Darpan Anand

Prof. (Dr.) Darpan Anand is a Professor in the Computer Science Engineering Department at Chandigarh University, India with more than 17 years of experience in teaching, industry, and research. He is currently a member of the Board of Studies, a Member of the research Degree Committee, Outcome Based Education Coordinator, ABET Accreditation Coordinator, Research Coordinator, and the Coordinator of Projects in the Department of Computer Science, Chandigarh University. He teaches Computer Networks, Operating Systems, Cryptography & Network Security, Machine Learning, Robotics Process Automation, etc. His research interests include Information Security, e-governance, machine learning, Intelligent Information Processing, Evolutionary Algorithms, etc. He has guided several Ph.D. and PG Dissertations. He is an author/co-author of more than 50+research papers (indexed in SCI, ESCI, Scopus, etc.), 1 Textbook, 6 book chapters (IET, Springer, and Elsevier), 4 patents, SWAYAM MOOC courses,

EDUCATION

B.Tech., M.Tech., Ph.D.

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence

Scopus Publications

Multi-Server Authentication and Key Agreement Protocol with Distributed Storage Utility
Darpan Anand, Vineeta Khemchandani, Vishan Gupta, and Lokesh Pawar
Springer Science and Business Media LLC



Unified Dataset Creation and Model Enhancement Through MURA and LERA Integration
Gurpreet Singh, Puneet Kumar, and Darpan Anand
Springer Nature Singapore



The Rise of Artificial Intelligence Agents in Medical Sciences
Vishan Kumar Gupta, Paras Jain, Shivani Agarwal, Anupriya, Avdhesh Gupta, and Darpan Anand
Springer Nature Switzerland



Application of Consensus Algorithms, Risk Control, and Application of Cryptographic Methods in Distributed Ledger-Based Blockchain Risk Control Technologies
F. M. Nazarov, Munish Sabharwal, Darpan Anand, Vishan Kumar Gupta, Vidisha, and Jaishree Meena
Springer Nature Singapore



A novel and efficient statistical and soft-computing intelligence integrated feature selection technique for human chronic diseases prediction
Amit Yadav, Munish Khanna, and Darpan Anand
Springer Science and Business Media LLC



DECODING MUSCULOSKELETAL DISORDERS: AN IN-DEPTH EXPLORATION OF EXISTING AI MODELS FOR ROBUST ABNORMALITY DETECTION AND ANALYSIS
Gurpreet Singh, Puneet Kumar, and Darpan Anand
World Scientific Pub Co Pte Ltd
Musculoskeletal disorders can significantly disrupt the quality of life of an individual. Early diagnosis and management are critical for minimizing the long-term impact of these disorders. The musculoskeletal upper extremities radiographs (MURA) and lower extremity radiographs (LERA) datasets have emerged as a significant resource in the field of musculoskeletal imaging, facilitating the development and evaluation of various AI models for diagnostic and predictive tasks. The systematic review is carried out in this work to scrutinize existing deep learning models, unraveling their capabilities in decoding complex abnormalities within the musculoskeletal system. By intricately analyzing these models, this study contributes valuable insights into their strengths, weaknesses and performance that are pivotal for advancing the field of musculoskeletal health, ultimately facilitating more informed and precise diagnostic practices. The various limitations and gaps identified during this review will undoubtedly prove valuable for researchers in this field, offering insights to increase the efficiency and effectiveness of their models for the classification and detection of abnormalities in the musculoskeletal system. This undertaking is not merely an aggregation of disparate studies but a deliberate effort to contribute to the ongoing discourse within healthcare, fostering a foundation for evidence-based practice and policy development.


