Office: Ross S625

Department of Mathematics and Statistics

York University/Fields Institute, ON

Phone: # 416-400-8802

Email: qmwang at yorku dot ca

- BS in Mathematics, Nanjing University, China 2005
- MS in Mathematical Sciences, NJIT, USA 2009

- PhD in Applied Mathematics (thesis advisor:
Demetrios T. Papageorgiou), NJIT USA 2010

**Researcher:**- Reseacher at Fields Institute, Toronto, Canada 2015 (Data
analysis, Scientific computing, Mathbiology, Applied
Physiology, Fluid Mechanics)

- Postdoc fellow 2013- 2015 York University, Canada (fetal circulation, impact of hypoxia and asphyxia, asymptotic analysis on PNP, film coating with heat source)
- Postdoc fellow 2011- 2013 UBC, Canada (morphogenesis, dorsal closure, cell intercalation in apical constriction, SPH simulation)
- Research Associate 2010 - 2011 NJIT, USA (dynamics of liquid threads, soluble surfactant covered bubble or drop, boundary integral simulation, fast matrix decomposition)
**Teaching**

- Ordinary differential equations instructor Spring 2011 NJIT
- Calculus Spring 2012, Advanced linear algebra Spring 2013 UBC
- Symbolic computation lab I M2041 Fall, 2013, 2014 YU
- Mathematical Modelling M4090 2014 YU
- Calculus 1310 2015 Winter York University
- Mathematical Modeling M6931 (graduate),
2015 Fall YU

- Journal reviewer:
*JFM, Phys.Fluids,**SIAM J. App Math,**Int. J. Heat & Mass transfer,**Int. J. Num. Methods in Biomed. Eng.*

- Conference/Meeting organized:
*Neurovascular coupling and related phenomena*, Fields Institute, July 2014

- Randomized matrix decomposition algorithm

- Non-uniform FFT in 1D (fast algorithm)
- Mathematical Modeling on applied physiology problem (fetal
sheep)

- dealing with heart rate, arterial blood pressure, EEG and
ECoG data

- sensitivity analysis on the parameters rising from a large
system of ODEs

__Big Data industrial workshop at Fields Institute__(May 25-30, 2015)- TMX problem on investigating volatility and liquidity of the stock market:
- both OTC and TSX data are given (but in different format
as they are recorded from two different systems)

- daily transaction data ~ 10^7 and data is given in locked
strings in text files (we have to decode them first)!

- data are given for all stocks over years (in workshop with 3 working days we managed to analyze data for 3 months)
- 6-month project with TMX continuing the work from the workshop
(Oct 2015-Mar 2016)

- Investigating multiple stocks over months and years to probe the relationship between market liquidity and trade volume and other factors
- To apply fast algorithm on statistical and machine learning
models (based on work of L. Greengard and his collaborators)

- Solid background in general applied mathematics, numerical computations, statistical modeling, machine learning algorithms and data analysis
- Extensive research experience in mathematical modeling and analysis, numerical simulations and scientific computing in the field of fluid mechanics, electrohydrodynamics, cell mechanics and applied physiology
- Programing experiences in Matlab, Fortran, C/C++, Maple and Python (in particular, Python-pandas for data analysis, Python-sklearn for machine learning) and familiar with SQL, R, MS Office, Latex
- Fast learner and good at team work; excellent skills in
problem solving, communication and presentation skills

- Theoretical and Computational Fluid Mechanics, Biofluids;
- Free Boundary Problems, Multiphase Flows, Stability Theory, Wave Propagation;
- Asymptotic, Perturbation Methods
- Computational Methods (boundary integral, immersed boundary, pseudospectral, e.g.) and Scientific computing (tree code, basic fast multipole, nonuniform FFT, compression of low rank matrices)
- Big Data and machine learning