Frontend Developer
TrackFund - Personal Finance Manager helps you take control of your money with ease. Track income, monitor expenses, set budgets, and generate insightful reports - all in one sleek, user-friendly dashboard. Whether you're saving for a goal or just managing daily expenses, TrackFund empowers smarter
6M Hyderabad commuters guess bus arrival daily. Static schedules fail. No real-time, low-data fix. Process Built GPS + historical delay prediction engine. Weighted blend of live position, schedule, history. Results 91% prediction accuracy. Loads in 2s on 2G. 1-tap ETA. Works on basic Android, no install needed. Reflection Connect real TSRTC GPS feed from day one to validate prediction model against actual live delays.
Do toss wins matter? Which phase decides IPL? Who are top 5 batters/bowlers across 2021-25? Process Downloaded cricsheet.org CSVs, cleaned data in pandas, analysed toss, phases and players. Results Toss+field = 58% wins. Death overs gap is 3.6x bigger than powerplay. Kohli leads runs. Reflection Add venue and pitch data to see if toss advantage varies by ground.
At 8pm, people stare at their fridge and order Swiggy. The gap: ingredients ≠ meal ideas. Process Mapped real fridge scenarios. Built ingredient-matching engine. No API, no signup, instant. Results 20+ recipes, 0 API cost, works offline, loads in 1 sec. Any tired person can use it. Reflection Add voice input and regional Indian recipes. Better mobile UI for one-handed use at 8pm.
Built a mobile-first tool to track factory batch sustainability using real operational data. Process Designed low-friction workflows and transparent scoring for non-technical factory operators. Results Generated transparent sustainability scores and printable reports in under 2 minutes. Reflection Add offline sync and OCR bill scanning to reduce manual factory-floor data entry.
The challenge was to create a fictional product campaign capable of gaining real online attention. I identified digital burnout and “chronically online” behavior as a highly relatable Gen Z problem. Instead of using random humor, I created OFFLINE™ — a fake energy drink designed to disconnect users from screens. The goal was to combine meme culture, premium startup branding, and relatable internet behavior into a campaign that felt absurd, believable, and highly shareable. Process I approached the project like a real viral product launch. First, I studied meme-driven brands like Liquid Death, Duolingo, and Ryanair to understand how humor and minimal branding create high engagement. I explored multiple product ideas before selecting OFFLINE™ because it directly targeted internet addiction and screen fatigue. Early concepts felt too chaotic or meme-heavy, so I refined the design using a cleaner layout, cyberpunk-inspired visuals, premium typography, and subtle notification graphics. I focused on making the campaign feel realistic enough to stop scrolling while still being absurd enough to encourage reposts, comments, and meme participation. Results The final campaign successfully combined realism, humor, and internet culture into a cohesive viral marketing concept. The poster was optimized for reposts, meme engagement, and short-form social content. The project demonstrated strong audience targeting, branding consistency, and understanding of Gen Z attention behavior. The campaign was designed to encourage curiosity, comments, and organic sharing by blending believable startup aesthetics with relatable digital burnout humor. Reflection With more time, I would expand OFFLINE™ into a multi-platform campaign with TikTok/Reels videos, animated ads, meme replies, and a fake product landing page. I would also test multiple headlines and visual styles across different online communities to compare engagement levels. More audience testing would help refine humor, improve relatability, and identify which content formats generate the strongest organic sharing and retention.
College students make frequent small payments for food, travel, recharges, and daily expenses, making it difficult to track where their money goes each month. Many expense-tracking tools require mobile apps, internet access, or complex setups. This project solves that problem by providing a lightweight Python command-line application that allows students to record expenses, monitor spending, identify their highest spending category, and stay within a monthly budget using a simple offline interface. Process I began by analyzing the hackathon requirements and designing a menu-driven command-line workflow. Expenses were initially stored using Python lists and dictionaries to keep the solution simple and efficient. To improve usability, I added functions for adding, viewing, and analyzing expenses. Next, I implemented CSV-based storage so data persists even after the application closes. To go beyond the minimum requirements, I added category-wise reports, expense deletion, and monthly budget monitoring with warning alerts. Finally, I refined the terminal output, added input validation, and handled invalid user inputs to improve reliability and user experience. Results The final application successfully implements all required features: expense tracking, viewing records, total spending calculation, and highest spending category analysis. Additional features such as CSV-based data persistence, category reports, expense deletion, and budget alerts were added to enhance functionality. The solution works completely offline, uses only Python standard libraries, and provides students with a simple and reliable way to monitor spending habits and manage personal finances. Reflection With more time, I would replace CSV storage with SQLite to improve scalability and data management. I would also add monthly spending summaries, graphical visualizations, and PDF report exports to provide deeper financial insights. Support for multiple user accounts and secure authentication would make the application more practical for real-world use. A future version could also include a desktop or web interface while keeping the same expense-tracking and analytics features.
Companies receive hundreds of applications through traditional job portals but struggle to identify candidates who can actually perform the job. Recruiters spend significant time screening resumes with limited insight into real skills. This project explored how proof-of-work hiring—through challenges, portfolios, and work samples—can help companies evaluate job-ready talent faster. The objective was to identify organizations that could benefit from this approach and develop strategies to initiate partnership conversations. Process I approached the challenge from a business development perspective. First, I identified industries where skills-based hiring is most effective, including SaaS, FinTech, EdTech, and E-commerce. I then researched companies with active hiring needs and mapped decision-makers such as Talent Acquisition Heads and HR Leaders. To prioritize opportunities, I created a scoring framework based on hiring activity, role volume, growth stage, and adoption potential. Finally, I designed outreach campaigns including cold emails, LinkedIn messages, and follow-ups while preparing responses to common hiring objections. Results The project resulted in a pipeline of 25 qualified companies that could benefit from proof-of-work hiring. I developed a prioritization framework to identify the highest-potential partnership opportunities, selected the top three target companies, and created a complete outreach strategy. The final solution demonstrated a structured approach to researching prospects, engaging decision-makers, and positioning proof-of-work hiring as a solution for improving candidate quality and reducing screening effort. Reflection With more time, I would validate findings through direct conversations with recruiters and hiring managers. I would also use live hiring data and outreach metrics to refine the prioritization model and measure partnership conversion potential more accurately.
This is S’s work on Wooble.
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