Doctorate Surendra Solanki: Assistant Professor at Manipal University jaipur, Jaipur, Rajasthan, India

Dr. Surendra Solanki is a passionate academician and data science researcher with extensive experience in artificial intelligence, machine learning, and wireless communication systems. His academic journey is marked by a Ph.D. in Computer Science and Engineering from NIT Bhopal, where his research focused on deep learning-based spectrum sensing for cognitive radio networks. He has hands-on expertise in deep learning frameworks like TensorFlow and PyTorch, along with proficiency in Python, R, and MATLAB. With a multidisciplinary outlook, he actively explores large language models, federated learning, blockchain integration in AI systems, and generative models for vision and NLP tasks. Dr. Solanki combines teaching, research, and practical implementation to address complex real-world problems and empower future technologists.

Online Profiles

Scopus Profile

• 108 citations from 93 documents, and 15 scanned items

• An h-index of 4

Education

Dr. Solanki earned his Ph.D. in Computer Science and Engineering from the prestigious Maulana Azad National Institute of Technology (MANIT), Bhopal, where he conducted deep learning-based research on spectrum sensing techniques in cognitive radio systems from 2018 to 2024. He completed his M.Tech. in Computer Science and Engineering from the same institution in 2017 with a CGPA of 7.90; his thesis involved secure data hiding using image steganography. He holds a B.E. degree in Information Technology from the Institute of Engineering and Technology, Devi Ahilya Vishwavidyalaya (DAVV), Indore, graduating in 2012 with 69% marks. His strong academic foundation has enabled him to bridge theory with emerging technologies effectively.

Research Focus

Dr. Solanki’s research interests lie at the intersection of deep learning, wireless networks, and privacy-preserving artificial intelligence. His doctoral research contributed to improved performance in cognitive radio networks through the use of CNNs, RNNs, and hybrid DL architectures. More recently, he has worked extensively with large language models such as BERT, GPT, LLaMA, and Falcon for natural language processing, medical diagnostics, and multi-modal AI systems. His ongoing research explores explainable AI using Grad-CAM and LIME, federated learning for secure health data analytics, AI-driven malware detection, and generative AI for synthetic data creation and model interpretability.

Experience

Dr. Solanki is currently employed as an Assistant Professor in the Department of Artificial Intelligence and Machine Learning at Manipal University Jaipur, where he teaches undergraduate and postgraduate courses, supervises student research, and develops AI-focused curriculum (2023–Present). Previously, he served as a Senior Faculty in IT at SAGE University Indore (through iNurture Education Solutions) from 2022 to 2023, where he taught advanced machine learning and deep learning subjects. Earlier in his career, he worked as an Assistant Manager in eGovernance for the Government of Madhya Pradesh (2014–2015), contributing to digital infrastructure development. His roles have balanced academic instruction, administrative leadership, and applied research.

Research Timeline

Between 2018 and 2024, Dr. Solanki conducted his doctoral research at MANIT Bhopal on deep learning architectures for cognitive radio, resulting in significant publications in IEEE Access and Springer. In 2020, he expanded into blockchain-integrated AI and device authentication systems for smart grids, leading to co-authored IEEE conference papers. From 2021 onward, his research embraced interdisciplinary domains like federated learning in healthcare, Android malware detection using graph neural networks, and self-supervised models for chest X-ray diagnosis. The timeline from 2023 to 2025 shows his contributions in LLM applications, multimodal AI, and knowledge distillation techniques for resource-efficient models in healthcare and audio processing.

Awards & Honors

Dr. Solanki has earned several accolades throughout his academic and professional career. He has authored more than 18 papers in high-impact journals indexed in SCI and Scopus, including Q1 journals such as IEEE Access and Scientific Reports. His innovations have led to the successful filing and publication of 6 patents in AI, Blockchain, and IoT domains. He has received multiple invitations to review for reputed journals and serve as a speaker at IEEE international conferences. His contributions in federated learning, modulation recognition, and AI for healthcare have been appreciated by both academic and industry collaborators, marking him as a notable emerging researcher in applied AI.

Top-Noted Publication

One of Dr. Solanki’s top-recognized publications is titled “A deep ensemble learning approach for squamous cell classification in cervical cancer”, published in Scientific Reports (Nature Portfolio, Q1 Journal) in 2025. This paper proposes a robust ensemble model leveraging deep CNNs and transformers to enhance the accuracy of cervical cancer cell classification, showcasing significant improvements over traditional ML approaches. The work stands out for its clinical relevance, explainability, and technical depth, contributing to the field of AI in medical diagnostics. The publication has attracted significant citations and collaborative interest from researchers working in computational pathology. [DOI: https://doi.org/10.1038/s41598-025-91786-3]