Expertise

Topics:  Machine Learning, Algorithms, Computational Biology, Bioinformatics, Data Mining

Ameet Talwalkar is an assistant professor in the Machine Learning Department at Carnegie Mellon University, and also co-founder and chief scientist at Determined AI. He led the initial development of the MLlib project in Apache Spark, is a co-author of the textbook Foundations of Machine Learning (MIT Press), and created an award-winning edX MOOC on distributed machine learning.

Media Experience

Pittsburgh’s AI-Powered Renaissance  — CMU News
"CMU has an unparalleled degree of expertise in AI among its faculty and students. In the context of human-centric AI, the fact that we have distinct departments in machine learning, human-computer interaction, and language technologies, coupled with a highly collaborative research environment, gives CMU and Pittsburgh a technical advantage. We have a burgeoning startup scene, in part based on academic spinouts, including two of the fastest growing AI startups in the world: Abridge AI and Skild AI."

Researchers outline promises, challenges of understanding AI for biological discovery  — Medical Xpress
"Interpretable machine learning has generated significant excitement as machine learning and artificial intelligence tools are being applied to increasingly important problems," said Ameet Talwalkar, an associate professor in CMU's Machine Learning Department (MLD).

Determined AI makes its machine learning infrastructure free and open source  — TechCrunch
“They’re using things like TensorFlow and PyTorch,” said Chief Scientist Ameet Talwalkar. “A lot of the way that work is done is just conventions: How do the models get trained? Where do I write down the data on which is best? How do I transform data to a good format? All these are bread and butter tasks. There’s tech to do it, but it’s really the Wild West. And the amount of work you have to do to get it set up… there’s a reason big tech companies build out these internal infrastructures.”

AI in the 2020s Must Get Greener—and Here’s How The push for energy efficient “Green AI” requires new strategies | Opinion  — IEEE Spectrum
The environmental impact of artificial intelligence (AI) has been a hot topic as of late—and I believe it will be a defining issue for AI this decade. The conversation began with a recent study from the Allen Institute for AI that argued for the prioritization of “Green AI" efforts that focus on the energy efficiency of AI systems.