Seemeen Karimi
About Seemeen Karimi
Seemeen Karimi is a Staff Engineer at Lawrence Livermore National Laboratory, where he has worked since 2020. He has extensive experience in biomedical engineering and healthcare data modeling, with previous roles at NeuroLogica Corp and Analogic.
Work at Lawrence Livermore National Laboratory
Seemeen Karimi has been employed as a Staff Engineer at Lawrence Livermore National Laboratory since 2020. In this role, he contributes to various engineering projects, leveraging his extensive background in biomedical engineering and imaging technologies. His work at the laboratory focuses on applying advanced engineering principles to support research initiatives.
Current Role at Elimu Informatics
Since 2017, Seemeen Karimi has served as the Director of Research and Development at Elimu Informatics in the Greater San Diego Area. In this position, he oversees research initiatives and development projects, aiming to enhance healthcare data solutions. His leadership role involves guiding teams in the creation of innovative technologies and methodologies.
Previous Experience at NeuroLogica Corp
Seemeen Karimi held two positions at NeuroLogica Corp. He served as the Director of Advanced Development for 10 months in 2009 and as an Imaging Specialist from 2004 to 2009. In these roles, he focused on advanced imaging technologies and contributed to projects related to security CT systems and imaging solutions.
Educational Background in Biomedical Engineering
Seemeen Karimi obtained his Bachelor of Engineering (BE) in Biomedical Engineering from the University of Mumbai, studying from 1991 to 1995. He furthered his education with a Master of Science (MS) in Biomedical Engineering from the University of North Carolina at Chapel Hill, completing his studies from 1995 to 1997. He later earned a Doctor of Philosophy (PhD) in Electrical Engineering, specializing in Signal and Image Processing, from UCSD between 2010 and 2014.
Expertise in Healthcare Data and Security
Seemeen Karimi possesses expertise in building statistical models for healthcare data, particularly from electronic health records (EHRs). He has collaborated with the University of Texas to develop a prototype genomics archiving system utilizing homomorphic encryption, focusing on secure computation for genomic data. Additionally, he developed Loupe, a knowledgebase that models millions of relationships between EHR concepts for context-relevant viewing.