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| Category | Technologies |
|---|---|
| Languages |             |
| UX/UI |     |
| Tools |                      |
| Database, Virtualizing/Hosting, & Remote Pipelines |          |
| Command Line |    |
| Framework |        |
| IDE |      |
| OS |        |
- Development of tools to automate vulnerability scanning, intrusion detection, and endpoint security.
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Capabilities:
- Network monitoring, anomaly detection, and secure access control using Python, Bash, and PowerShell.
- Integration with libraries such as nmap, Wireshark, Metasploit, and Scapy for automated incident response.
- Task automation for regular security audits, secure software deployment, and penetration testing using **Ansible** and **Terraform**.
- Optimization of large codebases for faster, parallel execution.
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Capabilities:
- Threading, Multiprocessing, and CUDA for GPU acceleration in Python, C++, and C.
- Refactoring to improve runtime efficiency, memory usage, and system stability.
- Utilization of multi-core CPU and GPU processing to improve real-time performance across distributed systems.
- Scripts to automate software installation and system configuration using package managers like
winget,nuget, andchoco. - Focused on ensuring secure and efficient deployment environments for both personal and professional use.
- Custom-designed interfaces for user-friendly applications in healthcare, research, and data visualization.
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Capabilities:
- Development of responsive web applications using HTML, CSS, and JavaScript.
- Integration with Bootstrap, React, and Vue.js for enhanced interactivity and data visualization.
- Focus on accessibility and usability, ensuring high-quality UX for end-users.
- Automation scripts for repetitive workflows across research and development environments.
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Capabilities:
- Automated data collection, cleaning, analysis, and reporting using Python and Bash.
- Workflow automation in clinical and lab settings, integrating multiple software tools like Excel, Access, and PowerShell.
- Tools for scheduling, file management, and communication across distributed teams using Zapier and IFTTT.
- Development of statistical tools for deep analysis and hypothesis testing.
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Capabilities:
- Use of Linear Mixed Models, Generalized Linear Models, and Bayesian Inference to explore complex datasets.
- Time series analysis, survival models, and cross-sectional study analysis using statsmodels, SciPy, and R.
- Custom-built tools for regression, residual diagnostics, and sensitivity analysis.
- Creation of comprehensive visualizations for data-driven decision-making.
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Capabilities:
- Development of dashboards and visual tools using matplotlib, seaborn, and Plotly for interactive graphics.
- Statistical plotting for multi-dimensional data, including heatmaps, spider plots, and time-based visualizations.
- Use of parallel computing techniques to solve large-scale computational problems.
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Capabilities:
- Efficiently running processes across multiple CPU/GPU cores using OpenMP, CUDA, and MPI.
- Code optimization for distributed systems, focusing on reducing computation time and memory overhead.
- Utilization of libraries like Dask and Ray for parallel processing in Python.
- Development of algorithms for solving complex optimization problems in engineering and physics.
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Capabilities:
- Use of gradient descent, simulated annealing, and other optimization techniques for large-scale data problems.
- Application of optimization libraries like SciPy and Cvxpy to solve real-world problems in machine learning, physics, and economics.