Nahid Ul Islam
Scholar

Nahid Ul Islam

Google Scholar ID: uusv5scAAAAJ
PhD (Computer Science) Student
Medical Image AnalysisDeep LearningComputer Vision
Citations & Impact
All-time
Citations
120
 
H-index
6
 
i10-index
4
 
Publications
16
 
Co-authors
0
 
Resume (English only)
Academic Achievements
  • Published multiple conference and journal papers in the fields of Computer Vision and Medical Image Analysis; holds two granted patents and five pending patents.
Research Experience
  • - Graduate Research Assistant, Arizona State University (Aug 2018 – Present): ASU-Mayo Clinic Joint Research Collaboration – Published five conference papers and two journal papers; hold two granted and five pending patents; developed EViT system for pulmonary embolism diagnosis; designed Foundation X multi-task model for chest X-ray analysis; advanced Foundation CTPA generic slice-based 3D foundation model.
  • - Graduate Technical Intern, Intel Corporation, Client Computing Group (May 2017 – Aug 2017): Applied deep learning and computer vision techniques for obstacle detection/classification and collision prediction.
  • - Graduate Software Engineering Intern, Intel Corporation, Client Computing Group (Feb 2017 – May 2017): Developed a human activity recognition system based on video using deep learning and computer vision technologies.
Education
  • - Ph.D. in Computer Science, Arizona State University, USA (2018 – Present), Supervisor: Dr. Jianming Liang, Research Area: Computer Vision, Deep Learning, Medical Image Analysis
  • - M.Sc. in Computer Science, University of Texas at San Antonio, USA (2015 – 2017), Supervisor: Dr. Qi Tian, Research Area: Computer Vision, Machine Learning, Image Processing
  • - B.Sc. in Computer Science, BRAC University, Bangladesh (2010 – 2014), Supervisor: Rubel Biswas, Research Area: Image Processing
Background
  • Research Interests: Computer Vision, Deep Learning, Medical Image Analysis. Summary: A Ph.D. candidate in Computer Science at Arizona State University (collaborative research with Mayo Clinic), specializing in developing annotation-efficient and generalizable deep learning frameworks, with a strong record of publications in leading journals and conferences, and holding multiple granted and pending patents.
Miscellany
  • Programming skills: Python, MATLAB, Java, C/C++; strong foundation in algorithms, data structures, and database design; extensive experience in object-oriented analysis, design, and implementation.
Co-authors
0 total
Co-authors: 0 (list not available)