Hi, I'm Jenish Lad — a final-year B.Tech Computer Engineering student at Indus University, Ahmedabad. I build practical software across data science, AI/ML, and full-stack development, with a focus on clean architecture, useful features, and real-world problem solving.
I am currently seeking internships primarily in Data Science and AI/ML, while also bringing solid full-stack development experience across web and product-oriented builds. My work spans machine learning applications, intelligent systems, and polished end-to-end products — from finance and conversational AI to security-focused detection platforms.
- Actively looking for Data Science internships
- Open to AI/ML roles and research-oriented collaboration
- Strong foundation in full-stack web development
- Interested in impactful, product-focused project work
FlowLedger — Privacy-First Android Finance Tracker
A native Android personal-finance tracker for recording expenses and income, setting budget limits, managing loans/EMIs, and visualizing spending. FlowLedger is designed around local-only storage, quick expense logging, and a premium mobile user experience.
| Attribute | Details |
|---|---|
| Stack | Java, Android Studio, Gradle, Room Database, Android SDK |
| Core Features | Expense and income tracking, budget alerts, EMI/loan tracking, filtering, search, payment-method tracking, spending insights |
| Data & Security | Local-only data storage, Room parameterized queries, allowBackup="false" to reduce backup extraction risk |
| UI/UX | Glassmorphism-inspired interface, liquid navigation, dark-mode support, chart-based insights |
| Build | Android APK available in the repository |
| Repository | View FlowLedger |
Brewbit POS — Full-Stack Smart Cafe Management System
A full-stack point-of-sale ecosystem for cafes and restaurants. Brewbit POS combines a staff management dashboard with customer-oriented ordering flows, real-time kitchen updates, reporting, inventory control, and table management.
| Attribute | Details |
|---|---|
| Stack | Next.js, TypeScript, Turborepo, tRPC, Drizzle ORM, PostgreSQL, Zod, Docker |
| Architecture | Monorepo structure with shared UI, configuration, validation, API, and database layers |
| Core Features | POS checkout, floor-plan management, kitchen display system, inventory management, reporting, order workflows, session tracking |
| Security | JWT authentication, bcrypt password hashing, RBAC middleware, parameterized ORM queries, authorization validation |
| Deployment | Live Demo |
| Repository | View Brewbit POS |
Vynix — Finance-Oriented Android Application
A collaborative Android application project focused on building a practical mobile experience for finance-oriented workflows and everyday user interaction.
| Attribute | Details |
|---|---|
| Stack | Java, Android Studio, Android development tools |
| Focus | Mobile application architecture, practical finance-related user workflows, and collaborative development |
| Experience | Android UI implementation, structured app logic, and usability-focused mobile development |
| Status | Public project repository |
| Repository | View Vynix |
ML-Chatbot — AI Data Assistant for ML Workflows
An interactive desktop AI data assistant that lets users upload CSV datasets, train machine-learning models, generate predictions, visualize results, and receive optional explanations through a conversational interface.
| Attribute | Details |
|---|---|
| Stack | Python, Tkinter, scikit-learn, Pandas, data visualization libraries, Ollama |
| ML Capabilities | Classification and regression workflows with Random Forest, Decision Tree, Gradient Boosting, Extra Trees, AdaBoost, KNN, Logistic/Ridge, and SVM |
| Core Features | CSV upload, target detection, feature selection, missing-value handling, model selection, predictions, feature importance, analytics dashboard |
| AI Integration | Optional local LLM explanations through Ollama and Qwen |
| Metrics | Supports accuracy, RMSE, R-squared, and model-specific prediction insights |
| Repository | View ML-Chatbot |
Chocodream — Product-Focused Web Experience
A web project focused on presenting a polished, brand-oriented digital experience with an emphasis on modern interface design, clear product discovery, and user-friendly browsing flows.
| Attribute | Details |
|---|---|
| Category | Product and brand-focused web application |
| Focus | UI/UX design, responsive layouts, product presentation, and user interaction |
| Development | Frontend-oriented web development workflow |
| Status | Public project repository |
| Repository | View Chocodream |
SpendWise — Personal Finance Management Project
A finance-focused project built around tracking expenses, improving spending visibility, and creating a simple, practical experience for everyday personal-finance management.
| Attribute | Details |
|---|---|
| Category | Personal finance and expense-management application |
| Focus | Expense tracking, usability, financial organization, and practical product design |
| Development | Application-focused development with a user-first utility mindset |
| Status | Public project repository |
| Repository | View SpendWise |
Sentinel — AI/ML Security Platform (In Progress)
An active project focused on intelligent threat monitoring and security-oriented analysis. Sentinel combines your interest in cybersecurity with data science and AI/ML-driven detection workflows.
| Attribute | Details |
|---|---|
| Stack | Python, data science workflows, machine learning, security analytics |
| Focus | Threat-aware analysis, suspicious-pattern detection, and intelligent monitoring |
| Status | Actively under development |
| Goal | Apply AI/ML techniques to real-world cybersecurity challenges |
| Repository | Coming soon on GitHub |
Sentinel represents the next step in combining data science, machine learning, and practical security impact.
Learning:
- Advanced data science & ML pipelines
- Production-ready AI integration
- Scalable backend systems
Building:
- Sentinel (active — security + AI/ML)
- Full-stack web applications
- Data-driven intelligent products
Exploring:
- Feature engineering & model evaluation
- Clean UI with useful feature design
- Real-world software implementation
Open To:
- Data Science internships
- AI/ML collaboration & roles
- Full-stack development opportunities
- Innovative project building
Building intelligent products with data science, clean engineering, and practical full-stack execution.