Ashay Kushwaha — Systems Builder
SYSTEMS
RESEARCH
OPEN
IMPACT
Ashay Kushwaha — Systems Builder

I build systems
that make complexity usable.

나는 센티넬 사이퍼다.
A CURIOUS MIND
WITH THE DISCIPLINE
TO TURN IDEAS
INTO REALITY.

Data meets impact.

I engineer open-source systems that turn raw data into decisions — NGO-volunteer matching platforms, climate policy dashboards, causal inference engines, real-time sentiment pipelines. Each project starts with a question and ends with a tool anyone can use.

29
Open Source Projects
68
PR Contributions
50
PRs Merged
Why I Build

I believe the best tools should belong to everyone. Not locked behind paywalls. Not hidden in proprietary systems. Open-source is how we democratize the best tools — and that's exactly what I build.

My work spans cybersecurity risk analysis, climate policy visualization, causal inference, and social impact platforms. The common thread: taking complex data and making it actionable for the people who need it most.

What I bring
Full-stack data engineering — Python to ReactML & causal inference for real-world problemsOpen-source as an ethos, not an afterthoughtClean architecture, reproducible results
Interests
Cybersecurity AnalyticsClimate TechCausal InferenceDeveloper ToolingOpen-Source EcosystemsSocial Impact

Tools of the trade.

The instruments behind the systems — no percentages, just proof.

Languages
Python
Data, ML, automation
Python
TypeScript
Frontend & tooling
TypeScript
SQL
Analytics & PostGIS
SQL
Frameworks
React
Interactive dashboards & PWAs
React
FastAPI
High-performance APIs
FastAPI
Streamlit
Rapid data apps
Streamlit
Node.js
Backend services
Node.js
Data & AI
XGBoost
Risk scoring & prediction
XGBoost
Gemini
Content analysis & generation
Gemini
VADER
Sentiment analysis
VADER
Causal Inference
Time series & treatment effects
Causal Inference
Infrastructure
PostGIS
Spatial queries & mapping
PostGIS
PWA
Offline-first web apps
PWA
REST APIs
API design & integration
REST APIs
Docker
Containerized deployments
Docker

Systems that solve real problems.

Open-source, MIT-licensed. Each project ships as a complete, production-ready tool — not a demo.

NSE Sentiment Analyzer

Live NSE price + multi-source sentiment

Enter any NSE ticker for a BULLISH / NEUTRAL / BEARISH signal: smart ticker search (504 aliases, handles rebrands and splits), 9-source news sentiment with event-aware scoring across 19 event types, a SmartScore 0-100 fusing recency-weighted EWMA, headline breadth and news volume, enhanced VADER plus a 123-term Indian financial lexicon, and RSI(14)/MACD technicals. 139 tests, AGPL v3.

StreamlitPythonNLPFinance
View on GitHub
React

KarmaMap

Hyper-local NGO-volunteer matching platform

Production-grade PWA connecting NGOs with nearby volunteers. PostGIS proximity matching scored by skill and road distance (OSRM), role-based dashboards for volunteers/NGOs/corporates, a karma points + streaks incentive system with leaderboard, offline-ready installable PWA, and Supabase Row-Level Security. React + Vite frontend on Vercel, Express backend on Render.

ReactPostGISSupabasePWATypeScript
Streamlit

NSE Portfolio Risk Scanner

Institutional-grade risk analytics for NSE

Upload a holdings CSV (or try the sample) for a full risk report: Historical, Parametric and Cornish-Fisher VaR at 95/99, CVaR, Sharpe and Sortino, beta vs Nifty, 10,000-path Monte Carlo, HMM regime detection, Hierarchical Risk Parity optimization and scenario stress tests. 355 tests, 90 percent coverage, zero API keys. Deployed on Streamlit Cloud.

StreamlitPythonRisk Analytics
Streamlit

FII/DII Dashboard

Institutional flow tracking from NSE India

Auto-fetches daily FII/DII flows from NSE India into SQLite; 4 interactive charts (net flow trend, FII vs DII, rolling averages, Nifty overlay), date-range filtering and CSV export. Premium UI with Lucide icons, zero cron, no API keys. 49 tests, AGPL v3.

StreamlitPythonnsepython
Streamlit

DeltaGrid

Paris Agreement NDC progress tracker

Computes the gap between Paris Agreement NDC pledges and actual energy-transition trajectories for 200+ countries. A 0-100 Green Score from 6 energy shares, real-time slider re-ranking, Plotly choropleth maps, CSV/XLSX upload with auto-preprocessing, and country classification (hidden champions to laggards). 123 tests, MIT.

StreamlitPythonClimate
Streamlit

CausalLens

Causal inference for time series

Did that policy work? Five causal methods — ARIMA ITS, SARIMAX, Bayesian STS (Google CausalImpact), Difference-in-Differences, and Synthetic Control — with counterfactual charts, p-values, 95 percent CIs, placebo sensitivity checks, and PDF/HTML export. 207 tests, 11 pre-loaded datasets, MIT.

StreamlitPythonCausal Inference

Let's build something together.

Open to collaborations, research partnerships, and conversations at the intersection of data, security, and social impact.

Find me online.

All my work is open-source and MIT-licensed. I'm most active on GitHub and LinkedIn.

GitHubXLinkedInMedium
Let's talk.

Interesting project, research collab, or just want to geek out about causal inference? I'm here for it.

Connect on LinkedIn