We are primarily concerned with analyzing and mining complex data in various forms - including structured and semi-structured data, signal streams, images and videos - in order to characterize and understand the underlying phenomena and obtain actionable insights. Most of our approaches are based on statistical machine learning, data mining and AI techniques that are attuned to complex data and scalable computation. We address fundamental conceptual/algorithmic issues and also work on a wide variety of real-life applications.
Jette Henderson receives AMIA 2018 Doctoral Dissertation Award (Second Place)
Prof. Ghosh receives Best Professor Award, McCombs School of Business, as Voted by MSBA Class of 2019
Joyce Ho joins CS faculty at Emory as of Jan 2016.
Prof. Ghosh gives a keynote on Personalized Medicine at ICHI 2015
Sanmi to join CS faculty at UIUC Interview
Prof. Ghosh receives 2015 IEEE Tech Achievement Award.
5 Papers accepted at AISTATS 2015. 3 of them are Oral presentations (6% acceptance rate)
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
Niyati Parameswaran receives the Anita Borg Scholarship, and is in the winning teams for Google Hackathon and IBM's Watson Got Talent , all in 2014.
Prof. Ghosh gives a keynote at ICDM 2013 "Predictive Healthcare Analytics under Privacy Constraints"
Prof. Ghosh is Conference Co-chair for SDM 2013
Dr. Koyejo and Prof. Ghosh receive the Amazon Best Student Paper Award at UAI 2013 for "Constrained Bayesian Inference for Low Rank Multitask Learning".
Prof. Ghosh is co-author of the Best Paper at ASPDAC 2012 "EPIC: Efficient Prediction of IC Manufacturing Hotspots with a Unified Meta-Classification Formulation"
Prof. Ghosh is Conference Co-Chair of SDM 2012, Anaheim, CA
IDEAL alumna Srujana Merugu receives the Best Paper Award at SDM11 for "Exploiting Coherence in Reviews for Discovering Latent Facets and Associated Sentiments"
Prof. Ghosh is Program Co-Chair of KDD 2011 (with Prof. Smyth of UC Irvine). KDD is the #1 Conference in Data Mining.
Sponsoring the IDEAL Lab
The Intelligent Data Exploration and Analysis Lab (IDEAL) which is directed by Prof. Ghosh, relies heavily on sponsorship from industry. Industrial participation is central to identifying critical real-life problems for intelligent data analysis and data/web mining. Through this exposure, students can strengthen and find practical applications for their research. Industry benefits by having access to students who are intimately familiar with the problems they are trying to solve and the cutting-edge technologies they are using to do it.
Two levels of industrial sponsorship are common:
Academic cycles are: Fall: Sept 1 - Jan 15. Spring: Jan 16 - May 31. Summer: June 1 - Aug 31.
Checks are made out to "The University of Texas". Accompanying the check should be a cover letter that reads:
[Company Name] is pleased to give an unrestricted gift of $xx,xxx to support the research of Prof. Joydeep Ghosh in the Department of Electrical and Computer Engineering at The University of Texas at Austin, Texas. There is no restriction on the use of these funds.If you prefer to sponsor the lab as a whole, rather than an individual student, you could do so by signing on as a preferred industrial partner; please contact Prof. Ghosh for details.
Contract research is also possible. The terms of the contract must comply with The University of Texas and State of Texas guidelines, including fairly stringent IP issues. Contract research entails about 50% overhead on most items, but accomodates a list of deliverables. It costs approximately $80,000 to support one student plus one month of faculty time for nine months.
Sponsorship entails the following specific benefits (note that non-sponsors also get access to publications and most software, although usually not as promptly):
The primary contact for sponsorship issues is:
Prof. Joydeep Ghosh, Dept. of ECE
The University of Texas at Austin
Austin, TX 78712-1084 USA
Voice: (512) 471-8980
Fax: (512) 471-2893
The template for this page was kindly provided by my colleague, Prof. Brian Evans.