Help & Supportcareers@gravityer.com
👋 Hi, I'm William Liaw, a Master’s student in Data AI at IP Paris. Passionate about engineering, AI, and research. Check out my projects and let's collaborate!
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
air-traffic-allocation-genetic-algorithm
November 24, 2025 – December 9, 2025
air-traffic-allocation-genetic-algorithm — GitHub repository
View ProjectChinese2PDF
August 29, 2025 – October 21, 2025
A Python tool that converts Chinese text into beautifully formatted PDFs with Hanzi, Pinyin (with tones & colors), and ruby annotations using LaTeX. Ideal for language learners and educators.
View ProjectApplicationVisualizer
November 5, 2024 – September 2, 2025
This repository visualizes job/internship application processes using Sankey diagrams. Track stages like initial screening, interviews, and outcomes with Python. Built with Plotly, Matplotlib, and Conda, this tool helps analyze application flows and trends in an easy-to-interpret format.
View Projectacademix
October 20, 2024 – September 2, 2025
Academix: A versatile LaTeX template for academic writing, inspired by EPUSP Thesis Template. Customize articles, reports, or theses effortlessly with options for chapters, citations, and flexible formatting.
View ProjectIMA208
October 9, 2024 – October 10, 2024
This repository contains resources for IMA208 - 3D Vision and Video. It covers motion estimation, object tracking, stereo vision, and 3D point cloud reconstruction, with a focus on practical exercises and group work.
View ProjectIMA204
October 6, 2024 – October 10, 2024
This repository contains resources for IMA204 - Medical and Biological Imaging / Knowledge Representation. It focuses on image registration, statistical shape analysis, graph-based methods, and medical imaging techniques such as X-ray and MRI.
View ProjectIA206
October 3, 2024 – October 4, 2024
This repository contains materials for IA206 - Neuro-Symbolic Artificial Intelligence, taught by Professor Nils Holzenberger at Télécom Paris during the 2023-2024 academic year, covering Prolog, ProbLog, formal logic, natural language processing, symbolic machine learning, knowledge representation, and probabilistic programming.
View ProjectCultural Fit Analysis
The candidate's personal projects demonstrate a strong inclination towards academic and research-oriented topics within AI and Data Science, aligning well with roles that value continuous learning and problem-solving. The breadth of technologies used (Prolog, Python, C++, LaTeX) suggests adaptability and a willingness to explore different tools. The focus on personal projects indicates self-motivation and initiative, which are positive indicators for cultural fit in a dynamic environment. However, the lack of team-based or collaborative project descriptions makes it difficult to assess direct team collaboration fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-directed learning approach. The diversity of projects, from neuro-symbolic AI to air traffic allocation and medical imaging, suggests intellectual curiosity and an ability to tackle varied problems. However, without psychometric test results or interview data, it is difficult to assess specific soft skills like teamwork, stress handling, or communication clarity in a professional setting.