Jonathan Hans

About

Researcher & Software Developer

Jonathan is a research engineer from Inventec Corp, a world-leading computer and electronics manufacturer with more than 16 billion USD annual revenue. At Inventec AI Center, he focuses on improving its manufacturing processes and pushing its technological advancements through deep learning algorithms. Speaks English, Chinese, and Native in Bahasa Indonesia.

Jonathan received his B.Sc in Computer Science from Petra Christian University (2017) and M.Sc in Computer Science from the National Taiwan University of Science and Technology (2019).

Resume [PDF]

Education

Master of Science

Feb 2017 - Jan 2019

National Taiwan University of Science and Technology, Taipei, Taiwan.

Thesis: Controllable and Identity-Aware Facial Attribute Transformation using Generative Adversarial Networks.
Improved training and inference efficiency of image-to-image translation deep learning model.
Best Master Thesis Award IICM 2019.
Graduated with 4.19 out of 4.3 GPA.

Bachelor of Science

Aug 2013 - Feb 2017

Petra Christian University, Surabaya, Indonesia.

Cisco Networking Academy 2016 NetRiders CCENT ranked 8th in APACJ and 3rd in Indonesia.
Final project: OCR for Indonesia's National ID card using traditional image processing and SVM.
Graduated with 3.94 out of 4.0 GPA.

Professional Experience

Research Engineer

Feb 2019 - Present

Inventec Corp., Taipei, Taiwan.

Invented a novel transition mechanism between motions of simulated characters that enables motion repertoire expansions without additional learning.
Devised an accurate inventory simulation and forecasting solution for AI-assisted inventory management, leading to a ~40% reduction in real-world inventory cost.
Developed the first-place solution for the intelligent forecasting competition hosted by USAID in 2020.
Designed a character controller to produce natural and lifelike movements of simulated characters while obeying highlevel user directives using Deep-RL and GAN.
Implemented order forecasting scheme into a centralized system to improve lead-time and maintain reliable product supply of the inventory management process.
Researched and deployed SOTA deep learning solutions for internal business units involving computer vision for defect inspection and time-series forecasting (three accepted US patents and three pending patent applications).

Deep Learning Engineer intern

July 2018 - Sep 2018

Industrial Technology Research Institute, Zhudong, Taiwan.

Designed a pipeline to clean, preprocess, encode, and decode MIDI files.
Developed MAC- Net, an endless music generator using LSTM as the backbone.
Implemented GAN to improve the LSTM's memory stability for endless music generation.