Work and Service

Software Engineer Intern

Internship at Bosch - UAES (Shanghai, China)

• Responsibilities:
• Lead cross-functional team in the developing enterprise-level software with extendable AI system using Agile and Scrum methodologies.
• Construct flexible and scalable database for confidential data, with maintenance protocol and action plan to mitigate risks in future development.
• Develop the software layer: conduct data analysis using Panda and Numpy framework, implement core logics and algorithms, build machine learning model tailored for company data using PyTorch, Tensorflow, and Scikit Learn, develop software’s frontend.
• Achievements:
• Implement process automation, reducing manual workload by 60-90%.
• Add resource recycling to the pipeline, introducing standards.

Programming Language Researcher

Apprenticeship at McGill University

• Responsibilities:
• Design logic frameworks to replicate real life models (software, hardware, systems, and more!) using functional programming languages.
• Mechanize normalization by evaluation to enhance model reasoning, reducing model verification speed from days to seconds.
• Achievements:
• The frameworks are applicable to various industrial settings.
• Automate up to 100% of verification process in the pipeline.

Natural Language Processing Researcher

Apprenticeship at McGill University

• Responsibilities:
• Research state-of-the-art (2023) natural language processing models for the classification of Chinese characters.
• Implement and optimize classification machine learning models without high-order semantic logics.
• Achievements:
• Reach +90% model accuracy.

Software Engineer Intern

Internship at Anban Tech (Shanghai, China)

• Responsibilities:
• Debug and improve the intelligent fuzziness testing system.
• Achievements:
• Clean noise from data depending on the noise intensity.

Volunteer

Elderly care-taker at Royal Victoria Hospital

Life Guard

Guardian at World Gym Brossard

Asgardian Knight Commander

Protector of seven galaxies

Skills

• Full-Stack Software Development (2.5 years)
• AI Engineering (2 years)
• Data Scientist (3 years)
• Build Machine Learning Models (2 years)
• Logic and Reasoning Researcher (1.5 years)

Research and Project

Research

• Normalization by Evaluation for Simply Typed Lambda Calculus (2024)
Normalization by Evaluation (NbE) is a powerful normalization concept in type theory and functional programming that aims to establish a consistent normal form of representing typable expression. The technique is useful to construct efficient and extendable verifier which can reason about model properties.

This research presents an overview of NbE acting on the model of Simply Typed Lambda Calculus in proof assistant Coq.
Repository link: here
Download paper: here
Amazing supervisors: Jason Hu, PhD., Prof. Brigitte Pientka
• A Deeper Exploration of Natural Language Processing in Chinese (2023)
We present a Natural Language Processing (NLP) task of text classification for text in Chinese, with a deeper focus on radical and stroke information for individual Chinese character. We utilize multinomial naive bayes classifiers with different selection strategies. Our work proves the effectiveness of the technique, as it outperforms expectated accuracy while completely disregards textual semantic logic.

Download paper: here
Amazing teammates: Ava Gilmour, Haiqi Zhou

Project

• Multiple ML competition experience that scored within top 25% globally, with best ML models ranked 12/993 and 82/4770.
• Multiple independent projects on GitHub:
• ML model that can detects hand gesture and translate into simple commonly used phrase or English alphabet using American Sign Language.
• Cryptographic cipher and attack design.
• Mechanizing simple shell in C utilizing different memory management methods.
• Exploration of software development principles and design patterns.
• Simple video game design and modding.

Technology

Fluent in:

• AI Tools: Relevance AI, Make, Agentive, Voiceflow, HuggingFace, Google VertexAI, Kaggle Database.
• Microsoft: Azure, Excel, Power BI, PowerPoint, Word.
• Python: Daily usage. To implement Machine Learning Model or to build an AI system.
• Java: Software design and video game modding.
• C: For low-level high-performance implementation. Building simple shell.
• R: Efficiently compute various statistical model, such as rank-based non-parametric statistic and regression models.
• SQL: Data retrieval and manipulation. Neatly structure and classify data while assuring easy and fast access.
• OCaml: Functional programming, mostly used for research purpose.
• Coq/Beluga: Construct mathematical models of real life systems (such as software program or security protocol) and reason about their properties to ensure correctness.

Languages

• English: fluent
• French: fluent
• Chinese Mandarin: native
• German: half-work proficiency
• Japanese: half-work proficiency
• Spanish: beginner
• Russian: beginner

Education

MCGILL UNIVERSITY _{MONTREAL, QUEBEC, CANADA}

BACHELOR OF SCIENCE

Math & Computer Science