Even the best of teams can struggle to work together. This workshop uses The Five Dysfunctions of a Team by Patrick Lencioni to recognize common pitfalls of a team such as absence of trust, fear of conflict, lack of commitment, avoidance of accountability, and inattention to team results. Participants will then explore the meaning behind these issues and identify various strategies for overcoming them.

This is a great class that uses a variety of equipment that will tone and strengthen your entire body. This class will have you sweating hard and feeling accomplished.

Introduction to Qualitative and thematic anaylsis with NVivo. If you conduct interviews, focus groups, or work with qualitative data and would like to learn about one of the most powerful qualitative analysis software, this workshop is for you. No prior experience with NVIVO needed.

Brace yourself for an electrifying workout experience that blends the power-packed moves of kickboxing. Every session is a thrilling combination of strength, agility, and cardiovascular training designed to keep you at the top of your game. This 30-minute cardio session class will be quick, fun, and will have you jabbing and kicking up a nice sweat!   

This mind and body class utilizes yoga movements to improve your flexibility, posture, strength, and balance. The class will bring attention and focus to your breath while you flow from one posture to the next. 

Click here to let the organizers know if you are attending!Speaker Hmayag Partamian of the Department of Bioengineering will present "Machine Learning on Interictal Intracranial EEG Predicts Surgical Outcome in Drug Resistant Epilepsy."Abstract:Surgical success for patients with focal drug resistant epilepsy (DRE) relies on accurate localization of the epileptogenic zone (EZ). Currently, no exam delineates this zone unambiguously. Instead, the EZ is approximated by the area where seizures begin, which is identified manually through a tedious process that is prone to errors and biases. More importantly, resection of this area does not always predict good surgical outcome. Here, we propose an artificially intelligent, patient-specific framework that automatically identifies the EZ requiring little to no input from clinicians, without waiting for a seizure to occur. The framework transforms intracranial electroencephalography data into spatiotemporal representations of brain activity discriminating the epileptogenic networks from the background activity. The epileptogenic network delineates the EZ with high precision and predicts surgical outcome. The framework eliminates the need for manual data inspection and enhances surgical planning for patients with drug resistant epilepsy.The spotlight seminar is open to the UTA Community. Refreshments will be served at 3:45 p.m.