Processing (ICON) (pp. 593-601).

Awards/Recognitions (total 07): 

Paper titled ‘Embracing NLP-Enhanced Word Embeddings for Contextually Enriched Technical Debt Estimation in Software Code Comments: An Empirical Study’, awarded as Best Paper at 22^nd International Conference on Information Technology (OCIT), held at SRM University, AP, India, India, during 12-14 Dec, 2024, Authors: Ishpreet, Lov Kumar, Vikram Singh, Pratyush Mishra, and Proksh.

Paper titled ‘Advancing Video Summarization using Language-base Attention Transformer’, awarded as Best Paper at International conference on signal processing, computation, electronics, power and telecommunication (IConSCEPT 2024), held at NIT Puduccherry, India, during July -3-05, 2024, Authors: Hitesh Kumar, Vikram Singh and Lov Kumar.

Paper titled, ‘Connecting Word to Motion: unleashing Video Highlights and Moments through Cross Attention Temporal Grounding, awarded as Best Paper at 5^th Doctorial Symposium on Computational Intelligence (DoSCI 2024), held at IET, Lucknow, University of Delhi, and University of Calabara, Itly, during May 10-11, 2023. Authors: Hitesh Kumar and Vikram Singh

Access ‘E-content’ (recorded lectures): ‘Course – Information Retrieval & Web Search (30 videos)’ and ‘Course- Database Systems (30 videos)’.

(Last updated: April 10, 2025) 

Distributed Computing, Mobile Computing, Wieless Networks, Cognitive Radio Networks

Data Mining, Recommender Systems, and Java Technology

Information & Cyber Security, Mobile Security, Internet of Things, Machine Learning & Deep Learning,  DDoS Detection, Online Social Networks Analysis, Blockchain

Machine Learning, Image Processing & Medical Imaging, Algorithms and Data Structure, Soft Computing.

Teaching:

Programming in C, C++, Python, NS2; Unix and Linux Programming, Data Structure, Design and Analysis of Algorithms, Computer Networks, Soft Computing

Research: 

Wireless Networks, Mobile Computing, Distributed Computing, Cognitive Radio networks, Quantum Computing

Intellectual Property Rights:

Patent granted: (01)-Human-Assisting Robot (No- 559781)

Information Security, Cloud Security, Privacy Preserving in Data Publishing, Computer Networks, Network Security

Cloud Computing, Distributed Systems

Pattern Recognition and Machine Learning, Biometric, Computer Vision, Deep Learning

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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 Security, Software Engineering, Natural Language Processing, Applied Machine Learning, Big Data Analytics.

– Erdos Number: 4 (Kuldeep Kumar – Stanislaw Jarzabek – Tomasz Krawczyk – William T. Trotter, Jr – Paul Erdos).
– PhD Work listed in the 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

• Jan 2023-  Till Date:    Assistant Professor Gr-1, National Institute of Technology, Kurukshetra                                     Subjects Taught:  Database Management System, Data Mining
• Jan 2018- Jan 2023:    Assistant Professor, Birla Institute of Technology & Science, Pilani – Hyderabad                       Subjects Taught:  Database Management System, Data Mining, Secure Software Engineering, Database Security, Computer Programming, Machine Learning, Advance Data Mining 
• Aug 2017- Dec 2017: Lecturer, Thapar Institute of Engineering and Technology, Patiala                                              Subjects Taught: Discrete Mathematics, C Lab 

Applications of Artificial Intelligence in Cyber Physical System, Vehicular Communication, Software Defined Networking, Medical Image Watermarking and Analysis.

Research Publications:

Journals:

1. A. Sharma and L.K. Awasthi, “Ob-EID: Obstacle aware event information dissemination for SDN enabled vehicular network”, Computer Networks, Volume 216, 2022, 109257, ISSN 1389-1286, https://doi.org/10.1016/j.comnet.2022.109257.
2. A. Sharma and L.K. Awasthi, “Pr-CAI: Priority based-Context Aware Information scheduling for SDN-based vehicular network”,Computer Networks, Volume 193, 2021, 108097, ISSN 1389-1286, https://doi.org/10.1016/j.comnet.2021.108097.
3. A. Sharma and L.K. Awasthi, “AdPS: Adaptive Priority Scheduling for Data Services in Heterogeneous Vehicular Networks”, Computer Communications, Volume 159, 2020, Pages 71-82, ISSN 0140-3664, https://doi.org/10.1016/j.comcom.2020.05.013.
4. A. Sharma, A.K. Singh, and S.P. Ghrera “Robust and Secure Multiple Watermarking for Medical Images”, Wireless Personal Communication, Volume 92, 1611–1624 (2017). https://doi.org/10.1007/s11277-016-3625-x.
5. V. Rathi, A. Sharma, and A. K. Singh, “Multispectral images reconstruction using median filtering based spectral correlation”, Image and Vision Computing, vol 156, pp. 105462, 2025.

