DEV Community: ARSH VERMA

🏆 Won 1st Place at DesignVerse 2026 – Here's What I Learned

ARSH VERMA — Mon, 29 Jun 2026 05:11:47 +0000

I'm excited to share that I secured 🥇 First Position in DesignVerse 2026 – Online Design Hackathon, organized by VIT Bhopal University.

This wasn't just another competition—it was an opportunity to solve real-world design challenges under time constraints while focusing on creating meaningful user experiences.

🚀 What This Experience Taught Me

🎯 Design is about solving problems, not decorating screens

A beautiful interface means little if it doesn't help users accomplish their goals. Every design decision should have a purpose.

🔍 Research comes before pixels

Understanding the problem, defining user needs, and identifying pain points were far more valuable than jumping straight into Figma.

🔄 Iteration is everything

The first idea is rarely the best one. Testing, refining, and improving designs continuously made a significant difference.

💡 Constraints inspire creativity

Limited time forced me to prioritize what truly mattered and focus on delivering a clear, impactful solution.

🙏 A Huge Thank You

I'm grateful to the organizers, mentors, judges, and everyone who made DesignVerse 2026 possible. Competing alongside talented designers was inspiring, and I'm honored to have represented Team Design by Arsh.

🌱 What's Next?

This achievement is another milestone—not the destination.

I'll continue exploring:

🎨 UI/UX Design
📱 Product Design
🧩 Design Systems
🔬 User Research
♿ Accessibility
🚀 Building products that solve real problems

I'm looking forward to sharing more of my design journey, projects, and learnings with the community.

Thank you for reading! ❤️

Winning a competition is rewarding, but the greatest achievement is growing as a designer with every challenge. Here's to continuous learning and creating experiences that make a difference.

From Behind the Scenes to the Spotlight: My Journey as a Hackathon Core Organizer 🚀

ARSH VERMA — Mon, 29 Jun 2026 03:54:43 +0000

Hackathons are often remembered for the amazing projects that participants build, but behind every successful event is a team that works tirelessly to make everything happen.

I'm excited to share that I was recognized as a Hackathon Core Organizer and awarded the Hackathon Leadership Certificate for my contribution to Design2Code 2.0, organized by the UX Club, VIT Bhopal University, in collaboration with Devnovate.

The Experience

Being part of the core organizing team wasn't just about managing an event—it was about creating an environment where developers could innovate, collaborate, and learn together.

From planning logistics and coordinating with team members to ensuring the event ran smoothly, every challenge became an opportunity to grow. It taught me that leadership isn't about giving instructions; it's about solving problems, supporting your team, and staying calm under pressure.

What I Learned

1. Leadership is Service

A leader's role is to enable others to perform at their best. Supporting teammates and helping resolve challenges was one of the most rewarding aspects of this experience.

2. Communication is Everything

Organizing a hackathon involves constant communication between organizers, mentors, participants, and sponsors. Clear communication can prevent many potential issues before they arise.

3. Teamwork Makes the Difference

No successful event is the result of one person's effort. Every organizer, volunteer, mentor, and participant played a vital role in making Design2Code 2.0 successful.

4. Every Challenge is a Learning Opportunity

Unexpected situations are inevitable in any event. Learning to adapt quickly and think on your feet is a skill that extends far beyond hackathons.

A Big Thank You

I would like to thank:

Devnovate
UX Club, VIT Bhopal University
Our mentors and faculty coordinators
My fellow organizers and volunteers
Every participant who brought enthusiasm and creativity to the event

Your support and collaboration made this experience truly memorable.

What's Next?

This recognition motivates me to continue contributing to the developer community, organize more impactful events, and keep improving my technical and leadership skills.

Whether it's building projects, contributing to open source, or helping organize tech communities, I'm excited for the journey ahead.

If you're considering volunteering or organizing a hackathon, I highly recommend it. The experience teaches lessons that no classroom can.

Thank you for reading! ❤️

Let's Connect!

Have you ever organized or volunteered at a hackathon? What was your biggest takeaway?

I'd love to hear about your experience in the comments!

