KshitijJha

• Built 9 REST endpoints across 6 resources in C#/.NET 8, then rebuilt the same API in Node.js so the team could compare the two while deciding whether to move off ASP.NET MVC.
• Developed the Next.js prototype that consumes both services, including a proxy layer and role conditional routing.
• Wrote MSSQL stored procedures handling multi mode read and write paths against a 7 table schema, working in SSMS with SQL Server running in Docker.
• Delivered a Stimulsoft Reports.JS proof of concept by reverse engineering integration patterns nobody had documented. The write up fed a stakeholder decision affecting 300+ Crystal Reports.

• Built a Fleet Management REST API on my own in C#/.NET 8, using Dapper for data access against SAP HANA, and authored the supporting table schema.
• Developed a React Native client that consumes the API end to end.

Raw TCP, no framework. A listener hands each connection to its own goroutine, a shared register maps connections to users, and a mutex guards that register because several goroutines write to it at once. I got failures out of it: deadlocks, a concurrent map access race, WaitGroup misuse. I found each one by reasoning through the synchronisation model instead of adding sleeps until the crashing stopped. It's the smallest project on this list and the one that taught me the most.

Gold, silver and copper CFDs on the Capital.com API. EMA 9/21 crossover with RSI(14) confirmation, ATR(14) for stop sizing, a 1.5x ATR stop against a 3x ATR target, 1% account risk per trade, one open position per instrument. I fixed the stopping criteria in advance so I could not move them once it started losing. The lesson that stuck was infrastructural: GitHub Actions' built in cron was unreliable across a two hour test window, so the schedule now comes from an external trigger and the workflow listens.

A Tkinter GUI talking to a multithreaded TCP socket server over SQLite. The brief asked for none of that. I added live currency conversion across USD, GBP, INR and MUR, plus sales analytics in matplotlib. It was the first time I had two processes that needed to agree with each other, which is a specific and annoying kind of problem.

It blends ECMWF, GFS and UKMO ensembles with two deterministic providers into a single distribution, adds a climatological prior weighted by how far out the forecast is, and only logs a prediction when its edge over the market clears ten points. Everything resolves against historical records and scores itself on win rate, ROI and calibration. It is still running. The honest verdict is that the sample is nowhere near big enough to claim an edge.

A small 2D platformer in Godot 4.7: a player controller, an enemy, collectible coins, killzones, and a game manager tying the run together. Exported to WebAssembly, so it runs in the browser with no engine install.