Dr. Rutuja Sujit Kadam

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NAME : Dr. Rutuja Sujit Kadam
DESIGNATION : Associate Professor
QUALIFICATION :

  • Ph.D (Computer Science and Engineering), Symbiosis International University (NAAC A++ Accredited), 2022.
  • M.Tech (Information Technology), Bharati Vidyapeeth Deemed University College of Engineering, Pune, 2015.
  • B.E (Information Technology), Pune Institute of Computer Technology (PICT), Pune University, 2006.

OVERVIEW OF PROFILE :

Dr. Rutuja Sujit Kadam is an accomplished academician and researcher with a strong scholarly presence across leading international research platforms including Google Scholar, Scopus, Web of Science, ORCID, Vidwan, and ResearchGate. She is currently serving as an Associate Professor in the Department of Computer Engineering at MIT Academy of Engineering, Alandi.

She holds a Ph.D. in Computer Science and Engineering from Symbiosis International University, along with an M.Tech in Information Technology from Bharati Vidyapeeth Deemed University and a B.E. in Information Technology from Pune Institute of Computer Technology (PICT). Her academic background demonstrates a strong integration of theoretical foundations and applied research expertise.

Dr. Kadam has authored numerous peer-reviewed research articles published in reputed international journals and conferences, with publications indexed in Scopus and Web of Science. Her research work is accessible through prominent scholarly databases such as IEEE Xplore, Springer, Elsevier, Taylor & Francis, PeerJ, and other internationally recognized digital libraries. Her publications have garnered citations from the global research community, reflecting the quality and impact of her scholarly contributions.

She actively contributes to the academic ecosystem as a reviewer for reputed international journals and conferences and maintains active research collaborations through platforms such as ORCID and ResearchGate.

Dr. Kadam has participated in and contributed to several international workshops, seminars, symposiums, and conferences, and continues to serve as a researcher and resource person in her areas of specialization. Her academic and research activities reflect a sustained commitment to research excellence, innovation, and ethical scholarship.

FORE FRONT AREA OF RESEARCH : Artificial Intelligence, Machine Learning, Multimodal Data Fusion, Precision Agriculture
EMAIL ID : rutuja.kadam@mitaoe.ac.in
CONTACT NO : 020 – 30253500

EXPERIENCE : Teaching: 15 years



  • Recognized researcher with publications indexed in Scopus and Web of Science, reflecting sustained scholarly impact and international research visibility.
  • Active reviewer for reputed international journals and conferences, contributing to peer review and quality assurance in scholarly publishing.
  • Invited as a resource person for several Faculty Development Programs.
  • Owns a YouTube channel dedicated to Computer Science tutorials, aimed at helping students and researchers understand key concepts and applications.

INTERNATIONAL JOURNALS

  • R. Mota, R. Wankhade, G. R. Shinde, G. Bobhate, and G. Kaur, “Integration of deep learning algorithms for real time vehicle accident detection from surveillance videos,” Bull. Electr. Eng. Inf., vol. 14, no. 5, pp. 3568–3577, 2025.
  • R. Kadam, G. Mane, R. Bhise, G. G. Tejani, and S. J. Mousavirad, “PriBeL: A primary betel leaf dataset from field and controlled environment,” Data in Brief, vol. 61, 2025.
  • P. Kulkarni, N. Sarwe, A. Pingale, G. Shinde, and G. Kaur, “Exploring the efficacy of various CNN architectures in diagnosing oral cancer from squamous cell carcinoma,” MethodsX, vol. 13, 2024.
  • R. Patil and S. Sharma, “Automatic glaucoma detection from fundus images using transfer learning,” Multimedia Tools Appl., vol. 83, no. 32, pp. 78207–78226, 2024.
  • R. R. Patil, S. Narwadkar, P. S. Mehta, K. Kadam, and V. Bidve, “Unveiling precision: Eye cancer detection redefined with particle swarm optimization and genetic algorithms,” IAES Int. J. Artif. Intell., vol. 14, no. 2, pp. 1087–1095, 2024.
  • G. Kaur, P. Agrawal, L. Pinjarkar, P. Parkhi, and B. Hambarde, “Predictive modeling of Bitcoin prices using machine learning techniques,” Int. J. Intell. Syst. Appl. Eng., vol. 12, no. 17s, pp. 578–586, 2024.
  • A. Adake, A. Agrawal, D. Verma, A. Nimbulkar, and S. Gulhane, “Investigation on state of the art paraphrase detection approaches and resources,” Panam. Math. J., vol. 34, no. 2, pp. 236–253, 2024.
  • R. R. Patil, S. Kothari, S. Sharma, S. Shejwal, and M. Karthikeyan, “Cancer XAI: A responsible model for explaining cancer drug prediction models,” Int. J. Intell. Syst. Appl. Eng., vol. 11, no. 4, pp. 472–484, 2023.
  • R. R. Patil, R. Rani, S. Kumar, and S. K. Pippal, “A machine learning model for predicting innovation effort of firms,” Int. J. Electr. Comput. Eng., vol. 13, no. 4, pp. 4633–4639, 2023.
  • R. R. Patil, A. Singh, A. Ganesh, R. Rani, and S. K. Pippal, “Secure voting website using Ethereum and smart contracts,” Appl. Syst. Innov., vol. 6, no. 4, 2023.
  • R. R. Patil, S. Kumar, R. Rani, P. Agrawal, and S. K. Pippal, “A bibliometric and word cloud analysis on the role of the Internet of Things in agricultural plant disease detection,” Appl. Syst. Innov., vol. 6, no. 1, 2023.
  • R. R. Patil, S. Kumar, S. Chiwhane, R. Rani, and S. K. Pippal, “An artificial intelligence based novel rice grade model for severity estimation of rice diseases,” Agriculture Switzerland, vol. 13, no. 1, 2023.
  • R. R. Patil, S. Kumar, and R. Rani, “Comparison of artificial intelligence algorithms in plant disease prediction,” Revue d’Intell. Artif., vol. 36, no. 2, pp. 185–193, 2022.
  • R. R. Patil and S. Kumar, “Priority selection of agro meteorological parameters for integrated plant diseases management through analytical hierarchy process,” Int. J. Electr. Comput. Eng., vol. 12, no. 1, pp. 649–659, 2022.
  • R. R. Patil and S. Kumar, “Rice Transformer: A novel integrated management system for controlling rice diseases,” IEEE Access, vol. 10, pp. 87698–87714, 2022.
  • R. R. Patil and S. Kumar, “Rice Fusion: A multimodality data fusion framework for rice disease diagnosis,” IEEE Access, vol. 10, pp. 5207–5222, 2022.
  • R. R. Patil, G. Kaur, H. Jain, K. Rao, and A. Sharma, “Machine learning approach for phishing website detection: A literature survey,” J. Discrete Math. Sci. Cryptogr., vol. 25, no. 3, pp. 817–827, 2022.
  • R. R. Patil and S. Kumar, “Predicting rice diseases across diverse agro meteorological conditions using an artificial intelligence approach,” PeerJ Comput. Sci., vol. 7, pp. 1–25, 2021.
  • R. R. Patil, S. Kumar, V. Kumawat, N. Krishnan, and S. K. Singh, “A bibliometric analysis of plant disease classification with artificial intelligence using convolutional neural network,” Library Philos. Pract., pp. 1–14, 2021.
  • R. Patil and S. Kumar, “A bibliometric survey on the diagnosis of plant leaf diseases using artificial intelligence,” Library Philos. Pract., pp. 1–25, 2020.
  • R. Patil, A. Jagtap, and R. Joshi, “Integrated management system for sugarcane disease using deep learning techniques — A review,” Int. J. Sci. Technol. Res., vol. 8, no. 11, pp. 1133–1137, 2019.

