Welcome to Fall 2016 Bio-Seminar in the Department of Electrical & Computer Engineering at Texas A&M!

Next Seminar

See you next spring!

Tentative Schedule

2016-09-02 Intrinsically Bayesian Robust Operators and Optimal Experimental Design Based on Uncertainty Quantification

by Prof. Edward Dougherty from ECE @ TAMU

[Slides]

2016-09-16 Cryo-EM and Molecular Modeling of Structure and Dynamics for RNA Molecules

by Prof. Junjie Zhang from Biochemistry @ TAMU

2016-09-23 High-Throughput Microfluidics: An Example in Accelerating Next-Generation Biofuel Development

by Prof. Arum Han from ECE @ TAMU

2016-10-07 Info-Clustering: An Information-Theoretic Paradigm for Data Clustering

by Prof. Tie Liu from ECE @ TAMU

2016-10-14 High-dimensional Classification via Sparse Linear Projections with Application to Gene Expression Data

by Prof. Irina Gaynanova from Statistics @ TAMU

2016-10-21 Optimal Expert Knowledge Elicitation for Bayesian Network Structure Identification

by Prof. Shuai Huang from Industrial Engineering @ University of Washington hosted by ISEN @ TAMU

2016-10-28 Questioning Questions in Computational Neuroscience

by Prof. Yoonsuck Choe from CSE @ TAMU

[Slides]

2016-11-04 Covariance Tomography: Understanding Heterogeneous Protein Structures Using Cryogenic Electron Microscopy

by Prof. Hemant Tagare from EE & BME @ Yale hosted by ECE Department Seminar

2016-11-11 New Ways to Imaging Interventional Devices with MRI

by Prof. Jim Ji from ECE @ TAMU

2016-11-18 Understanding Social Spammers: A Data Mining Perspective

by Prof. Xia Ben Hu from CSE @ TAMU

2016-12-02 Hacking Nervous System: Opportunities and Challenges in Soft Wireless Bioelectronics

by Prof. Sung Il Park from ECE @ TAMU

Other notable events on campus

2016 Fall ECE Department Seminar

2016-09-23 to 2016-09-24 Conference on Advances in Big Data Modeling, Computation and Analytics

2016-10-21 TAMU Engineering and Health Science Symposium Series (EHSSS): Collaborative Research in Neuroscience

2016-10-24 TAMU CSE Distinguished Lecture "Three Principles of Data Science: Predictability, Stability, and Computability" by Prof. Bin Yu from UC Berkeley

2016-10-26 TAMU Imaging Science Spot Series featuring Nobel Laureate Prof. W. E. Moerner