UT-MINDS (Machine INtelligence and Decision Systems) @ WNCG

The WNCG initiative in Machine INtelligence and Decision Systems (UT-MINDS) involves research in large-scale data mining and machine learning, with applications to solving complex engineering or business problems. Going beyond just algorithmic/statistical machine learning, we specialize in reliable and effective design of full-stack systems, from acquisition and conditioning of sensory and other high-volume/disparate data sources, through to continual learning and decision making logic built on top of learning systems.

Topics of expertise include modeling and analysis of complex networks, both social and physical, design of large-scale recommender systems, analysis of heterogeneous and complex EHR and other health data, learning from distributed sensor data acquired from intelligent transportation systems, multi-modal machine learning, etc. Seminal advances have been made in the theoretical (sample complexity, statistical bounds, etc), algorithmic, statistical and hardware/software implementational aspects associated with such problems. We have also deployed several data-driven solutions that interface with real cyber-physical systems.

UT-MINDS invites industry partners through its AFFILIATES program.

News

Prof. Robert Heath gave a keynote talk on “Configuring MIMO Communication Links with Machine Learning“ at IEEE ML4COM. Video of the talk is available here: YouTube | YOUKU

Two papers at ICML 2018 from UT-MINDS authors!

Four papers from UT-MINDS authors at AISTATS 2018! Congratulations to Rahi Kalantari, Rajiv Khanna and Rajat Sen!

Machine Learning for Healthcare startup Accordion Health acquired by publicly listed health analytics company, Evolent Heath. All 3 founders of Accordion Health are from UT-MINDS.

Prof. Alex Dimakis has 6 papers accepted at ICML, 2017. Congrats! This is a top international conference on machine learning.

Prof. Ghosh appointed as Chief Scientific Officer of CognitiveScale. CognitiveScale incorporates several AI technologies, including advanced machine learning, for scalable, enterprise-level solutions, and counts several Fortune 500 Companies among its clients. Prof. Ghosh will continue to be a faculty at UT; however this engagement showcases the relevance of our group in enabling innovative and industry-strength products and solutions.

Team headed by Prof. Ghosh receives 2017 Distinguished Clinical Informatics Research Paper Award at AMIA for "PheKnow-Cloud: A Tool for Evaluating High-Throughput Phenotype Candidates using Online Medical Literature"

Alumna Suju Rajan receives the 'Best Paper Award at RecSys14 for "Beyond Clicks: Dwell Time for Personalization"

Joyce Ho and Yubin Park are 2014 Code-a-Palooza Winners at Datapalooza 2014