Computer Science, Computer Science Applications, Information Systems, Software
4
Scopus Publications
4
Scholar Citations
1
Scholar h-index
Scopus Publications
The Impact of AI on Employability and Evolving Job Roles of IT Professionals Divyesh P. Gohel, Janak H. Maru 2026 Innovations in Machine Engineering and Digital Conference Imed 2026, 2026 Artificial Intelligence (AI) is rapidly transforming the nature of work, the demand for skills, and the professional roles of Information Technology (IT) practitioners. This review paper examines the multifaceted impact of AI on employability and the evolving job roles of IT professionals by synthesizing recent empirical studies, conference findings, and industry reports. The review highlights how automation, generative AI, and intelligent systems are reshaping task structures, leading to both job displacement risks and the creation of new AI-driven roles. It further explores the demand for hybrid skill sets that integrate technical expertise with higher-order cognitive, ethical, and socio-emotional competencies. The paper also discusses organizational implications, including changes in project management practices, innovation performance, and AI adoption challenges in education and industry. Ethical concerns such as transparency, explain-ability, psychological effects, and responsible AI governance are analyzed as critical factors influencing employability outcomes. A conceptual framework is proposed linking AI adoption to employability and role transformation, mediated by skill adaptation, continuous learning, and organizational readiness. Overall, the review finds that AI is not simply replacing jobs but is redefining professional identity in IT, emphasizing reskilling, adaptability, and lifelong learning as key determinants of future employability. The paper concludes with directions for educators, policymakers, and industry leaders to design AI-inclusive curricula, workforce development strategies, and policies that support sustainable human–AI collaboration.
Implantable AI Pacemakers Using On-Device Learning to Prevent Atrial Fibrillation Before Onset Prakash Gujarati, Divyesh Gohel 2026 Innovations in Machine Engineering and Digital Conference Imed 2026, 2026 This paper gives the design and system-level analysis of an implantable artificial intelligence-enabled pacemaker that uses on-device learning to identify and prevent atrial fibrillation before it can impact the patient clinically. The proposed pacemaker transforms lightweight embedded learning models using intracardiac electrograms in real-time to help offer control and decisions to ultra-low-power implantable hardware. Individual adaptation of the patient makes it possible to detect early instances of atrial electrophysiological instability, and preventative pacing with a closed-loop control approach. System analysis indicates that the proposed solution would provide an average lead time of 24 minutes prior to onset with an average prediction accuracy of 87 percent of atrial fibrillation and energy usage that is within clinically acceptable ranges. These findings suggest that anticipatory, learning-pacing can be practiced within the implantable limits and can substantially decrease the atrial fibrillation burden.
A Deep Learning - Driven Convolutional Neural Network Framework for Automated Detection and Classification of Tomato Leaf Diseases to Enhance Precision Agriculture and Crop Health Monitoring Bhojani Aarati Harilal, Divyesh P. Gohel Iet Conference Proceedings, 2025 Techniques for identifying diseases in tomato leaves involve visual inspection, which is time-consuming, labor-intensive, and prone to human error. This paper suggests a CNN system based on deep learning for disease diagnosis and classification in order to overcome these limitations. Food safety and agricultural productivity are significantly impacted by tomato plants' vulnerability to certain diseases. The suggested method uses CNN architectures and image processing techniques, such as baseline CNN models and transfer learning models like Inception-V3, to reliably forecast a variety of tomato leaf diseases. The data set spans ten distinct disease classes and consists of 18,345 training photos and 3,875 validation images. To improve model performance, preprocessing methods such feature extraction, normalization, and picture augmentation are applied. The field-use monitoring systems will be built using Sphere. Future studies on these crops ought to concentrate on smartphone apps or similar technologies.
Recommender System: Techniques, Comparison & Solutions Divyesh Gohel, Pratik Vanjara 2022 IEEE 7th International Conference for Convergence in Technology I2ct 2022, 2022 There are several benefits of e-commerce websites that include cost effectiveness, convenience, flexibility, fast delivery, increase in income, etc. With these benefits, there is crucial role of e-commerce websites in business and users. However, e-commerce websites produce an overload of data, hence, Recommender Systems (RSs) provides a solution for the data overload problem. The present study, reviews different types of RSs and its pros and cons. Then, it does comparative study of different types of RSs. After the review, it’s concluded that collaborating filtering technique used more than all other ones in e-commerce websites. There are problems with almost all techniques including the collaborative filtering technique too. However there is a novel model proposed that fixes the collaborative filtering technique of ‘cold start’ at its best.
RECENT SCHOLAR PUBLICATIONS
The Impact of AI on Employability and Evolving Job Roles of IT Professionals DP Gohel, JH Maru 2026 Innovations in Machine, Engineering, and Digital Conference (IMED), 1-9 , 2026 2026
Implantable AI Pacemakers Using On-Device Learning to Prevent Atrial Fibrillation Before Onset P Gujarati, D Gohel 2026 Innovations in Machine, Engineering, and Digital Conference (IMED), 1-5 , 2026 2026
A deep learning-driven convolutional neural network framework for automated detection and classification of tomato leaf diseases to enhance precision agriculture and crop … BA Harilal, DP Gohel Parul University International Conference on Engineering and Technology 2025 … , 2025 2025 Citations: 3
Analyzing User-Based and Item-Based Recommender Systems: A Comparative Examination DP Gohel 2024
Recommender system: Techniques, comparison & solutions D Gohel, P Vanjara 2022 IEEE 7th International conference for Convergence in Technology (I2CT), 1-7 , 2022 2022 Citations: 1
A study of recommendation system in E-commerce D Gohel, DRP VANJARA 2022
MOST CITED SCHOLAR PUBLICATIONS
A deep learning-driven convolutional neural network framework for automated detection and classification of tomato leaf diseases to enhance precision agriculture and crop … BA Harilal, DP Gohel Parul University International Conference on Engineering and Technology 2025 … , 2025 2025 Citations: 3
Recommender system: Techniques, comparison & solutions D Gohel, P Vanjara 2022 IEEE 7th International conference for Convergence in Technology (I2CT), 1-7 , 2022 2022 Citations: 1
The Impact of AI on Employability and Evolving Job Roles of IT Professionals DP Gohel, JH Maru 2026 Innovations in Machine, Engineering, and Digital Conference (IMED), 1-9 , 2026 2026
Implantable AI Pacemakers Using On-Device Learning to Prevent Atrial Fibrillation Before Onset P Gujarati, D Gohel 2026 Innovations in Machine, Engineering, and Digital Conference (IMED), 1-5 , 2026 2026
Analyzing User-Based and Item-Based Recommender Systems: A Comparative Examination DP Gohel 2024
A study of recommendation system in E-commerce D Gohel, DRP VANJARA 2022
