Department of Mathematical Sciences Presentation�
December 5, 2024
Introducing NJIT
Introducing the Department of Mathematical Sciences (DMS)
MATHEMATICAL BIOLOGY
WAVE PROPAGATION
BIOSTATISTICS/APPLIED STATISTICS/ DATA SCIENCE
FLUID DYNAMICS
Introducing myself
�Welcome to the Department of Mathematical Sciences
In the Department of Mathematical Sciences we offer a vibrant environment with numerous courses and research exposure. With our variety of MS and PhD programs in applied mathematics, applied statistics, biostatistics, and data science, we present students with world-class educational opportunities. We are looking forward to welcoming you to our department!
Eliza Michalopoulou - DMS Chair
DMS conducts research in cutting-edge applied math sciences:
Why study at NJIT DMS?
Diverse Graduate Programs
NJIT Campus Tour
Wellness Center
Research & Graduate Life
current graduate students:
Our Faculty
Research Areas:�
Fluid Mechanics
Faculty in our department study fluids in physical and biological systems using a variety of numerical and analytical techniques
Dr. Shahriar Afkhami�
Scientific Computing applications in:
Fluid Dynamics, Machine/Deep Learning�
Flow in porous media:�
Nucleate boiling:
Machine Learning in drug targeting:
Dr. Wooyoung Choi�
Evolution of nonlinear water waves
Strongly nonlinear internal solitary waves
in density-stratified flows
Stability of nonlinear periodic waves and
nonlinear resonant wave interactions
Nonlinear Water Waves, Geophysical Fluid Dynamics, Scientific Computing
Dr. Linda Cummings�
Projects involve both analytical and numerical techniques, including asymptotic analysis, partial differential equations, complex analysis and graph-theoretic approaches.
Mathematical modeling of real-world systems arising in a range of industrial and biomedical applications, including:
Dr. Lou Kondic�
Fluid mechanics and soft matter:
computing, networks, topology, big data�
Interaction networks in particulate matter�
Fractal growth
Nanoscale fluid instabilities
See also cfsm.njit.edu
Dr. Enkeleida Lushi�
Research Topics: fluid-structure interactions, �swimmer locomotion and collective behavior, �active matter in complex confinement and flows.�
Potential projects can be tailored to the student’s strengths and interests, and involve mathematical modeling in collaboration with experimentalists, asymptotic analysis, high performance computation of the resulting PDE systems.
Dr. Anand Oza�
Mathematical modeling and physical applied mathematics, motivated by fluid dynamics and soft/active matter systems.
Flapping wings:
models for schools & flocks
Walking droplets:
hydrodynamic quantum analogues
Hydrophobic surfers:
wave-coupled active matter
Bursting bubbles:
free-streamline flow past an oil film
Dr. Xinyu Zhao�
Quasi-periodic water waves, hydrodynamic stability,
PDE-constrained optimization
Quasi-Periodic Water Waves
PDE-Constrained Optimization
Hydrodynamic Stability
Mathematical biology
Our faculty work in many areas of mathematical biology, including neural science, tissue engineering, and phylogenetics
Dr. Casey Diekman�
Mathematical modeling of biological oscillations; computational neuroscience; systems biology; data assimilation
Data-driven modeling of circadian clock neurons
Simulation of cardiac arrhythmias
Dr. James MacLaurin
Mathematical Biology, Statistical Mechanics, Stochastic Analysis, Large Deviations
Biological Pattern
Formation
Waves, patterns and oscillations in neuroscience
Emergent Dynamics in High Dimensional Disordered Landscapes
Dr. Victor Matveev
Cell biophysics (cell calcium dynamics, synaptic neurotransmitter release)
computational neuroscience, reaction-diffusion systems
Collaborative neuroscience research:
Study of calcium control of synaptic neurotransmitter release
Calcium-buffer reaction-diffusion system:
Lab: Dr. Ebenezer Yamoah (University of Nevada, Reno)
2. Synaptic vesicle fusion in retinal amacrine cells
Lab: Dr. Henrique von Gersdorff (Vollum Institute, Portland)
Software for modeling of cell calcium dynamics:
Dr. Kristina Wicke
Research Interests: Mathematical Phylogenetics, Graph Theory, Combinatorics, Algorithms.
