Ioannis Sgouralis, Graduate Student

I was born in Kalampaka, Greece under the rocks of Meteora. In 2004, I entered the School of Applied Mathematical and Physical Sciences at the National Technical University of Athens (NTUA), from which I graduated in 2009 with a Diploma in Applied Mathematics. My major was in Applied Analysis and Engineering. During the year 2008-2009, I conducted my diploma thesis on the Direct Problem of Acoustic Wave Scattering, under the supervision of Professor Drossos Gintides.

In the summer of 2009, I moved to Durham, NC to continue my studies at the Mathematics Department of Duke University. My research interest is in Mathematical Physiology, mainly in Renal Hemodynamics. Since the summer of 2010, I have been working on a model of the renal afferent arteriole. The goal of the project is to understand the interactions between blood flow, autoregulatory mechanisms, and kidney functions under physiologic and pathophysiologic conditions.

Please note: Ioannis has left the Mathematics department at Duke University; some info here might not be up to date.

Contact Info: 

Office Location:	025 Physics
Office Phone:	919-660-2832
Email Address:
Starting Year:	2009
Mentor(s):	Stephanos Venakides
Advisor(s):	Anita T. Layton

Education:

PhD	Duke University	2014
MS	Duke University	2011
Diploma	National Technical University of Athens	2009

Specialties:

Applied Math

Research Interests: Mathematical Physiology, Computational Fluid Dynamics

Mathematical Physiology: Blood flow autoregulation is an essential factor of proper renal activity. In the microcirculatory level, it is mostly achieved by the afferent arterioles which are vessels capable of adjusting diameter and so of determining blood delivery to the nephrons where the main renal functions take place. In order to regulate blood flow, afferent arterioles respond to signals initiated by two major mechanisms: tubuloglomerular feedback, and the myogenic response. My work focuses on the latter and involves the integration of cellular, vascular, and hemodynamical properties into multi-scale mathematical models that can be used to study the renal autoregulatory process.

Computational Fluid Dynamics: Many biological scenarios involve fluid motion in domains of complex geometry and deformable boundaries that commonly result in nontrivial fluid-structure interaction problems. My interest is on numerical methods capable of computing solutions to such problems.

Areas of Interest:

Biological Modeling
Renal Hemodynamics
Fluid Dynamics

Keywords:

renal autoregulation • myogenic response • afferent arteriole • hemodynamics • fluid-structure interactions

Curriculum Vitae

Undergraduate Research Supervised

• Justin Summerville (May, 2013 - June, 2013)  

Recent Publications   (More Publications)

1. Ioannis Sgouralis, and Anita T. Layton, Theoretical Assessment of Renal Autoregulatory Mechanisms, Am J Physiol Renal Physiol (Accepted, March, 2014)
2. Yi Li, Ioannis Sgouralis, and Anita T. Layton, Computing viscous flow in an elastic tube, Numer Math Theor Meth Appl (Accepted, 2014)
3. Brendan C. Fry, Aurelie Edward, Ioannis Sgouralis, and Anita T. Layton, Impact of renal medullary three-dimensional architecture on oxygen transport, Am J Physiol Renal Physiol (Submitted, 2014)
4. Ioannis Sgouralis, and Anita T. Layton, Control and modulation of fluid flow in the rat kidney, Bull Math Biol (2013) 75:2551-2574 (December, 2013) [doi]
5. Ioannis Sgouralis, and Anita T. Layton, Autoregulation and conduction of vasomotor responses in a mathematical model of the rat afferent arteriole, Am J Physiol Renal Physiol, vol. 303 (July, 2012), pp. F229-F239 [doi]

Selected Talks

1. A dynamical nephrovascular model of renal autoregulation, March, 2014, Ph.D. Defense Seminar    
2. Renal autoregulation in a dynamic nephrovascular model, November 1, 2013, Graduate/Faculty Seminar [mcal]    
3. A numerical method for solving the advection-diffusion equation in moving domains, April 12, 2013, Graduate/Faculty Seminar [mcal]    
4. How do you swim in reversible Stokes flow, October 26, 2011, Biofluids (Math 387) [available here]