The Data Shows: MCIRCC Student Researchers are Top Notch!

MCIRCC offers hearty congratulations to four students who recently won awards from the National Institutes of Health (NIH) and the University of Michigan Electrical Engineering and Computer Science Department (EECS).

The students comprise different data-based disciplines—from computer science to bioinformatics—yet are united as part of a research team under the leadership of Kayvan Najarian, PhD., Director of MCIRCC’s Data Science unit and an Associate Director at MCIRCC. The fact that these students won these highly competitive awards over the course of a single year speaks volumes towards their excellence in research. It also reflects the profound impact Dr. Najarian’s group has on the community, the university,  and on MCIRCC’s mission of transforming critical care through innovation, integration and entrepreneurship.

NIH F31 Predoctoral Training Grant

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Negar Farzaneh

(Ph.D. Candidate, Department of Computational Medicine and Bioinformatics)

The National Institutes of Health predoctoral training program enables promising predoctoral students who have the potential to develop into productive, independent research scientists to obtain mentored research training while conducting dissertation research.

The EECS Outstanding Research Award

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Cheng Jiang

(M.S. Student, Electrical Engineering and Computer Science) 

The EECS Outstanding Research Award is given to students whose project performance goes above and beyond the requirements in a course or as part of an independent project with a faculty member or graduate student. Cheng received this award for his project “Mid-surface Detection and Outcome Prediction for Patients with Traumatic Brain Injuries.

NIH T32 Bioinformatics Training Program Appointees

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Olivia Alge

(Ph.D. Student, Department of Computational Medicine and Bioinformatics)

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Elisa Warner

(Ph.D. Student, Department of Computational Medicine and Bioinformatics)

The NIH Bioinformatics Training Program trains Ph.D. students in the fundamentals and applications of computational and information sciences to gain insights and develop new strategies to solve problems relevant to basic biomedical research.