I will join Smita Krishnaswamy's Lab at Yale University, as a Postdoc.

I completed my PhD in the Department of Computer Science at University of Maryland, College Park. My research advisor and mentor at UMD was Professor Dianne P. O'Leary. My main research interests are*,*

__scientific computing__*, and solving hard*

__machine learning__*.*

__optimization problems__
For my dissertation, I have been working on __interpretation of neural networks and application of homotopy methods__.
We developed mathematical methods to study trained neural networks as
nonlinear functions, __interpret their behavior__, study their __decision boundaries__,
and to __improve and debug them__. Our research has implications for __adversarial robustness__
of deep learning models and their __generalization error__, too.
We also developed methods to refine the structure of trained networks using matrix
conditioning.

Last summer, I was at the Los Alamos
National Laboratory for their Applied Machine Learning
Fellowship. I finished a project about interpretation of Gaussian graphical models
for unsupervised learning of data gathered by the
Mars rover. It is published in the proceedings of a SIAM conference.

I like to solve challenging optimization problems in different contexts.
I am comfortable with nonlinear optimization problems, integer programming and
linear programming. During my coursework, I took __Scientific Computing I and II__,
__Nonlinear Optimization II__, __Integer Programming__,
__Sparsity and Machine Learning__, __Machine Learning__, __High Performance Computing__, and several other courses.

I have worked on __real-time optimization problems__ in Humanitarian Aid delivery systems and Freight transportation systems.
We developed a probabilistic framework to optimize the decisions. Our formulation is
nonlinear and non-convex, and we designed a __homotopy algorithm__ to
solve it in real-time.

In Fall 2018, I received the Graduate
School's Outstanding Teaching Assistant Award. That semester, I was a TA for the
course CMSC460 "Computational Methods".

I am also a licensed structural engineer in Maryland. Before studying computer science,
I was a structural design engineer.

Here is a list of papers that I have worked on:

- Interpreting Neural Networks Using Flip Points
- Debugging Trained Machine Learning Models Using Flip Points
- Learning Diverse Gaussian Graphical Models and Interpreting Edges
- Investigating Decision Boundaries of Trained Neural Networks
- Refining the Structure of Neural Networks Using Matrix Conditioning
- Optimizing Real-time Decisions in Hierarchical Humanitarian Aid Delivery Systems
- A Probabilistic Framework and a Homotopy Method for Real-time Hierarchical Freight Dispatch Decisions