Why We Need a "Trust-First" UX in Health-Tech (and How I Built One)

ARSH VERMA — Wed, 24 Jun 2026 06:12:53 +0000

When developers build digital health applications, we usually optimize for one thing: Utility. We build sterile dashboards, complex data-entry forms, and clinical drop-down menus designed to extract as much medical history as possible.

But what happens when your users are too anxious, scared, or hesitant to even fill out the first form?

I recently published an academic research paper titled "Designing for Hesitation: A Trust-First UX Framework for Healthcare Technology in Low-Trust Populations", and I wanted to share the core architectural and UX lessons I learned while building the case study application (MannSaathi).

The Problem: Healthcare Hesitation
In developing nations (and globally), access to digital health isn't just blocked by slow internet; it's blocked by psychological hesitation. When a user is worried about a highly sensitive symptom (like mental health or a chronic condition), hitting an "Identity Wall" (mandatory email/phone sign-up) immediately destroys trust.

Traditional GUIs with Latin medical jargon cause severe cognitive overload for users with low health literacy. They abandon the app before they ever get help.

The Solution: The "Trust-First" UX Framework
To solve this, I designed a framework that abandons the "Utility-First" approach for a "Trust-First" methodology:

Zero-Friction Anonymity: Absolutely no logins or identity walls. Sessions are ephemeral. You open the app, and you are immediately safe.
Empathetic Persona Architecture: Instead of an authoritative, robotic "Doctor" bot, the UI acts as a peer-level, non-judgmental companion.
Cognitive Decoupling: Users type in unstructured, chaotic, code-mixed natural language (like Hinglish), and the complex clinical mapping happens silently in the backend.
The Tech Stack
To make this UX feel seamless, the heavy lifting had to be invisible to the user.

Frontend (Next.js & TypeScript): The UI is intentionally minimalist. Deep dark-mode aesthetics to reduce eye strain (catering to late-night, private usage). No navigation bars, just a clean chat interface.
Backend & AI (Python): This is where the magic happens. I utilized an XLM-RoBERTa-large model, fine-tuned using LoRA (Low-Rank Adaptation) on massive medical datasets.
By fine-tuning with LoRA, the model can rapidly classify medical domains and urgency from chaotic, colloquial text (e.g., Hinglish) without needing to interrupt the user to clarify symptoms via rigid UI dropdowns.

The Results
When tested, replacing traditional GUI forms with this Trust-First conversational design resulted in some crazy metrics: 🚀 Time-to-Disclosure plummeted from the industry average of ~3 minutes down to just 14 seconds. 📈 Triage Completion Rates hit 88%.

We need to stop building health-tech that acts like a bureaucratic clinic, and start building technology that acts like a trusted companion.

Read the Research
If you are interested in UX, HCI, or AI in healthcare, you can read my full, open-access research paper here: Read the Paper on Zenodo

You can also check out the code for the project on GitHub: MannSaathi GitHub Repo

I'd love to hear your thoughts on building empathetic interfaces! Let's discuss in the comments. 👇

Building MannSaathi — An AI Health Companion That Understands Fear, Not Just Symptoms

ARSH VERMA — Sun, 21 Jun 2026 03:56:29 +0000

# Building MannSaathi — An AI Health Companion That Understands Fear, Not Just Symptoms

Fear is the real illness. We are the cure.

That line became the entire foundation of a project I've been building called MannSaathi — an anonymous, AI-powered health companion designed to solve a problem most healthcare apps completely ignore.

The Problem Nobody Talks About

India doesn't lack hospitals. It doesn't lack clinics, diagnostic centers, or telemedicine platforms. The infrastructure is there.

What's missing is the courage to take the first step.

People delay seeking healthcare not because care doesn't exist, but because of things that never show up in a hospital's capacity report:

Fear of diagnosis — not knowing feels safer than knowing
Social stigma — worrying about what people will think
Masculinity norms — "real men don't complain"
Cost concerns — assuming it's unaffordable without checking
Lack of time — life getting in the way
Denial — "it's probably nothing"

So I asked myself a different question: what if the product's job wasn't to fix the system, but to fix the hesitation?

That's what MannSaathi tries to do.

