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Machine Learning Manager, Apple Ads
I have an electrical engineering (signal processing and computer vision) and mathematics background. I have worked on engineering problems including recommender systems, machine learning, computer vision particularly as applied to medical image processing and x-ray security imaging, time series analysis, blind source separation, and microphone array processing. I also do a lot of algorithm design and algorithm development; I primarily work in C++, Java, or Scala typically with Matlab or Python for prototyping. I also use Pig, Hive, and Spark, as well as R for statistical exploration. Specialties: Machine learning, classification, computer vision, image processing, image denoising, sparse reconstruction, compressed sensing, mathematical optimization, level set methods, image segmentation, image registration, graph-based methods, combinatorial optimization, 3D visualization.
Georgia Institute of Technology
Ph.D., Electrical and Computer Engineering
January 1, 2001 – January 1, 2005
Rutgers University
M.S., Electrical and Computer Engineering
January 1, 1998 – January 1, 2001
Rutgers University
B.S., Electrical Engineering
January 1, 1994 – January 1, 1998
Apple
Machine Learning Manager, Apple Ads
July 1, 2025 – Present
Cupertino, California, United States
Apple
Machine Learning Engineer - Ad Platforms Engineering
November 1, 2021 – July 1, 2025
Cupertino, California, United States
Netflix
Senior Machine Learning Engineer
October 1, 2017 – November 1, 2021
Los Gatos, California
ipsy
Director of Personalization
August 1, 2016 – October 1, 2017
San Mateo, California
Netflix
Sr. Research/Software Engineer
December 1, 2012 – August 1, 2016
Los Gatos, CA
American Science and Engineering
Senior Image Processing Scientist
January 1, 2011 – December 1, 2012
Siemens Corporate Research
Research Scientist
January 1, 2006 – January 1, 2011
University of Pennsylvania
Postdoctoral Research Fellow
September 1, 2005 – October 1, 2006
Sarnoff Corporation
Signal Processing Consultant
May 1, 2000 – August 1, 2001
Lutron Electronics
Electrical Engineering Intern
May 1, 1997 – September 1, 1997
Cultural Fit Analysis
The candidate has a diverse background spanning research, image processing, and machine learning engineering across various industries (tech, medical, defense). While the target role is 'Data Analyst', the candidate's experience is heavily skewed towards Machine Learning Engineering and Research, which is a more specialized and advanced domain. This indicates a potential overqualification or a need to align expectations regarding the scope of a Data Analyst role. The breadth of experience suggests adaptability, but the direct alignment with a pure 'Data Analyst' role, which often focuses more on reporting, dashboards, and business intelligence rather than model development, is moderate.
Soft Skills & Operational Fit
The candidate's resume highlights leadership in technical projects and teams, participation in hackathons, and conducting technical interviews, suggesting strong collaboration, problem-solving, and mentorship abilities. The descriptions indicate a proactive approach to improving processes (e.g., A/B experiment design).