┌─[samridhi@github]─[~]
└──╼ whoami> Computer Science student at JIIT Noida
> Building at the intersection of security, systems, and AI
> Passionate about understanding how things break — and how to fix them
> Currently learning: Binary Exploitation · Network Security · ML with Python
> Open to: Internships · Collaborations · Open Source
🌐 Portfolio: samridhi-kulshrestha-portfolio.vercel.app
I'm a CS undergrad who started with competitive programming, got pulled into cybersecurity, and never looked back. I like systems-level thinking — which is why C++ and Python feel like home. DSA isn't just exam prep for me; it's how I think about designing efficient solutions (ask DRAS).
When I'm not coding, I'm breaking things ethically in CTFs or reading about how the next zero-day got discovered.
🚨 DRAS 2.0 — Emergency Management & Response Gateway
A live, deployed system that computes optimal rescue routes across 7 UP cities during multi-incident emergencies — built as a full DSA showcase.
The problem: When disaster strikes, emergency responders need the fastest route — not just the shortest. They also need to know which hospitals might become isolated (articulation points), where hazards are highest, and how to visit every relief centre efficiently.
What it does:
- Plots hospitals, relief centres, and live disaster risk zones (earthquake, storm, nuclear, rail accident, and more) on an interactive map
- Computes rescue routes via Dijkstra (shortest distance), A* (fastest with heuristic), and Min-Max Hazard (safest path) — side-by-side
- Identifies critical infrastructure nodes using Tarjan's algorithm and MST via Kruskal + Union-Find
- Approximates the optimal hospital tour using a nearest-neighbour + 2-opt TSP solver
- Shows execution time, nodes visited, and complexity class for every route — because it's also a DSA explainer
- Supports live GPS location, IP fallback, email alerts, and shows all incidents within 20km of you
Stack: Python 3.10 · Flask · C++ (engine) · Leaflet.js · OpenStreetMap · Render
📋 Attendify 2.0 — Cloud-Based Attendance Management System
Eliminates proxy attendance and saves 10–15 minutes of lecture time per class by replacing paper registers with a live digital system.
The problem: Traditional roll-calls waste instructional time, and paper registers are trivially exploited — students mark absent friends present ("proxy"), creating fraudulent records with no accountability.
What it does:
- Role-based dashboards for Admins, Teachers, and Students — each sees exactly what they need
- Teachers mark an entire class in seconds via digital checklist; every entry is timestamped instantly
- Students view their live attendance percentage and total-vs-attended stats in real time
- MongoDB Atlas NoSQL backend maps Student IDs to Subject IDs as flexible JSON documents
- Deployed on Render with CI/CD — every GitHub push goes live automatically
- Sessions prevent students from accessing teacher or admin routes; env vars keep credentials safe
Stack: Python · Flask · MongoDB Atlas · Gunicorn · Vanilla JS · Render
🩺 Health Lens — Medical Image Analysis Tool
An AI-powered health analysis tool that processes medical data and images to surface actionable insights.
Languages
Web & Frameworks
Data & DevOps
class Samridhi:
def __init__(self):
self.education = "BTech CSE · JIIT Noida"
self.location = "Greater Noida, India"
self.interests = ["Cybersecurity", "AI/ML", "Systems Programming", "DSA"]
def currently_doing(self):
return {
"learning" : ["Binary Exploitation", "Network Security", "ML with Python"],
"building" : "Next project (ask me what's in the pipeline)",
"open_to" : ["Internships", "Collaborations", "CTF teams"],
}
def say_hi(self):
print("Let's build something that matters. Reach out anytime 👋")
me = Samridhi()
me.say_hi()
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║ "Security is not a product, but a process." — Schneier ║
║ ║
║ Currently running on: chai + curiosity ║
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