What I Built

MannSaathi is a full-stack, anonymous-first health companion that lets people check symptoms, talk through what they're feeling, and get calm, non-alarming guidance — without ever creating an account.

Core principles baked into the product:

100% Anonymous — no login wall, ever. The moment you ask a hesitant person to sign up, you lose them.
Calm language always — the AI never says "high risk" or "emergency." Risk indicators use amber, not red.
Built for how Indians actually talk — Hindi, English, and Hinglish, not textbook phrasing.
A custom-trained AI model — not a wrapper around ChatGPT or Gemini.

The AI — Trained From Scratch

This was the part I wanted to get right the most.

Most "AI health" projects just call an LLM API and call it a day. I wanted MannSaathi's model to actually understand the way people in India describe symptoms — which is messy, mixed-language, and full of context an off-the-shelf model won't catch.

Base model: xlm-roberta-large
Fine-tuning method: LoRA (Low-Rank Adaptation) — lets you fine-tune a large multilingual model without needing massive GPU resources
Training environment: Kaggle's free T4 GPUs
Output: Detects 22+ symptom categories across Hindi, English, and Hinglish input

The model is hosted on Hugging Face's Inference API, decoupled from the main app, so it scales independently of the frontend/backend.

Tech Stack

Frontend:

Next.js 14 (App Router)
React + TypeScript
Tailwind CSS
Framer Motion for animations
Zustand for state management

Backend:

FastAPI (Python) — handles AI routing and inference orchestration
Prisma ORM
Neon — serverless PostgreSQL

Auth & Infra:

Google OAuth (optional — anonymous mode is the default)
Hugging Face Inference API for AI hosting
Deployed on Render (both frontend and backend)

Design Decisions That Actually Mattered

A few choices that seem small but changed everything:

Dark mode by default — most people check symptoms privately, often at night. Dark mode isn't just aesthetic here, it's functional.
No red for risk levels — red triggers panic, which is the opposite of what a hesitant user needs. I used warm amber instead.
Three-step max flows — every additional decision point is a chance for an anxious user to bounce. The symptom checker never exceeds 3-4 steps.
Anonymous-first, not anonymous-only — registered accounts unlock history and streaks, but nothing meaningful is gated behind login.

What's Next

This is still evolving — next on the list is expanding the symptom taxonomy, adding voice input for users who find typing symptoms difficult, and improving the model's confidence calibration on edge cases.

Links

🌐 Live site: https://mannsaathi-mukk.onrender.com
💻 GitHub: https://github.com/ArshVermaGit/mannsaathi
🤗 AI Model: https://huggingface.co/ArshVerma/mannsaathi-symptom-classifier-large
🎥 Full walkthrough video: https://www.youtube.com/watch?v=c58bVmaaMQ0

Would genuinely love feedback from anyone who's worked on health-tech, multilingual NLP, or anonymous-first product design — drop a comment below.

— Arsh

Building SimplyPDF — Privacy-Focused PDF Tools in the Browser

ARSH VERMA — Wed, 11 Feb 2026 13:23:05 +0000

Hey everyone 👋

I wanted to share a project I built during the WiCS Online Hackathon (Winter 2026) — it’s called SimplyPDF.

🧩 The idea
I wanted to create a lightweight set of PDF tools that run entirely in the browser. Most tools require uploads, which introduces latency and privacy concerns — so I focused on client-side processing instead.

⚙️ What it does
• Merge / Compress / Convert / Split PDFs
• Runs fully in-browser
• No file uploads — files stay on your device
• Simple, responsive UI

🛠️ Built with
Frontend-focused web stack and browser-based processing libraries.
Designed and implemented end-to-end by me during the hackathon.

🔗 Demo Video
https://youtu.be/SdoFA6ISg1A?si=XsofJPcVPNAemKQp

🌐 Live App
https://simplypdf.vercel.app

💻 GitHub
https://github.com/ArshVermaGit/SimplyPDF

🏆 Devpost Submission
https://devpost.com/software/simplypdf

I’d really appreciate feedback — especially on:
• UX improvements
• Performance ideas
• Architecture suggestions
• Feature ideas worth adding next

Thanks for checking it out 🙏