Once every week while school is in session, EECS invites a distinguished researcher or practitioner in a computer science or electrical and computer engineering-related field to present their ideas and/or work. Talks are generally targeted to electrical engineering and computer science graduate students. This colloquium series is free and open to everyone.

Upcoming Colloquia

Sensors for Closed-loop Health Management

Monday, October 2, 2017 - 4:00pm to 4:50pm
LPSC 125

Speaker Information

J.-C. Chiao
Janet and Mike Greene Professor
Jenkins Garrett Professor
Electrical Engineering Department, University of Texas - Arlington


Mobile technologies have changed our life style significantly. Personalized tools such as wearable and implantable devices through wireless communication and Internet of Things have been utilized in healthcare to provide unique functions and reduce costs. Individuals can be empowered with tailored solutions without limitation in mobility or daily activities. Quantitative documentation of physiological parameters presents more accurate assessment. Direct stimulation on tissues or organs by electrical signals can restore or improve body functions. Continuous monitoring and adaptive administration of therapy to treat symptoms via wireless body networking can adaptively optimize the closed-loop health management.


This presentation discusses the development of wireless micro devices and integrated systems for clinical applications. The systems are based on batteryless, wireless implants with enhancement in miniaturization and functionalization. Miniaturization owing to flexible substrates and the elimination of bulky batteries allows endoscopic or minimally invasive procedures to deploy the implants without painful surgeries. Several diagnosis and therapeutic treatment examples for management of gastric and neural disorders, particularly as closed-loop systems, will be introduced. These examples aim to inspire new system application ideas to address the implementation and cost challenges in healthcare, and enable integration of electronics and medicines to improve human welfare and assist better living.

Speaker Bio

J.-C. Chiao is Greene professor and Garrett professor of Electrical Engineering at University of Texas – Arlington. He received his PhD at Caltech and was with Bellcore, University of Hawaii-Manoa and Chorum Technologies before he joined UT-Arlington in 2002. 

Dr. Chiao has published more than 260 peer-reviewed papers and received 12 patents. He received the 2011 O'Donnell Award in Engineering presented by The Academy of Medicine, Engineering and Science of Texas. He received the Tech Titan Technology Innovator Award; Lockheed Martin Aeronautics Excellence in Engineering Teaching Award; Research in Medicine milestone award by Heroes of Healthcare; IEEE MTT Distinguished Microwave Lecturer; IEEE Region 5 Outstanding Engineering Educator and individual Achievement awards. Currently, he is an IEEE Sensors Council Distinguished Lecturer and serving as the Editor-in-Chief for Journal of Electromagnetics, RF and Microwaves in Medicine and Biology. His webpage is at http://www.uta.edu/faculty/jcchiao/

Human Allied Artificial Intelligence

Monday, October 9, 2017 - 4:00pm to 4:50pm
LPSC 125

Speaker Information

Sriraam Natarajan
Associate Professor
Department of Computer Science
University of Texas Dallas


Statistical Relational Learning (SRL) Models combine the powerful formalisms of probability theory and first-order logic to handle uncertainty in large, complex problems. While they provide a very effective representation paradigm due to their succinctness and parameter sharing, efficient learning is a significant problem in these models. First, I will discuss state-of-the-art learning method based on boosting that is representation independent. Our results demonstrate that learning multiple weak models can lead to a dramatic improvement in accuracy and efficiency.

One of the key attractive properties of SRL models is that they use a rich representation for modeling the domain that potentially allows for seam-less human interaction. However, in current SRL research, the human is restricted to either being a mere labeler or being an oracle who provides the entire  model. I will present our recent work that allows for more reasonable human interaction where the human input is taken as “advice” and the learning algorithm combines this advice with data. Finally, I will discuss our work on soliciting advice from humans as needed that allows for seamless interactions with the human expert.

Speaker Bio

Sriraam Natarajan is an Associate Professor at the Department of Computer Science at University of Texas Dallas. He is on leave as an Associate Professor of Informatics and Computer Science at Indiana University. He was previously an Assistant Professor at Indiana University, Wake Forest School of Medicine, a post-doctoral research associate at University of Wisconsin-Madison and had graduated with his PhD from Oregon State University. His research interests lie in the field of Artificial Intelligence, with emphasis on Machine Learning, Statistical Relational Learning and AI, Reinforcement Learning, Graphical Models and Biomedical Applications. He has received the Young Investigator award from US Army Research Office and the IU trustees Teaching Award from Indiana University. He is an editorial board member of MLJ, JAIR and DAMI journals and is the electronics publishing editor of JAIR. He is the organizer of the key workshops in the field of Statistical Relational Learning and has  co-organized the AAAI 2010, the UAI 2012, AAAI 2013, AAAI 2014, UAI 2015 workshops on Statistical Relational AI (StarAI), ICML 2012 Workshop on Statistical Relational Learning, and the ECML PKDD 2011 and 2012 workshops on Collective Learning and Inference on Structured Data (Co-LISD). He was also the co-chair of the AAAI student abstract and posters at AAAI 2014 and AAAI 2015 and the chair of the AAAI students outreach at AAAI 2016 and 2017.

Past Colloquia

John F. Wager
Monday, May 13, 2013 - 4:00pm to 4:50pm
Zhaohui Wang
Monday, April 22, 2013 - 8:45am to 9:45am
Danny Dig
Friday, April 19, 2013 - 9:00am to 10:15am
Stefano Rini
Friday, April 19, 2013 - 8:45am to 9:45am
Ashkan Behnam
Tuesday, April 16, 2013 - 8:45am to 9:45am
Ram Ravichandran
Monday, April 15, 2013 - 4:00pm to 4:50pm
Raffay Hamid
Monday, April 15, 2013 - 10:00am to 11:00am
Li-Jing Larry Cheng
Friday, April 12, 2013 - 8:45am to 9:45am
Hank Childs
Monday, April 8, 2013 - 4:00pm to 4:50pm