Senior AI Scientist2018 - 2020Analytics 4 Life
Technologies: Amazon Web Services (AWS), Docker, Keras, TensorFlow, AWS, MATLAB, Python, C++
- Developed an ML app that predicts cardiac diseases using non-invasively acquired data leading to pending US/international patents.
- Led a project to develop a protocol for patient data collection and automated quality assessment, reduced retrial efforts, and cost.
- Developed an ML-based anomaly detection algorithm for ECG and PPG signals: design of experiment, statistical analysis, ML model training and deployment, and automated reports.
- Improved inference performance of production ML model deployed on AWS by 60%: parallelization and algorithmic improvements.
- Led projects on feature engineering, model selection, and robustness analysis: data collection, quality assessment, feature engineering, model selection, deployment, and performance monitoring.
- Developed a deep learning-based app to predict the respiration information and waveform form the cardiac and blood volume data (ECG and PPG): providing a valuable health marker for disease prediction.
- Established effective communication with other teams (systems, QA, hardware, clinical), development in close liaison with cardiologists, clinical staff, and end-users.
- Prepared detailed technical reports for FDA submission; prepared marketing presentations; presented results to executives, investors, and partners; and authored the scientific manuscript.
- Conducted code reviews, involved in the hiring process, and trained junior data scientists and interns.
Senior Research Scientist, HPC Software Developer2015 - 2018Hexagon Manufacturing Intelligence
Technologies: TFS, GPGPU, MPI, OpenMP, UML, Python, C++
- Developed ML models to replace heavy simulations for the design and optimization of auto parts, a fast tool for the initial design and prototyping phase.
- Developed a high performance parallel linear system solver leading to 1,000 times speed-up: sparse direct solvers and iterative solvers (PCG, Algebraic multigrid).
- Developed a sparse/dense linear algebra library in C++, scientific code design, and optimization.
- Developed a tool for the probabilistic analysis of uncertainty propagation from input materials to the final product.
- Created mathematical, statistical, and numerical models for the simulation of sheet metal processes: differential equations, finite element method, and visualization.
- Authored, published, and presented a paper on probabilistic analysis of spring back phenomenon in the Institute of Physics (IOP) conference series.
- Utilized supervised and clustering ML techniques, design of experiments, Monte-Carlo simulation, and HPC.
Research Scientist2014 - 2015Alstom Power
Technologies: Models, Finite Element Method (FEM), Nastran, ANSYS, MATLAB, Python
- Developed a semi-analytical software tool and pipeline for improving the performance of old hydraulic turbines, thereby avoiding significant replacement cost.
- Developed a tool for predicting what parameters and loads (fluid dynamic forces and conditions) lead to a dangerous structural response (e.h. catastrophe vibrations).
- Designed and implemented an experimental setup for validating the results of the simulation tool.
- Prepared documentation and design guidelines, presented results, and published internal white paper.
Research Scientist2013 - 2014Bombardier Aerospace
Technologies: Finite Element Analysis (FEA), SOLIDWORKS, ANSYS, Python, MATLAB
- Developed a fast predictive software tool for designing fuselage components with lower weights and yet stable under the loads, reducing the initial design and prototyping cost.
- Developed design guidelines and design charts for various loads and geometries, resulting in a 10% weight reduction in the initial phase of the design.
- Developed mathematical and numerical models for the post-instability behavior of the fuselage component.
- Supervised and trained applications engineer on how to utilize the developed tool and guideline.
PhD Researcher2008 - 2013McGill University
Technologies: Bash, Linux, MPI, OpenMP, Python, Fortran, C++
- Studied and developed mathematical models for predicting the behavior of complex nonlinear systems: fluid-structure interaction, cardiovascular fibrillation, weather forecast, etc.
- Developed a high-performance numerical software tool for solving the nonlinear differential equations of the complex systems (airplane wing).
- Developed a pipeline to compile and deploy the program on a super-computing cluster (Mammoth), request shared (OpenMP) and distributed memory (MPI) resources, and collecting and analyzing Terabyte results.
- Designed and performed experiments on the nonlinear and chaotic response of elastic shell conveying fluid (artery conveying blood), and validated the results of the software tool.
- Developed machine learning meta models for forecasting the behavior of the complex systems without running heavy simulations.
- Taught courses on numerical methods, computer programming, mathematical modeling. Published and presented results in various journals and conferences.
- Utilized C++, Fortran, Python, distributed computing, OpenMP, MPI, statistical data analysis, stochastic signal processing, and experimental design.