Join us on Thursday, April 26, 2018, 3:00-5:00 PM at the Abess Center (Ungar 230C-D) for the 2017-2018 CCS Fellows’ concluding project presentations. The vision of the IDSC Fellows Program is to inspire a new generation of leaders in computational science to cross the traditional boundaries between disciplines, by equipping them with new cross-disciplinary skills and experience. The Program does this by offering mentorship outside the students’ area of expertise. “IDSC Fellow” is a prestigious designation awarded to two undergraduate students and two graduate students per year.

This event is free and open to interested UM Faculty/Staff/Students.  Refreshments will be served.

 

LOCATION
The Leonard and Jane Abess Center for Ecosystem Science and Policy, Room 230C-D, in the Arthur A. Ungar  Building, 1365 Memorial Drive, Coral Gables, FL 33146.  |  Map + Directions

 

Meet the 2017-2018 IDSC Fellows:

 

	Hanjing Dai Advisor   Brian Haus, PhD | Department of Ocean Sciences IDSC Mentor  Shahriar Negahdaripour, PhD | Electrical & Computer Engineering Project  Image Rectification for Polarimetric Slope Sensing Data Bio  Hanjing is a first-year Ph.D student working under the supervision of Dr. Brian Haus at the Division of Applied Marine Physics, University of Miami. She received her M.Sc. in Civil and Environmental Engineering in 2015 from HKUST. Her research interests focus on both fluid dynamics and morphology in coastal regions, by using laboratory and mathematical models she hopes to investigate the realistic evolution of the coastal environment. Hanjing does research in Civil Engineering, Ocean Engineering, and Remote Sensing.
	Matt Grossi Advisor   Tamay Özgökmen, PhD | Department of Ocean Sciences IDSC Mentor  Miroslav Kubat, PhD | Electrical & Computer Engineering Project  Predicting Ocean Dispersion Using Neural Networks Bio  Matt Grossi is a PhD student in Meteorology and Physical Oceanography at the Rosenstiel School of Marine and Atmospheric Science (RSMAS). He is working with Dr. Tamay Özgökmen and the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) towards understanding and predicting how spilled oil gets transported in the ocean using field observations, hydrodynamic models, and, as an IDSC Fellow, neural networks. Matt holds a B.S. in Physical Oceanography with a minor in Meteorology from Florida Institute of Technology and a M.S. in Oceanography from the University of Delaware. Before coming to the University of Miami, he worked in the Ocean Observation Laboratory at the University of Massachusetts Dartmouth School for Marine Science and Technology (SMAST) where he oversaw underwater glider operations and maintained a regional network of high-frequency (HF) radar sites for monitoring coastal ocean surface currents in near real time.
	Thomas McCauley Advisor   Michael Mcullough, PhD | Department of Psychology IDSC Mentor  Kamal Premarathe, PhD | Electrical & Computer Engineering Project  Properties of Network Models in Social Psychology Bio  Thomas graduated with a B.S. in psychology from the University of Delaware in 2014, and an M.A. in experimental psychology from the College of William & Mary in 2017.  He joined the EHB lab in fall of 2017, with the aim of pursuing questions pertaining to the evolved psychological mechanisms underlying cooperation, punishment, emotion, and morality. His goal is to understand how these mechanisms interact with enduring ecological features by identifying points of variance and invariance in their function across diverse societies. He’s also interested in statistics, experimental methodology, reproducibility in psychological science, and meta-science.
	Sathvik Palakurti Advisor   Michelle Afkami, PhD | Department of Biology IDSC Mentor  Neil Johnson, PhD | Department of Physics Project  Modeling Relationships Between Taxa Using Microbiome Networks Bio  Sathvik is an undergraduate student pursuing a degree in Biology and Mathematics (Applied). He is interested in emerging systems biology approaches to complex problems and is currently using coexpression network analyses of RNAseq data to ask about the molecular basis of Multiple Mutualist Effects.