- Detect and mitigate DDoS attacks to millions of AWS resources with low latency by processing TB/s data stream of user requests, via anomaly detection and feature engineering- Develop tools and metrics to assess efficacy, data analysis, and data labeling of PB’s of traffic data- Actively participated in on-call rotation, DevOps, minimizing the risk of downtime of essential AWS service- Utilized Concepts: cloud computing, data-streaming, anomaly detection, feature engineering, cyber… Show more - Detect and mitigate DDoS attacks to millions of AWS resources with low latency by processing TB/s data stream of user requests, via anomaly detection and feature engineering- Develop tools and metrics to assess efficacy, data analysis, and data labeling of PB’s of traffic data- Actively participated in on-call rotation, DevOps, minimizing the risk of downtime of essential AWS service- Utilized Concepts: cloud computing, data-streaming, anomaly detection, feature engineering, cyber security, data engineering, asynchronous stream processing, effect programming- Utilized Skills: Java, scala, rust, typescript, ruby, AWS Show less

- Discovered novel applications of machine learning, numerical optimization, and graph algorithms to solve various problems in quantum chemistry and theoretical physics- Drastically reduced computation time for molecular HPC simulations by foundational improvements to algorithms, and embarrassingly parallelizing across multiple distributed GPUs- Designed recommendation system and clustering algorithms for binary data (e.g. molecular fingerprints) and categorical data (e.g. DNA/protein… Show more - Discovered novel applications of machine learning, numerical optimization, and graph algorithms to solve various problems in quantum chemistry and theoretical physics- Drastically reduced computation time for molecular HPC simulations by foundational improvements to algorithms, and embarrassingly parallelizing across multiple distributed GPUs- Designed recommendation system and clustering algorithms for binary data (e.g. molecular fingerprints) and categorical data (e.g. DNA/protein sequences) analogous to natural language processing improving algorithmic complexity from quadratic to linear (i.e. order of 1M+ improvement for a large database) - Managed a molecular database utilizing clustering algorithms and SQL- Utilized Concepts: Numerical Optimization, Graph Theory, Machine Learning, Clustering Algorithm, High-Performance Computing, High-Dimensional Tensors, GPU Programming, Recommendation Engine - Utilized Skills: Scientific Modeling, Python, Cython, C++, Linux, CUDA, SQL Show less

- Lead projects of interdisciplinary teams, remote and on-site, to design and develop 7+ open-source Python libraries for the quantum chemistry, theoretical physics, mathematics, and cheminformatics community- Built a database of Terabytes of quantum chemistry calculations by automating data acquisition, cleaning, data analysis and visualization on high-performance computing (HPC) servers using SQL, hdf5, and PyTables- Design, develop, document, test, maintain, and deploy open-source… Show more - Lead projects of interdisciplinary teams, remote and on-site, to design and develop 7+ open-source Python libraries for the quantum chemistry, theoretical physics, mathematics, and cheminformatics community- Built a database of Terabytes of quantum chemistry calculations by automating data acquisition, cleaning, data analysis and visualization on high-performance computing (HPC) servers using SQL, hdf5, and PyTables- Design, develop, document, test, maintain, and deploy open-source libraries via DevOps and SDLC protocols (e.g. setup Travis CI and GitHub Actions, implement and integrate QA scripts into CI system, standardized build across Windows, macOS and Linux, deploy via conda, pypi, dnf, apt, homebrew, docker, and kubernetes)- Trained new developers in Python and modern development practices (e.g. git, Agile, unit testing, DevOps)- Presented at and moderated conferences, workshops, and hackathons to provide technical support and to train participants in maintainable development practices (e.g. version control, unit testing, QA, CI)- Utilized: Python, Object Oriented Programming, HPC, SQL, git, DevOps, Continuous Integration, Continuous Deployment, Unit Testing, Docker, Linux, Code Review, Project Management, Agile, Scrum, Kanban, Trello Show less

- Taught undergraduate and graduate students by leading tutorials, lectures, and labs- Topics: Quantum Mechanics, Programming, Thermodynamics, Linear Algebra, Calculus, Chemistry

- Designed and developed state-of-the-art wavefunctions and other quantum chemistry methods by leveraging knowledge in machine learning, deep learning, numerical optimization, regression, dimensionality reduction, and natural language processing by using Python, Cython, C++, NumPy, pandas, scikit-learn, and TensorFlow- Communicated scientific and technical information to general audience by presenting at conferences and workshops, writing grants, and collaborating with scientists from… Show more - Designed and developed state-of-the-art wavefunctions and other quantum chemistry methods by leveraging knowledge in machine learning, deep learning, numerical optimization, regression, dimensionality reduction, and natural language processing by using Python, Cython, C++, NumPy, pandas, scikit-learn, and TensorFlow- Communicated scientific and technical information to general audience by presenting at conferences and workshops, writing grants, and collaborating with scientists from around the world- Proven track record of independent scientific research with 20+ peer-reviewed publications, software releases, presentations at international conferences and workshops, received 50k+ in grants, and made direct contributions to receiving $500k+ in funding- Utilized: Scientific Modeling, Numerical Optimization, Graph Theory, Neural Network, Machine Learning, Data Science, Data Analysis, Data Visualization, Jupyter, Google Colab, LaTeX, Python, Cython, C++ Show less

- Attended IPAM's long program, Science at Extreme Scales - a collection of workshops to apply High-Performance Computing and Big Data Machine Learning to solve scientific problems - Investigated the applications of machine learning algorithms to solve the Schrodinger equation and wavefunction analysis tools to interpret neural networks