Meet the Writer: Hacker Noon's Contributor Disha Patel, Software Engineer & ML Researcher

\ Welcome to HackerNoon’s Meet the Writer Interview series, where we learn a bit more about the contributors that have written some of our favorite stories . So let’s start! Tell us a bit about yourself. For example, name, profession, and personal interests. I'm Disha Patel, a software engineer at Apple, a published ML researcher, and former university instructor. I was born in India, moved to the U.S. for my Master's in Computer Science, and somehow ended up teaching iOS development to 65 university students before turning 25. Outside of engineering, I'm into fitness, cooking, and building my curly hair care routine. I also have a growing Instagram community of 17,000+ developers and coders. \ Interesting! What was your latest Hackernoon Top story about? My latest piece, "Why On-Device ML Is the Future of Mobile Apps," explores why mobile developers should stop sending every ML prediction to a cloud API. The hardware in our pockets can already run billions of inferences per day, most developers just haven't caught up yet. I break down the latency, privacy, cost, and connectivity advantages of running ML directly on-device. https://hackernoon.com/why-on-device-ml-is-the-future-of-mobile-apps-and-how-to-get-started?embedable=true \ Do you usually write on similar topics? If not, what do you usually write about? Yes, I write at the intersection of mobile engineering and machine learning. My first HackerNoon article covered production patterns for deploying Core ML models on iOS. I also published ML research on benchmarking large language models for automated system diagnostics. The common thread is always the same: how do we take ML from “works in a notebook” to “works on a real device for real users”? \ Great! What is your usual writing routine like (if you have one?) I usually write on weekends or late evenings after work. Most articles start with a problem I personally ran into as an engineer or something my students repeatedly struggled with. I outline the structure first, write the technical content, then go back and simplify it without losing depth. If I wouldn't send it to a junior developer friend, it's probably not ready yet. \ Being a writer in tech can be a challenge. It’s not often our main role, but an addition to another one. What is the biggest challenge you have when it comes to writing? Simplifying without dumbing things down. The topics I write about - model quantization, on-device inference, production deployment are genuinely complex. The challenge is making them accessible without losing the technical depth that makes them useful. I also have to be thoughtful about what I share since I work at a major tech company and want to keep my writing focused on general engineering knowledge and personal research. \ What is the next thing you hope to achieve in your career? I'm currently working on my second research paper, focused on benchmarking lightweight transformer models for fault detection on edge devices. Long term, I want to help bridge the gap between ML research and practical engineering, especially in the on-device ML space where resource constraints actually matter. \ Wow, that’s admirable. Now, something more casual: What is your guilty pleasure of choice? Binge-watching cooking competition shows while eating instant noodles. The irony is not lost on me. \ Do you have a non-tech-related hobby? If yes, what is it? Fitness - I work out almost every day. It keeps me sane. I also share fitness content on Instagram alongside coding posts, which somehow led to 17K followers interested in both bicep curls and Swift closures. \ What can the Hacker Noon community expect to read from you next? Probably a deep dive into benchmarking lightweight transformers - DistilBERT, TinyBERT, and MobileBERT for fault detection on resource-constrained devices. I want to focus on real-world constraints like latency budgets, memory limits, and INT8 quantization instead of just benchmark marketing numbers. \ What’s your opinion on HackerNoon as a platform for writers? It’s one of the few platforms where technical depth is actually rewarded. On many platforms, algorithms prioritize engagement bait. On HackerNoon, genuinely useful technical articles still get surfaced. The editorial process has also been refreshingly fast and respectful of the writer’s original voice. \ Thanks for taking time to join our “ Meet the writer ” series. It was a pleasure. Do you have any closing words? If you're a mobile developer who hasn't started thinking about on-device ML yet, now is the time. The gap between cloud-first ML and on-device ML is closing fast, and engineers who understand both sides will become incredibly valuable. And if you're an immigrant engineer reading this, keep going. The path can be harder, but the work speaks for itself. Check out Disha Patel’s HackerNoon profile here, and read more of her amazing stories! https://hackernoon.com/u/dishapatel