Software Suite

Welcome to my toolkit! Over the years, I’ve fine-tuned my workflow using a range of software. This page provides insight into the tools that power my projects, tasks, and daily routines.
Last updated

26 November 2025

In the digital age where tools define the craftsman, my software ecosystem reflects my research journey, workflow preferences, and commitment to reproducible, high-quality work. This page presents a carefully curated suite of tools that empower my research in machine learning, academic writing, data analysis, content creation, and automation.

Machine Learning & AI Development

My machine learning workflow is built on reliable frameworks, configuration tools, and interactive environments that support both rapid experimentation and long-running research projects.

Deep Learning Frameworks

  • PyTorch — Primary deep learning library for building and training neural networks.
  • TensorFlow — Alternative ML framework for selected projects and comparisons.
  • PyTorch Lightning — High-level training framework for clean, modular, and scalable experiments.
  • Hugging Face Transformers — Library for state-of-the-art transformer-based NLP models.

Python Ecosystem

  • Python 3.x — Core programming language for ML, automation, and scripting.
  • Jupyter Notebook — Interactive environment for experimentation and visual debugging.
  • Google Colab — GPU-enabled cloud notebooks for resource-intensive experiments.

Configuration & Versioning

  • Hydra — Flexible configuration system for structured experiment management.
  • Data Version Control (DVC) — Version control for datasets, models, and ML pipelines.
  • TensorBoard — Visualization of learning curves, metrics, and model graphs.

Development Environment

A productive development environment is essential for maintaining clean code, reproducible projects, and smooth cross-platform workflows.

Code Editors & IDEs

  • Visual Studio Code (VS Code) — Primary IDE for Python, R, Quarto, and web development.
  • RStudio — Integrated development environment for R and R Markdown.
  • Doom Emacs — Highly customizable text editing environment for advanced workflows.
  • Notepad++ — Lightweight editor for quick edits on Windows.

Environment Management

  • Conda / Micromamba — Environment and package management for data science and ML.
  • Lightning-Hydra Template — Opinionated ML project template combining PyTorch Lightning, Hydra, and best practices.

Terminal & Shell

  • Windows Terminal — Modern and customizable terminal host on Windows.
  • PowerShell — Scripting and automation shell for system tasks.
  • WSL2 (Ubuntu) — Full Linux environment inside Windows for development and HPC access.

Research & Academic Writing

Research productivity depends on well-integrated tools for literature management, document preparation, and long-form writing across thesis work, articles, and talks.

Literature Management

Document Preparation

  • Quarto — Primary tool for reproducible reports, presentations, and thesis chapters.
  • LaTeX — Typesetting engine for professional-quality academic documents.
  • Pandoc — Document conversion backbone integrated with Quarto and R Markdown.
  • Markdown — Lightweight markup language for everyday writing.
  • TinyTeX — Minimal TeX distribution optimized for Quarto and R Markdown workflows.

Writing Tools

  • VS Code — Central editor for Quarto, Markdown, and LaTeX content.
  • Obsidian — Knowledge management system for research notes and ideas.

Diagramming & Graphics

  • TikZ/PGF — LaTeX-based diagrams for publication-quality figures.
  • Mermaid.js — Text-based diagrams embedded within Markdown and Quarto documents.
  • Draw.io (diagrams.net) — Browser-based diagramming for flowcharts and conceptual diagrams.
  • Inkscape — Vector graphics editor for technical illustrations and figures.

Statistical Computing with R

R plays a key role in my workflow for statistical analysis, reproducible reports, and structured automation around CVs and literature reviews.

Core R Tools

  • R — Language and environment for statistical computing and graphics.
  • tidyverse — Collection of packages for data manipulation and visualization.
  • rmarkdown — Dynamic documents combining code, output, and narrative.
  • pagedown — HTML-based paged documents, including academic CVs.

Use Cases

  • Automation for systematic literature review (SLR) tables and summaries.
  • CV generation via an Excel → R → pagedown pipeline.
  • Statistical analysis, exploratory data analysis, and visualization.