Discordance between gene
and species trees
Wave Propagation
This includes electromagnetic waves (optics and radio frequency), fluid waves, cold atoms, underwater acoustics, and other mechanical systems.
Dr. Travis Askham�
Efficient and high-order methods for PDE problems in complex geometry
PDE eigenvalues and eigenfunctions:�
Fluid flow:
Tools
Other interests
Dr. Christina Frederick
Multiscale modeling for inverse problems, harmonic analysis, robotics
High-frequency
underwater acoustics
Sampling theory for multi-tiling frequency domains
Path-Planning for mobile sensors
Gabor analysis
Dr. Roy Goodman
Dynamical systems, Hamiltonian mechanics, nonlinear waves
Bifurcations and chaos in coupled optical waveguides
Instabilties of periodic vortex motions (Behring dissertation 2020)
Optimal control of cold atom clouds (Adriazola dissertation 2021)
Linear Ramp
Computed Control
Dr. Eliza Michalopoulou
Listening to the ocean: geoacoustic inversion using sound propagation
Dr. Thi Phong Nguyen�
Direct and Inverse electromagnetic scattering, imaging methods for shape reconstructions, regularization of ill-posed problems.
Regularization methods for FDEs
Imaging methods:
reconstruction of cracks
Inverse scattering for complex periodic media
Statistics and Data Science
Our faculty work in areas such as statistical genetics, survival analysis, spatial statistics, machine learning, deep learning, multiple testing, and clinical trials
Dr. Chong Jin�
Research interests: multi-omics data, statistical genetics, statistical genomics, Mendelian randomization, cancer genomics, RNA-seq methods, single-cell RNA-seq methods, and statistical learning.
Cell-type-specific differential expression analysis
Multi-omics Mendelian randomization
Dr. Ji Meng Loh�
Research interests: Spatial statistics and spatial point processes, including bootstrap, dimension reduction, and statistical learning.
Modeling EEG data using latent state space models
Stochastic gradient descent for spatial data
Dr. Chenlu Shi�
Research interests: experimental design, computer experiments, big data reduction and analysis, hyperparameter optimization for deep learning.
performance comparison with other designs
soa: an example of strong orthogonal arrays (a type of designs for computer experiments)
Utilize it to collect data from borehole function for building an emulator
�Dr. Sundar Subramanian
Research interests: Survival data analysis, Bootstrap, Non- and semi-parametric models, Efficient estimation, Model checks and dimension reduction for location-scale, Empirical likelihood, Empirical processes, Large sample theory, Probability, Stochastic Processes
Bootstrap likelihood ratio simultaneous confidence bands for survival functions from twice censored data.
Model checks founded on empirical likelihood (EL) and the empirical characteristic function (ECF).
Empirical coverage probabilities (ECPs) of bootstrap likelihood ratio simultaneous confidence bands for survival functions from twice censored data. LCR is left censoring rate. RCR is right censoring rate.
Positions
Places
Academia, Government, Companies:
Alumni:
According to U.S. Bureau of Labor:
Employment in math occupations is projected to grow 27 percent from 2019 to 2029,
much faster than the average for all occupations. Growth is anticipated as businesses and
government agencies continue to emphasize the use of big data, which math occupations analyze.
Bachelor’s Degree Level: $77,266
Master’s Degree Level: $81,468
PhD Degree Level: $101,182
Graduate Admission
https://www.njit.edu/apply-now
PhD programs
Masters programs
Recommendation letters
Statement of purpose (Ph.D.)
Do we offer financial support? Yes
| Do we offer financial support? No |
Recommendation letters
Number of full-time students receiving support: 42 | |
Enrollments | |
Full-time | 39 |
Full-time women | 11 |
First year | 8 |
First year women | 2 |
Part-time | 1 |
Enrollments | |
Full-time | 33 |
Full-time women | 13 |
First year | 24 |
First year women | 11 |
Part-time | 22 |
Life in the NJIT DMS