Help & Supportcareers@gravityer.com
Computer Vision and Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
My research interests lie in the field of applied machine learning and computer vision. In my thesis, I studied the problem of semantic understanding of activities in videos. My thesis focused on the question of how to improve large-scale action recognition. I am also interested in unsupervised and weakly supervised analysis of videos.
Oregon State University
Doctor of Philosophy (PhD), Computer Science
January 1, 2011 – January 1, 2016
Shahid Beheshti University
Master of Science (MS), Computer Science
January 1, 2008 – January 1, 2010
University of Tehran
Bachelor of Science (BS), Computer Science
January 1, 2000 – January 1, 2005
Apple
Staff Machine Learning Research Engineer
October 1, 2020 – Present
Apple
Senior Machine Learning Research Engineer
January 1, 2017 – October 1, 2020
NVIDIA
Research Intern
June 1, 2016 – September 1, 2016
Santa Clara
Qualcomm Research
Intern
June 1, 2014 – September 1, 2014
San Francisco Bay Area
Oregon State University
Student
September 1, 2011 – December 1, 2016
Data Processing
Architect
July 1, 2008 – August 1, 2011
Data Processing
Developer and Designer
July 1, 2005 – July 1, 2008
American Football Video Analysis
December 1, 2011 – Present
In this project we analyze a wide range of american football videos to extract information for coaches. My task was to detect the start of plays which we call moment of snap. The difficulty in this project was the unconstrained video dataset with different viewpoints, noisy camera records and different fields. In mean time I also work on detecting the line of scrimmage, and camera motion.
Cultural Fit Analysis
The candidate's career trajectory from academic research to senior and staff roles at Apple, along with internships at NVIDIA and Qualcomm, suggests an ambition for high-impact, technically challenging environments. The personal project in sports video analysis indicates a proactive learning attitude and interest beyond core work. The target role of 'Data Analyst' might be a slight pivot from their primary Machine Learning Research Engineer background, but their analytical and research skills are highly transferable. The breadth of experience from network management to cutting-edge ML research shows adaptability. However, the lack of explicit project details or team contributions makes it difficult to fully assess cultural fit beyond technical alignment.
Soft Skills & Operational Fit
The candidate's resume indicates a strong research background and experience in large tech companies (Apple, NVIDIA, Qualcomm). This suggests a capacity for independent problem-solving, structured thinking, and working within established engineering processes. However, specific soft skills like teamwork, leadership, or communication are not explicitly detailed in the provided data. The project description for 'American Football Video Analysis' shows initiative and problem-solving in an unconstrained data environment.