Tejasva Maurya is a dedicated researcher specializing in artificial intelligence, deep learning, and data science. With a strong academic background in computer science and engineering, he has made significant contributions to AI-driven solutions in smart traffic management, healthcare applications, and natural language processing. His work focuses on applying advanced machine learning models to real-world challenges, particularly in image processing, sentiment analysis, and human-computer interaction. Tejasva has published research in reputable journals and book chapters, showcasing his expertise in AI and its interdisciplinary applications. He has also gained valuable industry experience through internships in data science and analytics, working on projects that optimize machine learning models and enhance data-driven decision-making. His technical proficiency includes programming in Python, deep learning frameworks like PyTorch, and working with Hugging Face models for NLP and computer vision tasks. With multiple achievements in AI research, including a Scopus-indexed publication and competition awards, Tejasva continues to push the boundaries of innovation in artificial intelligence. His long-term goal is to contribute groundbreaking research in AI while bridging the gap between theoretical advancements and practical implementations.

Professional Profile

• ORCID Profile

Education

Tejasva Maurya is currently pursuing a Bachelor of Technology in Computer Science and Engineering at Shri Ramswaroop Memorial University, where he has developed a strong foundation in programming, machine learning, and AI-driven applications. His coursework has provided extensive exposure to algorithms, data structures, deep learning, and computer vision techniques. Prior to his undergraduate studies, he completed his Intermediate education under the CBSE Board in 2021, securing an impressive 88.88%, which highlights his academic excellence and analytical abilities. His passion for artificial intelligence and research was evident early on, leading him to explore AI-related projects and specialized training in machine learning. Throughout his education, he has engaged in practical AI applications, contributing to his ability to develop innovative solutions in deep learning, NLP, and computer vision. His university studies have been complemented by self-driven research initiatives and internships, allowing him to apply theoretical knowledge to real-world problems. Tejasva’s continuous learning approach and commitment to AI research position him as an emerging talent in the field of artificial intelligence.

Professional Experience

Tejasva Maurya has gained substantial industry experience through internships and research projects in data science and machine learning. As a Data Scientist Intern at DevTown (June 2023 – December 2023), he worked on developing and optimizing deep learning models using PyTorch for real-world applications, focusing on NLP, image classification, and generative adversarial networks (GANs). He was responsible for designing data pipelines, preprocessing data, and conducting exploratory data analysis, ensuring the models were efficient and accurate. Additionally, Tejasva worked as a Data Analyst Trainee at MedTourEasy (August 2023 – August 2023), where he specialized in data visualization and statistical analysis. His role involved extracting actionable insights from large datasets using Python and Tableau and collaborating with different teams to implement data-driven strategies. His professional experience has strengthened his ability to apply AI techniques to practical problems, enhancing his understanding of machine learning implementation in different sectors. Through these roles, he has built strong analytical skills and technical expertise, preparing him for more advanced research in artificial intelligence and data science.

Research Interests

Tejasva Maurya’s research interests lie in artificial intelligence, deep learning, natural language processing, and computer vision. His primary focus is on developing AI-driven solutions for real-world applications, including smart traffic management, healthcare technology, and human-computer interaction. His work in vehicle classification using deep learning demonstrates his expertise in YOLO-based object detection models and their application in traffic surveillance and smart city planning. Additionally, he is keen on sentiment analysis and speech processing, contributing to AI models that improve text-to-speech (TTS) synthesis and NLP-based insights. His interest in federated learning for agricultural applications highlights his commitment to interdisciplinary research, exploring AI’s role in optimizing farming techniques and market stability. Tejasva is also exploring artificial emotional intelligence for psychological and mental health assessments, aiming to create AI models that assist in mental health diagnosis and emotional analysis. With a strong foundation in machine learning and AI, he aims to bridge the gap between theoretical advancements and practical AI implementations, driving innovation in multiple domains.

