Zhifu Ge

Dubsmash is the second-largest short-video social media app in the US, with over 1 billion video views per month. Zhifu has been the principal developer of the iOS app since October 2018, contributing 500+ commits.

- Owned 30+ bi-weekly releases
- Owns several vital areas of this large-scale social media app: the feed, the camera,
and the direct messages
- Leads the team on implementing several architecture design patterns to make the
codebase more maintainable, testable, and scalable: Dependency Injection, The Coordinator Pattern, and MVVM

ProntoForms is the iOS client of ProntoForms Corporation’s mobile forms system. It presents custom-made forms fetched from the server, let the users fill in data, and send the data back to the server.

ProntoForms has been a successful solution trusted by large companies like Unilever, AT&T, TOSHIBA, and BP.

I worked on ProntoForm during my employment with Brierwood Design Co-operative, from November 2016 to February 2018.

Technologies:

UIKit, Grand Central Dispatch, Core Data, MapKit, AVFoundation. Core Graphics, Core Animation, Amazon AWS, Rest APIs, Objective-C, Swift, Fastlane.

Wave Whiz is an iOS app for maximal overlap discrete wavelet transform (MODWT) analysis. It loads signal data from text files, or from the console where a user can type or paste in the values. Its main features include multi-resolution analysis (MRA), multi-scale analysis of variance (ANOVA), and denoising. Analysis results can be exported to text files.

Wave Whiz is heavy on data processing. To make the UI sleek and always responsive, I took full advantage of Grand Central Dispatch, NSOperations, and multi-threading best practices. The result is a stable, high performance, and power-efficient app that has been very well received by the client and the client's users.

Technology:

UIKit, Grand Central Dispatch, Accelerate (Apple's high-performance, energy-efficient vector-processing framework), vDSP (Apple's digital signal processing framework). Swift, C, Fastlane.

ECG Wiz is an iOS app for high-frequency ECG waveform analysis.

The app has a very complex 7-stage data processing system. To make the user interface always responsive, preserve battery life, and increase the processing speed, I optimized every aspect of the architecture and algorithm design, to the extent that re-implementing certain functions in C instead of Swift. The payoff is huge. It runs super fast, comparable to desktop-class applications of similar functions.

Technology:

UIKit, Grand Central Dispatch, Accelerate (Apple's high-performance, energy-efficient vector-processing framework), vDSP (Apple's digital signal processing framework). Swift, C, Fastlane.