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Manager, Machine Learning at Sentera, a John Deere company
I build and lead teams that turn cutting‑edge machine learning research into products that transform agriculture. At John Deere, I manage the development of advanced machine learning systems that deliver actionable insights to growers at a global scale. Previously, as Director of Machine Learning at Sentera, I founded and scaled the company’s ML capabilities, creating deep learning pipelines and computer vision tools that gave farmers and agronomists unprecedented aerial insights. These efforts positioned Sentera as an industry leader and directly contributed to its successful acquisition by John Deere. With a Ph.D. in Computer Science & Engineering from the University of Minnesota and a background spanning geometric vision, robotics, and real‑time perception systems, I’m passionate about driving innovation where AI meets the real world — solving complex problems with measurable impact.
University of Minnesota
Doctor of Philosophy - PhD, Computer Science
January 1, 2012 – January 1, 2018
University of Minnesota
Computer Science
January 1, 2012 – Present
Panepistimion Patron - Electrical Engineering department
Bachelor of Science (BS), Electrical and Electronics Engineering
January 1, 2006 – January 1, 2012
John Deere
Manager, Machine Learning
May 1, 2025 – Present
Greater Minneapolis-St. Paul Area · On-site
Sentera
Director of Machine Learning
January 1, 2024 – May 1, 2025
Tola Capital
Advisor
November 1, 2023 – Present
Seattle, Washington, United States · Remote
Sentera
Principal Scientist
December 1, 2017 – January 1, 2024
Aptiv
Perception Engineer
October 1, 2016 – December 1, 2017
Greater Minneapolis-St. Paul Area
Aptiv
Intern
June 1, 2016 – July 1, 2016
Los Angeles Metropolitan Area
University of Minnesota - Computer Science department
Teaching Assistant
September 1, 2013 – May 1, 2015
Center for Distributed Robotics UMN
PHD Candidate
September 1, 2012 – January 1, 2018
University of Minnesota - Digital Technology Center
Research Assistant
September 1, 2012 – January 1, 2018
Mobile Robot Obstacle Avoidance and Platooning
November 1, 2013 – December 1, 2013
Design of a feedback controller for mobile robot motion control Use of a laser scanner for avoiding obstacles Implementation of a leader-follower scheme via computer vision
Mobile Robot Obstacle Avoidance and Platooning
November 1, 2013 – December 1, 2013
Design of a feedback controller for mobile robot motion control Use of a laser scanner for avoiding obstacles Implementation of a leader-follower scheme via computer vision
Cultural Fit Analysis
The candidate's background is heavily skewed towards Machine Learning, Computer Vision, and Robotics, with significant leadership and research experience. While these fields involve data analysis, the direct alignment with a 'Data Analyst' role, which typically focuses on business intelligence, reporting, and statistical analysis using tools like SQL, Tableau, or Python for data manipulation, is not strong. The projects are highly technical and research-oriented. The breadth of skills listed is primarily in AI/ML, not core data analysis. This suggests a potential mismatch with a traditional Data Analyst role, but could be a strong fit for a Data Scientist or ML Engineer role.
Soft Skills & Operational Fit
The candidate's experience as a Manager and Director of Machine Learning, along with an Advisor role, suggests strong leadership, strategic thinking, and communication skills. The teaching assistant role also indicates an ability to explain complex concepts. However, specific operational fit for a Data Analyst role is not explicitly detailed in the provided data.