Resource Allocation Load Balancing Secure Schemes in Software Defined Networks: An Analytical Review
Lokesh Pawar, Rohit Bajaj, and Darpan Anand
EverScience Publications



The Future of Work: Robotic Process Automation and its Role in Shaping Tomorrow’s Business Landscape
Vivek Bhardwaj, Shveta Yadav, Navjeet Kaur, and Darpan Anand
Springer Science and Business Media LLC



Employee Retention and Attrition Prediction Using Machine Learning. Case Study on ITES Company
Uttam Singh Chaudhary and Darpan Anand
Springer Nature Singapore



Hybrid Deep Learning Model for Classification and Prediction of Abnormalities in Upper and Lower Extremities of Musculoskeletal Radiographs
Gurpreet Singh, Puneet Kumar, and Darpan Anand
Springer Science and Business Media LLC



A Precise Prediction of Cardiovascular Disease Using Machine Learning-Based Ensemble Model
Reema Goyal, Darpan Anand, Loveleena Mukhija, Sonam Juneja, and Shikha Atwal
Springer Nature Singapore



An Efficient Movie Recommendation Model Using Machine Learning-Based Ensemble Model
Reema Goyal, Darpan Anand, Loveleena Mukhija, Sonam Juneja, and Shikha Atwal
Springer Nature Singapore



Intelligent Management of Distribution Mechanisms Based on Machine Learning Algorithms for Optimal Data Storage
F. M. Nazarov, Garima Sharma, Munish Sabharwal, A. E. Rashidov, Darpan Anand, and Vishan Kumar Gupta
Springer Nature Singapore



Automated Classification of Date Fruit Varieties Using Convolutional Neural Networks
Vishnu Kant, Raghavendra Sridhar, Rashi Nimesh Kumar Dhenia, Ishva Jitendrakumar Kanani, Deepak Banerjee, and Darpan Anand
IEEE



Precision-Driven Indian Dance Form Detection Using CNN and KNN Models
Deepak Banerjee, Aadhya Raghavendra, Ashish Kumar Singh, Jhulan Kumar, Premlata Chopra, Darpan Anand, and Manish Kumar Singla
IEEE



Review on Deep Learning-Based Classification Techniques for Cocoa Quality Testing
Richard Essah, Darpan Anand, and Abhishek Kumar
Springer Nature Singapore



Deep Learning Driven Object Detection and Classification for Autonomous Vehicles in Diverse Traffic and Weather Conditions
Jayant Singh Jhala, Chandani Joshi, and Darpan Anand
IEEE
The rapid development of self-driving vehicles necessitates integrating a sophisticated sensing system to address various obstacles posed by road traffic efficiently. While several datasets support object detection in autonomous vehicles, evaluating their suitability for different weather conditions globally is crucial. In this study, we present deep learning models trained on a novel dataset derived from YouTube videos recorded from Indian car’s dashcams. These videos capture a wide range of conditions, including rain, fog, daytime, hazy and night-time driving scenarios prevalent in India. The dataset comprises a total of 1450 annotated images depicting vehicles and other road assets across six different classes. In this work, performance analysis of the YOLOv8 models trained using an existing dataset was compared with the model trained on an expanded version using the proposed weather-specific dataset. The results demonstrate improved accuracy metrics of 91.3%, 84.5%, and 91.2% for Precision, Recall, and mean Average Precision (mAP) upon integrating the proposed dataset. The model trained on this diverse dataset exhibits heightened robustness, proving highly beneficial for autonomous and conventional vehicle operations in India’s dynamic traffic environments. This research contributes to advancing object detection capabilities crucial for autonomous driving technologies in real-world settings.


A Credit Risk Assessment System for Financial Institutions Utilizing Deep Learning
Vishan Kumar Gupta, Paras Jain, Darpan Anand, Gamini Dhiman, Sarvesh Vishwakarma, and Anurag Aeron
IEEE
According to the banking supervision and regulation of the worldwide, credit risk approximation of a bank/financial institute is not only confined within a product line or value chain anymore. Today’s banking regulation is putting pressure on the banks to deliver the risk measure values by regarding the risk considerations more broadly than just product and trading desk level together with the changes in the market environment and customers’ commitments. Hence, it is deprived of fixed parameters and wholly relies on different parameters and huge data documents. Given very fast progress in the field of data availability, generation, storage, and data processing, machine learning now occupies a strategic position in all areas of the banking business and technologies. The usage of machine learning is extremely appreciable in the construction of credit risk modelling and loss estimations. Risk practitioners are inclining their focus toward applying the advantage of deep learning for the nonlinear relationships of substantive variables and default risk.


