Manisha Galphade

Manisha Galphade

Ph.D. Programme in Computer Science and Engineering
Ph.D. Admission Year: 2018
Guide: Dr. V.B. Nikam

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Biography

Manisha Galphade is an experienced academic professional currently working at School of Computing, MIT Art, Design and Technology University, Pune. With a teaching career spanning 16 years, she has contributed significantly to the field of education. She teaches subjects including Machine Learning, Database Management System, Theory of Computation, Data Mining, and many more. Throughout her career, she has authored 4 conference papers, 5 journal papers, and 3 book chapters, showcasing her dedication to research and academic development. She is also pursuing a PhD from Veermata Jijabai Technological Institute, Mumbai, furthering her academic expertise. Her research area is Artificial Intelligence, with research interests in Time Series Analysis, Image Processing, and Signal Processing. Passionate about fostering innovation and critical thinking, she strives to inspire students to reach their full potential. Her extensive experience and research contributions reflect her commitment to advancing knowledge and fostering growth in her field.

Academic Information (Degrees/Education)

ME in Computer Science and Engineering, MGM COE Nanded, SRTM University

Research Interests

Time series analysis, image processing, signal processing

Professional Affiliation

Assistant Professor at School of Computing, MIT Art, Design and Technology, Pune

Professional Experience

Teaching Experience: 16 Years

Publications

  • Galphade M., Nikam V.B., Banerjee B., Kiwelekar A.W.,Priyanka Sharma , (2024),“Stacked LSTM for Short Term Wind Power Forecasting using Multivariate Time Series Data”, International Journal of Interactive Multimedia and Artificial Intelligence (IJIMAI)
  • Galphade, M.,, Nikam, V., Banerjee, B., Kiwelekar, A. 2022, “Intelligent multiperiod wind power forecast model using statistical and machine learning model. ”, Bulletin of Electrical Engineering and Informatics,11(3), 1186-1193, doi:https://doi.org/10.11591/eei.v11i3.3756
  • Galphade M., V.B. Nikam, Biplab Banerjee , Arvind W. Kiwelekar, “Stacked LSTM for Short Term Wind Power Forecasting using Multivariate Time Series Data”,
    International Journal of Interactive Multimedia and Artificial Intelligence
  • P. G. Jaiswal, M. Galphade, “A Review on Machine Learning Techniques in Various Healthcare Application” in International Journal of Research and Analytical Reviews (IJRAR)
  • Abhishek Thorat, Mahesh More, Ganesh, Thombare, Vikram Takalkar, Manisha N. Galphade, (2015). “An Anti-phishing Framework using Visual Cryptography
    International Journal of Advanced Research in Computer and Communication Engineering 4(2): 332-334
  • Galphade, M., Nikam, V. B., Yedurkar, D., Singh, P., & Stephan, T. (2024). Semantic Analysis Using Deep Learning for Predicting Stock Trends. Procedia Computer Science, 235, 820-829.
  • Saigiridhari, A., Mishra, A., Tupe, A., Yedurkar, D., Galphade, M., 2024 “Deep CNN Based Alzheimer Analysis in MRI Using Clinical Dementia Rating.”,In: Muthalagu, R., P S, T., Pawar, P.M., R, E., Prasad, N.R., Fiorentino, M. (eds) Computational Intelligence and Network Systems. CINS 2023. Communications in Computer and Information Science, vol 1978. Springer, Cham. https://doi.org/10.1007/978-3-031-48984-6_9

  • Galphade M., More N., Nikam V. B., “Crop Yield Prediction using Weather Data and NDVI Time Series Data” in International Conference on Advances in Data computing and Security (I3CS),Sept.8-10, 2021 , at National Institute of Technology, Kurukshetra. Springer Book Series “Lecture Notes on Data Engineering and Communication Technologies”
  • Karhade A., Yogi A., Gupta A., Landge P., Galphade M., “CNN for Detection of COVID-19 using Chest X-Ray images” in International Conference on Advances in Data computing and Security (I3CS),Sept.8-10, 2021 , at National Institute of Technology, Kurukshetra. Springer Book Series “Lecture Notes on Data Engineering and Communication Technologies”
  • Galphade M., More N., Nikam V.B., Banerjee B., Kiwelekar A.W. (2021) “Understanding Deep Learning: Case Study Based Approach”, In: Suresh A., Paiva S. (eds) Deep Learning and Edge Computing Solutions for High Performance Computing. EAI/Springer
    Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-60265-9_9
  • More N., Galphade M., Nikam V.B., Banerjee B. (2021) High Performance Computing: A Deep Learning Perspective. In: Suresh A., Paiva S. (eds) Deep Learning and Edge Computing Solutions for High Performance Computing. EAI/Springer Innovations in
    Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-60265-9_15
  • More, N.P., Galphade, M., Nikam, V.B., Banerjee, B. (2022). Geospatial BigData and Its Applications. In: Goyal, M.K., Gupta, A.K., Gupta, A. (eds) Hydro-Meteorological Extremes and Disasters. Disaster Resilience and Green Growth. Springer, Singapore. https://doi.org/10.1007/978-981-19-0725-8_11

 

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