Mohammad Yosofvand

MACHINE LEARNING SCIENTIST.
Resourceful graduate researcher with
4+ years of experience in machine
learning and image processing.
Excited to implement deep learning
and computer vision techniques.
At Texas Tech University, designed and
developed computer programs
utilizing machine learning and image
analysis algorithms currently used in
laboratory and clinical applications.

Research Assistant|Texas Tech University
Lubbock, TX - August 2018 - Current
Key Qualifications & Responsibilities
• Developed deep learning algorithms to detect and
classify cells in clinical breast cancer images.
• Implemented computer vision and sophisticated image
processing algorithms to analyze several thousand
medical images.
• Modified an MRI reading program utilizing image
reconstruction algorithms to calculate the dose delivered
to the samples.
• Applied core machine learning methodologies; Artificial
Neural Networks and logistic regressions; on C-elegans
laboratory images.
• Demonstrated strong documentation and writing skills to
generate original correspondence and published several
related peer-reviewed papers.
Key Achievement:
• Designed and Developed "AdipoGauge" software for
detecting and counting adipose cells in microscopic
images which is currently used in clinical and laboratory
applications.

Ph.D.: Mechanical Engineering
Texas Tech University
Lubbock, TX. 2018-08 – Current
Selected Research Paper:
• AdipoGauge software for analysis of biological microscopic
images. Adipocyte, 2020. (IF: 4.5)
Selected Courses:
• Tensor and Linear Systems, Control Theory, Machine Learning,
Image processing, Optimization, Statistics, Professional
Communication in English