A Hybrid Approach for Mathematical Representation of Parallel Design
Nilesh N. Maltare, Safvan Vahora, Surendra Kumar Shukla, Ghanshyam Raghuwanshi, Sarvesh Vishwakarma, Darpan Anand, Vishan Kumar Gupta, and Jaishree Meena
IEEE
The best software development approaches are encapsulated in design patterns. Parallel design patterns are the patterns used in the development of parallel software. The proposed mathematical representation of design patterns provides better representation and understanding. The hybrid representation of the pattern includes all the key features such as visualization, relationship, class representation, and order specification from the existing languages (i.e., LePUS, ExLePUS, BPSL, and LOTOS) of the design patterns specifically for the parallel design. Furthermore, this proposed parallel design representation incorporates ordering constructs such as sequencing, synchronization, and parallel processing as a unique approach. The proposed pattern representation helps with the structural, behavioral, and collaborative aspects of the parallel design. The mathematical and visual representation of this approach leads to the robust and comprehensive parallel design of the software.


Forecasting students' adaptability in online entrepreneurship education using modified ensemble machine learning model
Amit Malik, Edeh Michael Onyema, Surjeet Dalal, Umesh Kumar Lilhore, Darpan Anand, Ashish Sharma, and Sarita Simaiya
Elsevier BV



To that of artificial intelligence, passing through business intelligence
Ruchi Doshi, Kamal Kant Hiran, Maad M. Mijwil, and Darpan Anand
IGI Global
Business intelligence (BI) is no longer adequate to handle the day-to-day operations of any firm considering the ever-increasing volume of data and the resulting overload. As the amount of data grows, it becomes increasingly difficult to evaluate, making the introduction of a decision-making methodology that can be described as real-time BI, very taxing and cumbersome. Because of this, it is becoming increasingly difficult to implement effective decision-making at the enterprise level that was driven by BI, so that the company may remain robust and resilient to both man-made dangers and natural calamities. With today's sophisticated malware and the growing importance of the Internet of Things (IoT), we require a more sophisticated intelligence system, which we currently refer to as Artificial Intelligence (AI). We have a better chance of surviving a cyber-attack thanks to AI and its two other subsets, Machine Learning (ML) and Deep Learning (DL). These technologies strengthen our organization's day-to-day operations and help us make more reliable decisions as stakeholders.


AI and IoT in Supply Chain Management and Disaster Management
Kaljot Sharma and Darpan Anand
CRC Press



Comparative Analysis of Supervised Learning Algorithms for Valuating Used Car Prices
Jayant Singh Jhala and Darpan Anand
IEEE
The Indian automobile industry had its highest-ever annual domestic passenger vehicle sales last year. A total of 3.793 million or 37.93 lakh units were sold in the country in 2022, which is 23.1 percent higher than the preceding year. Similarly, the used car sale is also be increased day by day. The actual and reasonable rates of used cars are important to sale and purchase so that, buyers and sellers will be get benefited. The disparity in prices due to various characteristics or features consistently making prediction of price a difficult job. In the matter of used car price prediction, it has been equally tough. It is challenging to determine when the advertised price is indeed legitimate. Used car prices are highly affected by features like new car price, engine power (cc), maximum power (bhp). For the sake of predicting used car prices on ground of its characteristics, this research target to generate machine learning models incorporating multiple linear regression, decision tree regression and random forest regression. The Car Dekho data set that is used, initially had 13 attributes and 19974 records. In this Research Field, significant study has been carried out; although, not all of them utilized Scikit-learn. Our Suggested models produced accuracy of 94.10% with random forest regression whereas 92.45% with decision tree regression and 89.85% with multiple linear regression.