Data Visualization & Graphics

Effective visualization is essential for interpreting models, communicating results, and producing publication-ready figures.

Data Visualization

  • Matplotlib — Foundation for static and custom plots in Python.
  • Seaborn — High-level interface for statistical graphics in Python.
  • ggplot2 — Grammar of graphics for expressive plots in R.
  • Plotly — Interactive plots and dashboards in Python and R.
  • Tableau — Visual analytics and business intelligence dashboards.

Image & Design Tools

  • GIMP — Open-source raster graphics editor for image editing.
  • LibreOffice Draw — Quick diagrams and illustrations.
  • Microsoft PowerPoint — Slides and visual content creation for teaching and talks.

High-Performance Computing

For large-scale experiments and model training, I rely on HPC clusters and monitoring tools to manage and track compute usage.

Cluster Computing

  • PBS Job Scheduler — Submitting and managing batch jobs on HPC clusters using commands such as qsub and qstat.
  • SSH / SCP — Secure remote access and file transfer to and from servers and clusters.

Monitoring Tools

  • htop — Real-time system and process monitoring in the terminal.
  • nvidia-smi — GPU monitoring and diagnostics for NVIDIA devices.

Version Control & DevOps

Version control, collaboration, and automation are central to maintaining clean, reproducible research codebases and websites.

Version Control & CI/CD

  • Git — Distributed version control system used across all projects.
  • GitHub — Code hosting, issue tracking, and collaboration platform.
  • GitHub Actions — CI/CD pipelines for testing, building, and deploying (including Quarto websites).
  • Data Version Control (DVC) — Versioning for datasets, trained models, and experiment pipelines.

Productivity & System Management

Good tooling for system management and productivity helps keep environments consistent and workflows efficient across machines.

System Management

Productivity Tools

  • Raindrop.io — Bookmark and resource management for web content and references.
  • Microsoft Edge — Primary web browser.
  • Espanso — Text expansion to speed up repetitive typing.
  • Slack / Microsoft Teams — Communication platforms for academic and collaborative work.

Cloud Storage

  • Google Drive — Cloud storage for backup, collaboration, and syncing across devices.

Content Creation & Outreach

Content creation is an important part of sharing research, teaching concepts, and building outreach through platforms like YouTube.

Video Production

  • OBS Studio — Screen recording and live streaming for tutorials and talks.
  • Shotcut — Open-source video editor for assembling and editing recordings.
  • YouTube Studio — Channel and content management for my ResearchInfuser YouTube channel.

Office Suites

A combination of open-source and proprietary office tools supports teaching, documentation, and administrative work.

Office Productivity

Automation & Scripting

Automation reduces repetitive work and keeps my workflows consistent, especially for documents, timetables, and websites.

Automation & Web Scripting

  • Google Apps Script — Automation for Google Workspace, including timetable generation and form processing.
  • Excel → R → pagedown pipeline — Automated generation of a structured academic CV from tabular data.
  • HTML / CSS / JavaScript — Web content customization, small utilities, and UI enhancements.

Open Source Projects

I maintain and contribute to open-source projects that support academic writing and reproducible research, especially in the context of MANIT thesis workflows.

Quarto Extensions

MANIT Thesis Quarto Extension (manit-thesis)

A Quarto extension for fully reproducible MANIT-style thesis formatting, providing a LaTeX-based template integrated with Quarto and Pandoc workflows.

MANIT Pre-Thesis Quarto Extension (manit-pre-thesis)

A Quarto template designed for MANIT-compliant pre-thesis submissions, with automated LaTeX styling and structured sections.

Hardware

I primarily work on a 15″ Dell Alienware M15 R6 equipped with an 11th generation Intel® Core™ i7, 16 GB DDR4 RAM, and an NVIDIA® GeForce RTX™ 3070 (8 GB) GPU. This setup provides a strong balance between development responsiveness, deep learning experimentation, and content creation.