Conferences:

1. A. Sharma and L. K. Awasthi, “A Comparative Survey on Information Dissemination in Heterogeneous Vehicular Communication Networks,” 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC), Jalandhar, India, 2018, pp. 556-560, doi: 10.1109/ICSCCC.2018.8703294.
2. A. Sharma, A. K. Singh, S.P. Ghrera, “Secure Hybrid Robust Watermarking Technique for Medical Images”, 4th International Conference on Eco-friendly Computing and Communication Systems, ICECCS 2015, Volume 70, 2015, Pages 778-784, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2015.10.117.
3. S. Chaudhary, A. Sharma, R. Singh and P. Kumar, “Lexicographic logical multi-hashing for frequent itemset mining,” International Conference on Computing, Communication & Automation, Greater Noida, India, 2015, pp. 563-568, doi: 10.1109/CCAA.2015.7148467.
4. A. Sharma, M. Dave, A. K. Singh and S. P. Ghrera “Encryption Based Medical Image Watermarking against Signal Processing Attacks”, International Conference on Future Computational Technologies (ICFCT 2015) Singapore, March 29-30, 2015, pp. 78-84.

Artificial intelligence, Machine Learning, Deep Learning, Image processing, Human-Computer Interaction, Robotics and Medical Imaging.

No. of patents: 1 Granted, 1 Published.

Project:

Funding Agency: Anusandhan National Research Foundation (ANRF)/Science and Engineering Research Board (SERB),Prime minister early research grant,(Duration: 3 years, Fund: approx. 30 Lakhs excluding institute overhead), Principle Investigator: Dr. Pratishtha Verma )                                                                          

PUBLICATION:
1. Verma, P., Srivastava, R., & Tripathy, S. K. (2025). An Assessment Towards 2D and 3D Human Pose Estimation and its Applications to Activity Recognition: A Review. SN Computer Science, 6(2), 190.
2. Maggu, J., Verma, P., & Singh, R. (2024). Clustering Techniques for Hyperspectral Images Using Joint Analysis Dictionary Learning. SN Computer Science, 5(7), 1-13.
3. Verma, P. (2024, September). Biometric Identification using Periocular Images with ViT-DeepSort and YOLOv7-GAN. In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I) (Vol. 7, pp. 1229-1234). IEEE.
4. Tripathy, S. K., Behera, C. K., Pandey, P. M., Pandey, V., & Verma, P. (2024, April). Spatially Attentive Scale Invariant Feature Modelling for Alzheimer’s Disease Detection. In 2024 IEEE 9th International Conference for Convergence in Technology (I2CT) (pp. 1-6). IEEE.
5. Pratishtha Verma and Rajeev Srivastava;Three stage deep network for 3D human pose reconstruction by exploiting spatial and temporal data via its 2D pose; Journal of Visual Communication and Image Representation (2020): 102866. [SCI, Elsvier]
6. Pratishtha Verma, Animesh Sah, and Rajeev Srivastava;Deep learning-based multi-modal approach using RGB and skeleton sequences for human activity recognition; Multimedia Systems (2020): 1-15.[SCI, Springer]
7. Pratishtha Verma, Rajeev Srivastava;Two stage multi view deep network for 3D Human Pose Reconstruction using images and its 2D joint heatmaps through enhanced stacked hourglass approach;, The Visual Computer (2021): 1-14. [SCI, springer]
8. Pratishtha Verma, Rajeev Srivastava;Reconsideration of multi-stage deep network for human pose estimation;, Computer methods in biomechanics and biomedical engineering: Imaging and visualization (2021): [SCI, Taylor and Francis]
9. Pratishtha Verma, Manminder Singh, Birmohan Singh, “Human Detection using Robust Feature Set of HOG and LBP with SVM”, International Journal of Advancements in Computing Technology (2017):1-9.
10. Pratishtha Verma, Amitesh Kumar, “Human Detection using Feature Fusion Set of LBP and HOG“ International Journal on Future Revolution in Computer Science & Communication Engineering (2017): 261-265.
11. Verma, Pratishtha, Vasu Aggrawal, and Jyoti Maggu;FExR. A-DCNN: Facial Emotion Recognition with Attention mechanism using Deep Convolution Neural Network; In Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing, pp. 196-203. 2022.
12. Presented a paper titled “Detect and Estimate: Simple and Efficient baseline for Human Pose Estimation” in International Conference on “Artificial Intelligence and Speech Technology (AIST 2019) organized by Indira Gandhi Technical University for Women (IGDTUW), Delhi held on November 14-15, 2019.
13. J. Maggu, J. K. Saini and P. Verma, "FILM.LrTL: FusIng MuLtiFocus IMages using Low-rank Transform Learning; 2022 1st International Conference on Informatics (ICI), 2022, pp. 60-65, doi: 10.1109/ICI53355.2022.9786913.