Blockchain in Education 4.0: A Review
Harsh Bansal, Divya Gupta, and Darpan Anand
IEEE
As the Fourth Industrial Revolution marks the beginning of an era of digitization, key principles like inter-operability, decentralisation, and virtualisation are significantly impacting a variety of fields, including education. Aiming to combine traditional educational techniques with cutting-edge ICT-enabled tools, including artificial intelligence, automation, and blockchain, this paradigm coined as “Education 4.0” intertwines with “Industry 4.0”. With its intrinsic qualities of decentralisation, immutability, consensus, and transparency, blockchain stands up as an effective solution to problems like governance and credential credibility of the courses in which the student is enrolled can be resolved. This paper has contribution in four folds. This paper makes four significant contributions to literature. It begins by highlighting the goals of Education 4.0 and the relationship between modern teaching methods with cutting-edge technology. It then delves into an analysis of blockchain protocols, spotlighting their alignment with the DeFi protocol stack. The next part divides blockchain projects into four distinct categories, following which reviews diverse blockchain-powered projects in education, evaluating their implementations, advantages, and potential drawbacks.


Empirical Analysis of Existing Procurement and Crop Testing Process for Cocoa Beans in Ghana
Richard Essah, Darpan Anand, and Surender Singh
Springer Nature Singapore

