From long runs to code sprints
As a former runner, I relentlessly pursue my goals. My finish line isn't a medal, it's a solution. My experiments aren't for headlines, but a better tomorrow. I want to fill the cracks in the world rather than widen them.
I like to craft sustainable solutions tailored to specific challenges. Explore my snippets and mini-projects that serve as components of sustainable solutions.
Web/App Development
I craft dynamic web experiences from the ground up using Python, PHP, and Java to sculpt robust backends. I use ReactJS and AngularJS to build apps that work even when the wifi doesn’t.
Data Analysis
I translate data into data-driven intelligence. Python helps me create wrangle complex datasets and create anomaly detectors and personalized recommendations systems, while ReactJS visualizes my creations.
Machine Learning
I bring languages and visions to life – building and deploying Natural Language Processing and Computer Vision models used in real-world applications. My toolkit includes crafting tailored loss functions like hierarchical cross-entropy for nuanced learning and classification.
Mechanism Design
I craft economic mechanisms that align individual actions with collective goals, like efficient markets or sustainable resource use. Think puzzles with purpose, building systems that guide behavior without coercion.
Operations Research
Unraveling the tangled threads of resource allocation through operations research, I wield linear and combinatorial tools to sculpt streamlined, cost-optimal solutions.
System Architecture/Design
I architect resilient, scalable systems using Docker orchestration, microservices via REST APIs, and Gitlab CI/CD pipelines for robust development - I build the foundation for smooth, high-traffic experiences.
My blog offers a glimpse into my mind, where I explore messy, real-world problems problems and their solutions. I look into sustainable solutions, impact-driven design, and practical approaches that go beyond the next shiny trend.
Fair Division of Goods: Sophisticated Mechanisms and Synthesis
Synthesizing fair division theory into practice - frameworks for algorithm selection, multi-objective optimization, and real-world applications from classrooms to welfare systems
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Fair Division of Goods: Optimizing for Social Welfare
Part 4 explores the shift from individual fairness to collective welfare in allocation problems. How utilitarian, Nash, and maximin welfare functions embody different philosophical commitments about efficiency versus equity, and when to prioritize the group over the individual.
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Fair Division of Goods: The Indivisibility Challenge
Part 3 explores why perfect fairness becomes impossible with indivisible goods like houses and watches, and how relaxed fairness notions (EF1, MMS) and simple algorithms (round-robin) provide practical solutions when theoretical perfection is unattainable.
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Fair Division of Goods: Cake Cutting
Part 2 explores cake-cutting algorithms for divisible goods, establishing theoretical foundations before confronting the harsh reality that most real-world problems involve indivisible items where perfect fairness often becomes impossible.
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Balancing LLM Prompt Analytics and User Privacy
Learn how to implement effective prompt analytics for large language models while safeguarding user privacy. Discover key strategies, best practices, and ethical considerations in this guide.
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Neural Variational Document Models with PyTorch for Topic Extraction
Discover how Neural Variational Document Models, implemented using PyTorch, improve topic modeling and unsupervised learning in natural language processing. Learn about the architecture, training process, and applications of these latent variable models for text analysis and beyond.
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