Book chapter: 1(Published), 3(accepted to publish)

Verma, P., Tripathi, G., & Singh, R. (2025). Empowering early detection: artificial intelligence as a tool for breast cancer diagnosis. In Revolutionizing Medical Systems using Artificial Intelligence (pp. 121-145). Academic Press.

 Google scholar.

No. of B.Tech Projects: 04 ( Supervised), 04 (on-going)

No. of M.Tech: 04 (On-going) 

No. of Ph.D: Nil

Computer Vision, Image Forensics, Image Processing,  Multispectral Imaging, Applied Deep Learning, and Machine Learning

Publications:

Journal Publications:
1. V. Rathi and P. Goyal, “Multispectral Image Demosaicking based on Novel Spectrally Localized Average Images”, IEEE Signal Processing Letters, vol. 29, pp. 449-453, 2022.

2. M. Gupta, V. Rathi and P. Goyal, “Adaptive and Progressive Multispectral Image Demosaicking”, IEEE Transactions on Computational Imaging, vol. 8, pp. 69-80, 2022.

3. V. Rathi and P. Goyal, “Generic Multispectral Demosaicking Based on Directional Interpolation”, IEEE Access, vol. 10, pp. 64715-64728, 2022.

4. V. Rathi and P. Goyal, “Multidirectional Weighted Interpolation based Generic Demosaicking for Single-Sensor Multispectral Imaging Systems”, Digital Signal Processing, vol. 129, pp. 103646, 2022.

5. V. Rathi and P. Goyal, “Generic Multispectral Demosaicking using Spectral Correlation between Spectral Bands and Pseudo-Panchromatic Image”, Signal Processing: Image Communication, pp. 116893, 2023.

6. V. Rathi, K. Rana, and P. Goyal, “Iterative spectral correlation based multispectral image demosaicking”, Signal, Image and Video Processing, vol. 18, pp. 7873–7886, 2024.

7. V. Rathi, A. Sharma, and A. K. Singh, “Multispectral images reconstruction using median filtering based spectral correlation”, Image and Vision Computing, vol 156, pp. 105462, 2025.

Conferecne Publications:

1. V. Rathi and P. Goyal, “Convolution Filter based Efficient Multispectral Image Demosaicking for Compact MSFAs”, IAPR endorsed 16th Intl. Conference VISAPP 2021, Austria. (Received Best Industrial Paper Award) [Core B]

2. V. Rathi, M. Gupta, P. Goyal, “A New Progressive Approach based on Spectral Difference for Single-Sensor Multispectral Imaging System”, IAPR endorsed 16th Intl. Conference VISAPP 2021, Austria. [Core B]

3. V. Rathi and P. Goyal, “Generic Multispectral Image Demosaicking Algorithm and New Performance Evaluation Metric”, 6th IAPR International Conference on Computer Vision & Image Processing (CVIP), 2022, IIT Ropar.

4. K. Rana, V. Rathi, and P. Goyal. “An Effective CNN-Based Method for Camera Model Identification in Privacy Preserving Settings.” 2023 IEEE International Conference on Image Processing Challenges and Workshops (ICIPCW), 2023, Malaysia. [Core B]

Google Scholar: Google Scholar Profile

M.Tech./Ph.D. Thesis Supervised:

M.Tech. Thesis Supervised: 2 (Ongoing)
PhD Thesis Supervised: 1 (Ongoing as a Co-supervisor)

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): 4, International Conferences: 6, Book Chapters: 2

Google Scholar Profile:

1. Sanyal, B., Mohapatra, R. and Dash, R., 2023. Indian TSR for partial occlusion using GDNN. Multimedia Tools and Applications, pp.1-16.
2.  Sanyal, B., Kumar Mohapatra, R. and Dash, R., 2022. Traffic sign recognition on Indian database using wavelet descriptors and convolutional neural network ensemble. Concurrency and Computation: Practice and Experience, 34(10), p.e6827.
3.  Sanyal, B., Mohapatra, R.K. and Dash, R., 2021. Real-time embedded TSR using MDEffNet: An efficient compact DNN on varied multi-resolution images across multiple databases. International Journal of Wavelets, Multiresolution and Information Processing, 19(03), p.2050082.
4.  Sanyal, S., Kumar Singh, V., Xhafa, F., Sanyal, B. and Mukhopadhyay, S., 2021. A game theoretic framework for surplus food distribution in smart cities and beyond. Applied Sciences, 11(11), p.5058.
5.  Sanyal, S., Mukhopadhyay, S., Xhafa, F., Singh, V.K. and Sanyal, B., 2022, August. An incentive framework for surplus food distribution in the context of smart cities. In International Conference on Network-Based Information Systems (pp. 35-47). Cham: Springer International Publishing.

Social Network Analysis, Natural Language Processing, Graph Mining, Machine Learning

Publications:

1. Pattanayak, Himansu Sekhar, Bhawna Saxena, and Adwitiya Sinha. “Influence maximization in social networks using community-diversified seed selection.” Journal of Complex Networks12, no. 1 (2024): cnae008.  https://doi.org/10.1093/comnet/cnae008
2.  Pattanayak, Himansu Sekhar, Harsh K. Verma, and Amrit Lal Sangal. “Lengthening of average path length in social networks due to the effect of community structure.” Journal of King Saud University-Computer and Information Sciences34, no. 10 (2022): 8401-8421. https://doi.org/10.1016/j.jksuci.2020.10.014
3. Pattanayak, Himansu Sekhar, Harsh K. Verma, and Amrit Lal Sangal. “Gravitational community detection by predicting diameter.” Discrete Mathematics, Algorithms and Applications14, no. 04 (2022): 2150145. https://doi.org/10.1142/S1793830921501457
4. Pattanayak, Himansu Sekhar, Amrit Lal Sangal, and Harsh K. Verma. “Community detection in social networks based on fire propagation.” Swarm and evolutionary computation44 (2019): 31-48. https://doi.org/10.1016/j.swevo.2018.11.006
5. Pattanayak, Himansu Sekhar, H. S. Bindra, and A. L. Sangal. “Gray zone effect in MANETs on proactive and reactive routing protocols.”  J. Comput. Sci. Inf. Technol2, no. 4 (2011): 1559-1563.
6. Pattanayak, Himansu Sekhar, Bhawna Saxena, and Adwitiya Sinha. “Community Detection in Weighted Time-Variant Social Network.” In Proceedings of the 2023 Fifteenth International Conference on Contemporary Computing, pp. 660-665. 2023. https://doi.org/10.1145/3607947.360807
7. Pattanayak, Himansu Sekhar, Harsh K. Verma, and A. L. Sangal. “Relationship Between Community Structure and Clustering Coefficient.” In Intelligent Computing and Applications: Proceedings of ICICA 2019, pp. 203-220. Springer Singapore, 2021. https://doi.org/10.1007/978-981-15-5566-4_18
8. Namkha, Stanzin, and Himansu Sekhar Pattanayak. “Encrypted Image based Reversible Data hiding using Invertible Image Conversion.” In 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC), pp. 128-133. IEEE, 2018. 10.1109/ICSCCC.2018.8703352
9. Pattanayak, Himansu Sekhar, Harsh K. Verma, and A. L. Sangal. “Community detection metrics and algorithms in social networks.” In 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC), pp. 483-489. IEEE, 2018. 10.1109/ICSCCC.2018.8703215
10. Gupta, Prateek, Himansu Sekhar Pattanayak, Lalit Kumar Awasthi, and Vachik S. Dave. “Bio-inspired multilevel ichb-heed clustering protocol for heterogeneous WSNs.” In Recent Trends and Best Practices in Industry 4.0, pp. 225-246. River Publishers, 2023. https://doi.org/10.1201/9781003441717

Btech Major Project Supervised: 2 (Completed)

MTech Thesis Supervised: 1 Ongoing

PhD Thesis Supervised: Nil

Cyber Security, Malware Analysis, Malware Detection, Phishing Detection, IoT, Applications of Machine and Deep Learning

Wireless Sensor Networks, Ad-hoc Networks, Internet of Things, IoT Security, Machine Learning, Deep Learning, Cyber-Physical Systems.