RECENT SCHOLAR PUBLICATIONS

• Energy efficient cyber-physical control of renewable microgrids using edge-AI enabled IoT and secure blockchain coordination
  BS Liya, E Harish Kumar, MM Morshedur Hassan, P Nisha, MG Aush, ...
  Scientific Reports , 2026
  2026
• Smart Grid Innovations: Integrating Renewable Energy Sources for Sustainable Power Systems
  P Pandey, MG Aush, K Chanthirasekaran, P Rodrigues, M Elangovan, ...
  Journal of Electrical Engineering & Technology, 1-17 , 2026
  2026
• Multi-Server Authentication and Key Agreement Protocol with Distributed Storage Utility
  D Anand, V Khemchandani, V Gupta, L Pawar
  Journal of Transformative Technologies and Sustainable Development 10 (1), 2 , 2026
  2026
  Citations: 1
• Soil Microbiome Legacies of Long-Term Pesticide Use and Implications for Plant–Insect Interactions in Agroecosystems
  B Puthillath, C Harish, A Latha, P Sudan, JD Werulkar, D Anand, ...
  Natural & Engineering Sciences 11 (1) , 2026
  2026
• The Rise of Artificial Intelligence Agents
  A Gupta, D Anand
  Data Science and Applications: Proceedings of ICDSA 2025, Volume 4 4, 121 , 2026
  2026
• A novel and efficient statistical and soft-computing intelligence integrated feature selection technique for human chronic diseases prediction
  A Yadav, M Khanna, D Anand
  Multimedia Tools and Applications 84 (33), 41853-41896 , 2025
  2025
  Citations: 11
• DECODING MUSCULOSKELETAL DISORDERS: AN IN-DEPTH EXPLORATION OF EXISTING AI MODELS FOR ROBUST ABNORMALITY DETECTION AND ANALYSIS
  G Singh, P Kumar, D Anand
  Journal of Musculoskeletal Research 28 (03), 2550004 , 2025
  2025
• The Rise of Artificial Intelligence Agents in Medical Sciences
  VK Gupta, P Jain, S Agarwal, Anupriya, A Gupta, D Anand
  International Conference on Data Science and Applications, 121-133 , 2025
  2025
• Securing Medicine Quality: A Blockchainpowered Approach to Pharmaceutical Integrity
  VKK Rejeti, BP Kumar, T Srilatha, V Sushma, V Anvitha, K Sindhu, ...
  2025 IEEE International Conference on Computer, Electronics, Electrical … , 2025
  2025
• Intelligent Management of Distribution Mechanisms Based on Machine Learning Algorithms for Optimal Data Storage
  FM Nazarov, G Sharma, M Sabharwal, AE Rashidov, D Anand, VK Gupta
  International Conference On Innovative Computing And Communication, 507-519 , 2025
  2025
  Citations: 3
• The future of work: Robotic process automation and its role in shaping tomorrow’s business landscape
  V Bhardwaj, S Yadav, N Kaur, D Anand
  SN Computer Science 6 (2), 111 , 2025
  2025
  Citations: 9
• Unified Dataset Creation and Model Enhancement Through MURA and LERA Integration
  G Singh, P Kumar, D Anand
  International Conference on Information Technology and Artificial … , 2025
  2025
• Hybrid deep learning model for classification and prediction of abnormalities in upper and lower extremities of musculoskeletal radiographs
  G Singh, P Kumar, D Anand
  SN Computer Science 6 (1), 32 , 2024
  2024
  Citations: 4
• A Precise Prediction of Cardiovascular Disease Using Machine Learning-Based Ensemble Model
  R Goyal, D Anand, L Mukhija, S Juneja, S Atwal
  International Conference on Micro-Electronics and Telecommunication … , 2024
  2024
  Citations: 1
• An Efficient Movie Recommendation Model Using Machine Learning-Based Ensemble Model
  R Goyal, D Anand, L Mukhija, S Juneja, S Atwal
  International Conference on Micro-Electronics and Telecommunication … , 2024
  2024
• Deep learning driven object detection and classification for autonomous vehicles in diverse traffic and weather conditions
  JS Jhala, C Joshi, D Anand
  2024 1st International Conference on Emerging Technologies for Dependable … , 2024
  2024
  Citations: 6
• Enhancing Financial Risk Management in Cryptocurrency Markets Through Machine Learning Analysis
  GVV Nagaraju, GR Chandra, K Murthy, A Ghosh, SV Lakshmi, D Anand
  Studies in Science of Science| ISSN: 1003-2053 42 (10), 56-62 , 2024
  2024
• Smart Containers for Leftover Food Tracking for Packed and Unpacked Food
  PVSV Mounika, T Anjani, V Pravallika, SS Sri, G Srujana, ...
  Engineering Proceedings 66 (1), 50 , 2024
  2024
  Citations: 2
• Application of Consensus Algorithms, Risk Control, and Application of Cryptographic Methods in Distributed Ledger-Based Blockchain Risk Control Technologies
  FM Nazarov, M Sabharwal, D Anand, VK Gupta, Vidisha, J Meena
  International Conference on Advances in Data-driven Computing and … , 2024
  2024
• A credit risk assessment system for financial institutions utilizing deep learning
  VK Gupta, P Jain, D Anand, G Dhiman, S Vishwakarma, A Aeron
  2024 1st International Conference on Advanced Computing and Emerging … , 2024
  2024
  Citations: 6