BOOK CHAPTER

  • R. R. Patil, C. Gandhewar, K. Sawant, J. Chafale, and S. A. Chaurasia, “Addressing educational inequities: A digital approach for underprivileged children,” in Strategies to Support Underrepresented Minority Students, pp. 127–141, 2025.
  • G. Kaur, P. Agrawal, L. Pinjarkar, S. Chaurasia, and S. Patil, “Comparison of machine learning and deep learning algorithms for diabetes prediction using DNA sequences,” in Genomics at the Nexus of AI, Computational Vision, and Machine Learning, pp. 269–284, 2024.

INTERNATIONAL CONFERENCES

  • R. Meshram, S. Krishna, O. Kulkarni, R. R. Patil, G. Kaur, and S. Maheshwari, “NPC behavior in games using Unity ML Agents: A Reinforcement Learning Approach,” in 2025 International Conference on Automation and Computation (AUTOCOM), Dehradun, India, 2025, pp. 1519–1523.
  • R. Kadam, K. Kamble, P. Bhadarge, S. Bhakte, and L. Pinjarkar, “Movie recommendation system using hybrid based method,” in Proceedings of the 2025 International Conference on Automation and Computation (Autocom 2025), pp. 119–126, 2025.
  • R. R. Patil, A. Sawant, A. Gamane, S. Sonawane, and G. Kaur, “Dark patterns detection on e-commerce websites,” in Proceedings of the 2025 International Conference on Automation and Computation (Autocom 2025), pp. 1302–1309, 2025.
  • R. R. Patil, M. Mahajan, S. Bhat, M. Agrawal, and G. Kaur, “Image captioning — A comprehensive encoder-decoder approach on Flickr8K,” in Proceedings of the 2025 International Conference on Automation and Computation (Autocom 2025), pp. 1310–1315, 2025.
  • R. R. Patil, A. Yenkikar, M. Bali, R. Mirajkar, and T. Ara, “Biomedical named entity recognition through spaCy: A visual exploration,” in Proceedings of the 2nd International Conference on Advancement in Computing and Computational Technologies (INCAcct 2024), pp. 17–22, 2024.
  • R. S. Kadam, K. R. Singh, S. Rajarajeswari, T. Agrawal, and R. Raghavendra, “Exploring the impact of AI-driven natural language processing in computational analysis,” in 2024 15th International Conference on Computing, Communication and Networking Technologies (ICCCNT 2024), 2024.
  • A. Kale, T. Yaduka, T. Shaikh, S. Chaurasia, and H. Kaur Khanuja, “Unveiling the power of AI prompt engineering: A comprehensive exploration,” in Proceedings of the 10th International Conference on Electrical Energy Systems (ICEES 2024), 2024.
  • R. R. Patil, S. Kumar, and R. Rani, “Smart IoT-based pesticides recommendation system for rice diseases,” Lecture Notes in Electrical Engineering, vol. 959, pp. 17–25, 2023.
  • R. S. Kadam, V. Mishra, S. Dev, A. P. Singh, and B. Geetha, “Applying deep learning strategies for optimizing real-time data analysis in machine learning,” in 2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SmartGenCon 2023), 2023.