Workshop Description (Intermediate Course)
The analysis of imaging datasets is both exciting and challenging. New and increasingly powerful techniques try to maximize the information derived from multi-dimensional imaging datasets. Yet, every dataset can be a unique analysis challenge, and packages may not always work out-of-the-box. In this workshop, we will explore some popular computational tools to extract quantitative information from imaging data. Our focus will be to first grasp the principles underlying image analysis, and see how they can be logically applied to different kinds of imaging datasets. We will cover image generation, filtering, object identification, measurement of object properties, and the basics of object tracking. Through a series of stepwise hands-on exercises for each concept, we will build up to the goal of designing a full image analysis pipeline. Some programming experience in Python is highly recommended (but optional). Participants are also welcome to bring their own images and videos for discussion.
Workshop Topics
Day 1
Day 1:
- Core concepts and motivation.
- What is a digital image?
- Pixel-level operations.
Day 2
Day 2:
- Pixel-level operations (cont.)
- Variance balancing (thresholding)
- Image segmentation
Day 3
Day 3
- Image segmentation (cont.)
- Feature extraction
- Intro to Modern Computer Vision
Technical Requirements
A MacOS, Windows or Linux computer with Anaconda– https://www.anaconda.com/products/individual Installed (Python 3.8 version). With this installation you will automatically receive Python interpreter as well as Spyder IDE. Please try to ensure, prior to the workshop, that Anaconda & Spyder have been successfully installed.
Instructor
Dr. Sai Bavisetty is a Postdoctoral Researcher in the Deeds Lab within the Department of Integrative Biology and Physiology. His research focuses on developing machine learning algorithms to uncover non-linear structures in high-dimensional and time-series data. Specifically, he aims to identify hidden patterns in brain activity to understand how these structures contribute to or are modified by disease states. Sai is also deeply interested in how network topology influences the dynamics of biological systems. He earned his PhD in Mathematics from the University of Illinois at Urbana-Champaign and previously completed a one-year postdoctoral fellowship at the University of Florida Shands Hospital.
Email: sbavisetty at g.ucla.edu
Videos
Reviews
The instructor takes time to listen to questions and provides clear answer
The instructor is an excellent communicator, listener, clearly answers questions, and a great teacher.
Workshop Details
Prerequisites: Intro to Python (W9) is recommended
Length: 3 days, 3 hrs per day
Level: Intermediate
Location: Boyer 529
Seats Available: 28
Spring 2026 Dates
Apr. 28, Apr. 29 and Apr. 30
9:00 AM – 12:00 PM
REGISTRATION IS OPEN!