MOST CITED SCHOLAR PUBLICATIONS

• A disaster management framework using Internet of Things‐based interconnected devices
  K Sharma, D Anand, M Sabharwal, PK Tiwari, O Cheikhrouhou, T Frikha
  Mathematical Problems in Engineering 2021 (1), 9916440 , 2021
  2021
  Citations: 209
• Forecasting students' adaptability in online entrepreneurship education using modified ensemble machine learning model
  A Malik, EM Onyema, S Dalal, UK Lilhore, D Anand, A Sharma, S Simaiya
  Array 19, 100303 , 2023
  2023
  Citations: 101
• Identity-based cryptography techniques and applications (a review)
  D Anand, V Khemchandani, RK Sharma
  Computational Intelligence and Communication Networks (CICN), 2013 5th … , 2013
  2013
  Citations: 57
• Cytokine imbalance in systemic lupus erythematosus: a study on northern Indian subjects
  V Arora, J Verma, V Marwah, A Kumar, D Anand, N Das
  Lupus 21 (6), 596-603 , 2012
  2012
  Citations: 56
• Data security and privacy functions in fog computing for healthcare 4.0
  D Anand, V Khemchandani
  Fog Data Analytics for IoT Applications: Next Generation Process Model with … , 2020
  2020
  Citations: 38
• Fog data analytics for Iot applications
  S Tanwar, R Gupta, A Kumari
  Studies in Big Data Book Series (SBD) 76, 3-17 , 2020
  2020
  Citations: 37
• An intelligent cocoa quality testing framework based on deep learning techniques
  R Essah, D Anand, S Singh
  Measurement: Sensors 24, 100466 , 2022
  2022
  Citations: 36
• Evolutionary optimization with deep transfer learning for content based image retrieval in cloud environment
  NHA Rufus, D Anand, RS Rama, A Kumar, AS Vigneshwar
  2022 International Conference on Augmented Intelligence and Sustainable … , 2022
  2022
  Citations: 33
• A deep convolutional extreme machine learning classification method to detect bone cancer from histopathological images
  D Anand, G Arulselvi, GN Balaji
  Journal of Optoelectronics Laser 41 (7), 456-468 , 2022
  2022
  Citations: 31
• A computational intelligence method for effective diagnosis of heart disease using genetic algorithm
  PS Kumar, D Anand, VU Kumar, D Bhattacharyya, TH Kim
  International Journal of Bio-Science and Bio-Technology 8 (2), 363-372 , 2016
  2016
  Citations: 29
• Identity and access management systems
  D Anand, V Khemchandani
  Security and Privacy of Electronic Healthcare Records: Concepts, Paradigms … , 2019
  2019
  Citations: 28
• Study of e-governance in India: a survey
  D Anand, V Khemchandani
  International Journal of Electronic Security and Digital Forensics 11 (2 … , 2019
  2019
  Citations: 26
• Lightweight Technical Implementation of Single Sign‐On Authentication and Key Agreement Mechanism for Multiserver Architecture‐Based Systems
  D Anand, V Khemchandani, M Sabharawal, O Cheikhrouhou, O Ben Fredj
  Security and communication networks 2021 (1), 9940183 , 2021
  2021
  Citations: 21
• Mobile Radio Communications and 5G Networks Proceedings of Fourth MRCN 2023
  NK Marriwala, S Dhingra, D Kumar
  Future , 2018
  2018
  Citations: 21
• Hybrid deep learning approach for automatic detection in musculoskeletal radiographs
  G Singh, D Anand, W Cho, GP Joshi, KC Son
  Biology 11 (5), 665 , 2022
  2022
  Citations: 20
• Unified and integrated authentication and key agreement scheme for e-governance system without verification table
  D Anand, V Khemchandani
  Sādhanā 44 (9), 192 , 2019
  2019
  Citations: 20
• Dynamic id based remote user authentication in multi server environment using smart cards: a review
  S Gaharana, D Anand
  2015 International Conference on Computational Intelligence and … , 2015
  2015
  Citations: 20
• Development of a compliant legged quadruped robot
  MM Gor, PM Pathak, AK Samantaray, K Alam, P Kumar, D Anand, P Vijay, ...
  Sādhanā 43 (7), 102 , 2018
  2018
  Citations: 19
• Leucocyte complement receptor 1 (CR1/CD35) transcript and its correlation with the clinical disease activity in rheumatoid arthritis patients
  D Anand, U Kumar, M Kanjilal, S Kaur, N Das
  Clinical & Experimental Immunology 176 (3), 327-335 , 2014
  2014
  Citations: 19
• Deformable facial fitting using active appearance model for emotion recognition
  LS Videla, MRN Rao, D Anand, HD Vankayalapati, S Razia
  Smart Intelligent Computing and Applications: Proceedings of the Second … , 2018
  2018
  Citations: 18