Developing a Brain Atlas Using Deep Learning with Theofanis Karayannis

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Today we’re joined by Theofanis Karayannis, Assistant Professor at the Brain Research Institute of the University of Zurich.

Theo’s research is currently focused on understanding how circuits in the brain are formed during development and modified by experiences. Working with animal models, Theo segments and classifies the brain regions, then detects cellular signals that make connections throughout and between each region. How, you may ask? The answer is (relatively) simple: Deep Learning. Adapting DL methods to fit the biological scope of work, Theo looks at the distribution of connections that makes neurological decisions in both animals and humans every day. From the way images of the brain are collected to genetic trackability, this is an episode you don’t want to miss.

About Theo

From the Interview

TWIMLcon Update

TWIMLcon: AI Platforms will feature live “keynote interview” podcast recordings with accomplished guests in the industry. Read on to learn about a few of the ones we just announced:

 Andrew Ng. I can’t think of anyone who’s done more to bring new practitioners into the fields of machine learning and deep learning than Andrew and we’re so excited to be opening the event with him. He’ll be sharing what he’s learned helping many businesses with machine learning and AI, and also speak with us about where he sees the field going.

Hussein Mehanna. Hussein is the Head of AI/ML Cruise, the self-driving car company. Before Cruise, Hussein helped build Google’s Cloud ML Platform and Facebook’s FBLearner platform. He’ll be sharing some of the lessons he’s learned building ML platforms from scratch at some of the most advanced companies in the space, and applying these lessons with much smaller teams.

Fran Bell. Fran is the director of data science responsible for Data Science Platforms at Uber. Fran leads a team building use-case focused ML platforms supporting areas like Forecasting, Anomaly Detection, Segmentation, NLP & Conversational AI, and more. Her platforms sit on top of Uber’s Michelangelo, putting her in a unique position to speak with us about how both low-level and higher-level ML platforms can drive data scientist and developer productivity.

Beyond keynote interviews like these, we’ve got a bunch of interesting speakers lined up to share their successes and failures helping their organizations build and productionalize ML and deep learning models. Stay tuned for more details!

Meetup Update!

Many of you are aware that we’ve been hosting a couple of paper-reading meetups in conjunction with the podcast. I’m excited to share that Matt Kenney, Duke staff researcher and long-time listener and friend of the show, has stepped up to help take this group to the next level. The paper reading meetup will now be meeting every other Sunday at 1 PM Eastern Time to dissect the latest and greatest academic research papers in ML and AI. If you want to take your understanding of the field to the next level, check for more upcoming community events.

We’ve also got a couple of study groups currently running, one working through the Deep Learning from the Foundations course, another on [Natural Language Processing] (, and another working through the Stanford cs224n Deep Learning for Natural Language Processing course. These study groups just started and will be working on these courses through October and November, so it’s not too late to join. Sign up on the meetup page at

Check it out

“More On That Later” by Lee Rosevere licensed under CC By 4.0

Leave a Reply

Your email address will not be published.