Nisha Ramesh
About Nisha Ramesh
Nisha Ramesh serves as the Lead Computer Vision Engineer at Epic Sciences in San Diego, California, where she has worked since 2021. She specializes in developing algorithms for tumor segmentation in brain images and has a strong research interest in shape modeling within the field of image processing and computer vision.
Work at Epic Sciences
Nisha Ramesh has been serving as the Lead Computer Vision Engineer at Epic Sciences since 2021. In this role, she focuses on the development of advanced algorithms for tumor segmentation in brain images. Prior to her current position, she worked at Epic Sciences as a Computer Vision Engineer from 2018 to 2021. Her contributions during this time helped advance the company's capabilities in image processing and analysis.
Education and Expertise
Nisha Ramesh holds a Doctor of Philosophy (PhD) in Electrical and Electronics Engineering from the University of Utah, where she studied from 2013 to 2018. She also earned a Master of Science (M.S.) in Electrical Engineering from the same institution, completing her studies from 2009 to 2011. Her undergraduate degree is a Bachelor of Engineering (B.E.) in Telecommunication from Vishveshvaraya Technological University, obtained from 2005 to 2009. Ramesh has expertise in developing algorithms for tumor segmentation and has a strong research interest in shape modeling within the fields of image processing and computer vision.
Background
Nisha Ramesh began her career as an Image Processing Engineer at Indica Labs in 2012, where she worked for nine months. She then served as a Research Scientist Intern at nView Medical in 2017, focusing on machine learning and image processing. Ramesh also gained valuable experience as a Graduate Research Student at the Scientific Computing and Imaging Institute at the University of Utah from 2013 to 2018, and she held a similar position at the University of Utah from 2010 to 2011.
Achievements
Ramesh led the development of the Breast Cancer Imaging Algorithm, a significant component of DefineMBC, a novel test for metastatic breast cancer. This algorithm integrates both cell-based and cell-free analysis from a single blood draw, showcasing her contributions to advancements in medical imaging and diagnostics.
Technical Skills
Nisha Ramesh utilizes a variety of programming languages and tools in her work, including C, C++, Python, MATLAB, ITK, CUDA, OpenCV, Caffe, TensorFlow, and LaTeX. Her proficiency in these technologies supports her efforts in image processing and computer vision, enabling her to develop effective algorithms for medical applications.