Machine Learning, Deep Learning, Bioinformatics, Blockchain, Software Engineering and Image Processing.

Research Interest:

Software Engineering, Machine Learning, Artificial Intelligence, Optimization Algorithms.

Publications:

Journal Publications:

1. Geetika, Navdeep Kaur, and Amandeep Kaur. “An optimized hybrid deep learning model for code clone detection.” International Journal of Information Technology, pp. 1-7, springer, 2025.

2. Mehta, Ashu, Amandeep Kaur, and Navdeep Kaur. “Optimizing Software Fault Prediction using Voting Ensembles in Class Imbalance Scenarios.” International Journal of Performability Engineering 20.11 (2024).

3. Maini, Ritika, Navdeep Kaur, and Amandeep Kaur. “HSHEP: An Optimization-Based Code Smell Refactoring Sequencing Technique.” Journal of Computational and Cognitive Engineering, pp.616-625, Springer,2024.

4. Amandeep Kaur, Sushma Jain, Shivani Goel & Gaurav Dhiman. “A review on machine-learning based code smell detection techniques in object-oriented software system (s).” Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 14.3, 290-303, 2021, Bentham Science.

5. Amandeep Kaur, “A Systematic Literature Review on Empirical Analysis of the Relationship Between Code Smells and Software Quality Attributes”. Archives of Computational Methods in Engineering, PP 1-30, Springer, 2019.

6. Amandeep Kaur, Sushma Jain, and Shivani Goel. “SP-J48: A Novel Optimization and Machine-Learning based Approach for Solving Complex Problems: Special Application in Software Engineering for Detecting Code Smells”, Neural Computing and Applications, Springer, 2019.

7. Amandeep Kaur, Sushma Jain, and Shivani Goel. “Sandpiper Optimization Algorithm: A Novel Approach for Solving Real-life Engineering Problems”, Applied Intelligence, Springer, 2019.

8. Gaurav Dhiman and Amandeep Kaur. “STOA: A Bio-inspired based Optimization Algorithm for Industrial Engineering Problems”, Engineering Applications of Artificial Intelligence, Elsevier, 2019.

Conference Publications:

1. Maini, Ritika, and Amandeep Kaur, “A Hybrid Approach for Detecting Software Refactoring Sequencing.”     International Conference on Deep Learning, Artificial  Intelligence and Robotics. Cham: Springer Nature Switzerland, 2023.

2. Amandeep Kaur, Sushma Jain, and Shivani Goel. “A support vector machine-based approach for code smell detection.” 2017 international conference on machine  learning and data science (MLDS). IEEE, 2017.

Reviewer for Journals : IEEE, Elsevier, Springer, Wiley, Taylor & Francis

B.Tech Major Project Supervised: 04 (Completed), 03(ongoing)

M.Tech Thesis Supervised: 04(ongoing)

Machine Learning, Active Machine Learning, Deep Learning, Active Deep Learning

PUBLICATIONS (SCI/E-Indexed Journals)
• P Kumar, A Gupta, A. Active instance selection via parametric equation and instance overlap aware scheme.
Applied Intelligence, 52, 994–1012,2022.
• P Kumar, A Gupta, Overlap Aware Active Learning Query Strategies for Pool Based Scenario, IETE Technical Review, 38, 347-356, 2021.
• P Kumar, A Gupta, Active Learning Query Strategies for Classification, Regression, and Clustering: A
Survey. Journal of Computer Science and Technology, 35, 913–945, 2020.
• M Rani, SB Dhok, RB Deshmukh, P Kumar, Compressed Signal Classification Using Informed Instance
Selection, IETE Technical Review, 38, 206-220, 2021.
• M Rani, SB Dhok, RB Deshmukh, P Kumar, Overlap Aware Compressed Signal Classification, IEEE Access,
IEEE Access, 8, 52950-52967, 2020.

M.Tech

1. Deepak Negi (Ongoing) – Enhancing Network Intrusion Detection using Active Learning
2. Shubhendu Sharma (Ongoing) – A Density-Based Active Learning Framework Leveraging Self-Supervised Features
3. Chandresh Kumar (Ongoing)
4. Mahendr Kumar  (Ongoing)

Image Processing