DR KUSH BHUSHANWAR

About

Dr. Kush Bhushanwar is a researcher and academician in the field of Computer Science and Engineering, with research interests centered on Artificial Intelligence, Machine Learning, Data Science, Data Analytics, Data Visualization, and Intelligent Systems. His work focuses on applying computational intelligence and data-driven techniques to solve real-world problems and support informed decision-making.

He has been actively involved in scholarly activities including research publication, manuscript review, curriculum development, and mentoring undergraduate engineering students. His research emphasizes the integration of AI and data science methodologies for practical applications in education, industry, and emerging technologies.

Dr. Bhushanwar regularly contributes to academic and professional communities through conference participation, peer review activities, and collaborative research initiatives. He is committed to advancing knowledge in AI-enabled systems while promoting innovation, ethical technology adoption, and outcome-based engineering education.

Employment

• Symbiosis University of Applied Sciences Sr. Assistant Professor
  2026 - Present
• Parul University Assistant Professor
  2024 - 2026
• Medi-Caps University Assistant Professor
  2022 - 2024
• Acropolis Institute of Technology & Research Assistant Professor
  2021 - 2022
• SAGE University Indore Assistant Professor
  2019 - 2021
• Malwa Institute of Technology Assistant Professor
  2011 - 2019

Education

• SAGE University PhD
  2020 - 2024

Projects & Funding

Projects & funding information is unavailable.

Publications (20)

• Comprehensive Survey of Fundus Image Analysis for Early Detection of Diabetic Retinopathy Using Deep Learning
  Signal Processing, Telecommunication & Embedded Systems: AI and ML Applications: Proceedings of Tenth International Conference on Microelectronics Electromagnetics and Telecommunications (ICMEET), Volume 3. Lecture Notes in Electrical Engineering (1599) 2026 DOI: 10.1007/978-3-032-20318-2_19
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• Enhancing Brain Tumor Detection in MRI Scans Through Advanced Deep Learning Models
  2026 DOI: 10.1007/978-981-96-8639-1_17
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• Advances In Maternal-Fetal Health Research: Genetic Variants, Image Processing Biomarkers, And Their Implications For Pregnancy Outcomes And Paediatric Development
  Genetics and Molecular Research 2026
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• Enhance Learning Capabilities of Students Using Gamification at University Level
  2025 DOI: 10.2991/978-94-6463-716-8_63
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• Soybean leaf pathogens classification using fine-tune vision transform
  IET Conference Proceedings 2025 DOI: 10.1049/ICP.2025.1305
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• Social media analysis for criminal behavior detection using CNN-RNN modelling
  IET Conference Proceedings 2025 DOI: 10.1049/ICP.2025.1313
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• Social Media Analysis for Criminal Behavior Detection: Methods, Application and Challenge
  International Conference on Sentiment Analysis and Deep Learning (ICSADL) 2025 DOI: 10.1109/ICSADL65848.2025.10933426
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• Inverse Cooking: Food Image to Recipe Generation Using Machine Learning
  2025 DOI: 10.1007/978-981-97-9855-1_25
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• Attenuation YOLOv5-based detection of anomalous behavior in ATM
  IET Conference Proceedings 2025 DOI: 10.1049/ICP.2025.1315
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• A Secure Framework for Decentralized Digital Lockers Using Blockchain Technology
  Journal of Computer Science 2025 DOI: 10.3844/JCSSP.2025.2105.2112
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