Research Skills

Tejasva Maurya possesses advanced research skills in machine learning, deep learning, and AI model development. His technical expertise includes Python programming, with proficiency in PyTorch, scikit-learn, NumPy, and OpenCV for implementing AI-based solutions. He has hands-on experience in computer vision techniques, including real-time object detection, image segmentation, and gesture-based human-computer interaction, leveraging tools like Mediapipe and Haar Cascades. In natural language processing (NLP), he is skilled in text processing, speech-to-text, and fine-tuning transformer models using Hugging Face frameworks. His research methodology includes data preprocessing, model fine-tuning, hyperparameter optimization, and performance evaluation using metrics like mAP and F1-score. He is proficient in working with large-scale datasets and has successfully published research on vehicle classification, federated learning, and AI-based healthcare applications. Additionally, he has experience in GANs and diffusion models, focusing on synthetic media generation and speech dataset augmentation. His ability to integrate AI solutions across different fields demonstrates his versatility as a researcher and innovator.

Awards and Honors

Tejasva Maurya has received multiple accolades for his contributions to AI research and innovation. One of his most notable achievements is publishing a Scopus-indexed journal article, “Real-Time Vehicle Classification Using Deep Learning—Smart Traffic Management,” in Engineering Reports (Wiley), which underscores the real-world impact of his research. He has also co-authored multiple book chapters in prestigious publishers like Nova Science, Wiley, and Bentham Science, covering AI applications in healthcare, federated learning, and artificial emotional intelligence. His research has been recognized for its contribution to intelligent traffic systems, patient-centric healthcare, and AI-powered decision-making. In addition to his research achievements, he secured 1st position in KIMO’s-Edge’ 23 Technology Competition, a testament to his problem-solving skills and technical expertise. His consistent excellence in AI research and project development has positioned him as an emerging leader in the field of artificial intelligence, with a strong track record of achievements.

Conclusion

Tejasva Maurya is a promising researcher in artificial intelligence, with expertise in deep learning, NLP, and computer vision. His strong academic foundation, technical proficiency, and impactful research make him a strong contender for recognition as a leading researcher in AI. With multiple publications, real-world AI applications, and industry experience, he has demonstrated both theoretical knowledge and practical problem-solving abilities. While he has made significant contributions, focusing on publishing in high-impact AI conferences, securing patents, and expanding interdisciplinary collaborations would further enhance his research portfolio. His dedication to bridging AI theory with real-world applications highlights his potential to contribute groundbreaking advancements in artificial intelligence.

Publications Top Notes

1. Title: Real Time Vehicle Classification Using Deep Learning—Smart Traffic Management
   Authors: Maurya, T., Kumar, S., Rai, M., Saxena, A.K., Goel, N., and Gupta, G.
   Publication: Engineering Reports, 7: e70082 (2025)
   DOI: https://doi.org/10.1002/eng2.70082

2. Title: Patient Centric Healthcare
   Authors: Maurya, T., Kumar, S., Rai, M., Saxena, A.K.
   Book: Harnessing the Power of IoT-Enabled Machine Learning in Healthcare Applications
   Editors: Mritunjay Rai, Ravindra Kumar Yadav, Neha Goel, and Maheshkumar H. Kolekar

3. Title: Integrating Artificial Intelligence and Deep Learning in Classification and Taking Care of DFU
   Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K., Pandey, J.K.
   Book: Machine Learning-Based Decision Support Systems for Diabetic Foot Ulcer Care
   Editors: Mritunjay Rai, Jay Kumar Pandey, and Abhishek Kumar Saxena

4. Title: Federated Learning-Based Approach for Crop Recommendation and Market Stability in Agriculture
   Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K.
   Book: Federated Learning for Smart Agriculture and Food Quality Enhancement
   Editors: Padmesh Tripathi, Bhanumati Panda, Shanthi Makka, Reeta Mishra, S. Balamurugan, and Sheng-Lung Peng

5. Title: Artificial Emotional Intelligence for Psychological State and Mental Health Assessment
   Authors: Kumar, S., Maurya, T., Rai, M., Saxena, A.K.
   Book: Artificial Emotional Intelligence: Fundamentals, Challenges and Applications
   Editors: Padmesh Tripathi, Krishna Kumar Paroha, Reeta Mishra, and S. Balamurugan