Vinod Kulathumani

About Vinod Kulathumani

AI Practitioner with 20+ years of experience in the areas of multi-sensor systems, computer vision / AI, distributed location services, mapping, object tracking, and distributed computing. In my current role as a Principal Scientist at Amazon, I lead the Core AI research and development for several innovative product features on Amazon\'s smart shopping cart that leverage latest advances in computer vision and machine learning.Prior to joining Amazon, I was chief scientist at Tvision where I led the design and implementation of activity recognition systems on resource constrained platforms. And before entering into the domain of AI-centered applications,> I have several years of research experience in building robust, fault-tolerant large scale distributed sensor actuator systems, which have been demonstrated to agencies such as DARPA and Los Alamos National Labs.> I was a tenured Associate Professor at West Virginia University where I mentored 3 PhD students, several MS students and acquired/managed managed several large research projects on multi-sensor systems, information-centric data dissemination, distributed querying and tracking.> I have also co-founded a startup company called Aspinity, which focuses on ultra-lower chips for AI applications based on analog signal processing. This diverse systems oriented experience makes me well equipped to manage and reason about end-to-end AI systems including those running on edge devices.

Experience

1. Sr Manager of Applied Science

   Amazon

   Apr 2023 — Present · Boston, MA, US

   Leading the Core AI Research and Development for Amazon Dash Cart and in-store automation for several features such as:1. Cart content estimation and shopper action resolution: A critical feature that fuses inputs from multiple on-cart cameras and sensors to discern shopper actions and generate an accurate, live receipt2. Location based features: Cart positioning and store mapping that support several downstream shopper companion applications such as location based product recommendations, interactive maps, product search and customer navigation3. Shelf modeling and merchant analytics: Building and maintaining a 2.5D model of the store with on-shelf product identification that delivers impactful merchant analytics features

Education

• The Ohio State University

  Ph.D, Computer Science

  1999 — 2008

• University of Mumbai

  Bachelor's degree, Computer Science

  1995 — 1999

Skills

• Wireless Sensor Networks
• Distributed Systems
• C
• Internet of Things
• Sensor Fusion
• Embedded Systems
• C++
• Java
• Algorithms
• Image Processing
• Machine Learning
• Pattern Recognition
• Latex
• Computer Vision
• Computer Science
• Matlab
• Python
• Software Engineering
• Programming
• Artificial Intelligence
• Signal Processing
• Opencv
• Data Mining
• Linux
• Research
• Digital Image Processing
• Sensors
• Simulations
• Data Analysis
• Teaching