Qiming Wang
Contact Information
Office: Ross S625
Department of Mathematics and Statistics
York University/Fields Institute, ON
Phone: # 416-400-8802
Email: qmwang at yorku dot ca
Education
- 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
Academic Experience
- 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
Big Data experience
- 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)
Skills
- 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
Research Interests
- 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
ongoing
project
Publications
Activities