Ms . TULASI GAYATRI DEVI ,National Formosa University,Taiwan
Dr. Abhishek Kumar is a distinguished academic and researcher at National Formosa University, Taiwan. He has earned recognition for his contributions to the field of mechanical engineering, particularly in areas related to advanced manufacturing technologies, robotics, and automation.Dr. Kumar holds a PhD in Mechanical Engineering from a reputed university, where he specialized in innovative techniques to enhance manufacturing processes. His research interests include additive manufacturing, smart manufacturing systems, and industrial automation. He has published numerous papers in top-tier journals and has presented his findings at various international conferences.
Education :
Ph.D. in Information Technology
Department of Information Technology,,National Institute of Technology Karnataka (NITK), Surathkal,,Mangaluru, Karnataka, India.,M.Tech in Computer Science & Engineering,Rao Bahadur Y. Mahabaleshwarappa Engineering College, Ballari,
Visvesvaraya Technological University, Belagavi,,Karnataka, India,B.E. in Computer Science & Engineering,Rao Bahadur Y. Mahabaleshwarappa Engineering College, Ballari,,Visvesvaraya Technological University, Belagavi,,Karnataka, India.
Experience:
- Research Scholar, Department of Information Technology, National Institute of Technology Karnataka (NITK), Surathkal, Mangaluru, Karnataka, India.
Skills:
- Machine Learning
- Deep Learning
- Image Processing
- Data Analysis
- Programming Languages: Python, MATLAB
- Software: TensorFlow, Keras, Scikit-learn, OpenCV
Research Focus:
- Developing and optimizing machine learning and deep learning models for healthcare applications, particularly in cancer detection and classification using medical imaging.
- Improving image processing techniques for better accuracy and efficiency in medical diagnostics.
Publications :
Title: Gaussian Blurring Technique for Detecting and Classifying Acute Lymphoblastic Leukemia Cancer Cells from Microscopic Biopsy Images
Title: Real-time microscopy image-based segmentation and classification models for cancer cell detection
Title: Segmentation and classification of white blood cancer cells from bone marrow microscopic images using duplet-convolutional neural network design
Title: Optimization-based convolutional neural model for the classification of white blood cells
Title: Analysis & Evaluation of Image filtering Noise reduction technique for Microscopic Images
Title: Survey of Leukemia Cancer Cell Detection Using Image Processing