Nanjing Forestry University · College of Chemical Engineering
Chemical Engineering of Forest Products · Undergraduate · 2024.09 - Present
GPA 3.6 · Class rank 1 · Major rank 2
Chemical Engineering of Forest Products · College of Chemical Engineering · Nanjing Forestry University
Xujie Fang
Modeling, research communication, and AI-assisted workflows for chemical problems
GPA 3.6, ranked 1st in class and 2nd in major. Building from chemistry and engineering fundamentals toward modeling, programming, and AI-assisted research workflows.
Education
Awards & Honors
View evidence2026 · International
MCM/ICM Honorable Mention (H Award)
International math modeling competition
2025 · International
MCM/ICM Honorable Mention (H Award)
International math modeling competition
2024-2025 · National
National Inspirational Scholarship
National-level scholarship
2024 · Provincial
CUMCM Jiangsu Provincial First Prize
Core math modeling achievement
2025 · Provincial
Jiangsu Advanced Mathematics Competition, 3rd Prize (A-level)
Mathematics proficiency
2025 · Provincial
MathorCup Math Modeling Challenge, Regional 2nd Prize
Math modeling event
2023 · Provincial
37th China Chemistry Olympiad (Preliminary), 2nd Prize
Chemistry foundation
2022 · Provincial
36th China Chemistry Olympiad (Jiangsu), 2nd Prize
Chemistry foundation
2024-2025 · University
University Merit Student
Comprehensive honor
2024-2025 · University
Academic Competition Outstanding Individual
Competition recognition
2024 · University
Baima Campus Freshman Volleyball Cup, Runner-up
Campus sports
2024 · College
College Freshman Debate, Runner-up
Communication & teamwork
Skills
Core Discipline
Organic chemistry mechanisms and chemical engineering fundamentals.
Modeling & Research
Mathematical modeling, scientific writing, and data visualization.
Dev & Productivity
Frontend fundamentals and AI-assisted development workflows.
Engineering & KM
Office, drawing, simulation, and reference management tools.
Projects & Practice
Mathematical Modeling Practice
Worked on open-ended modeling problems across CUMCM, MCM/ICM, and MathorCup. The practice emphasized problem decomposition, assumption design, data processing, result interpretation, and paper writing.
Capabilities： Problem framing, model assumptions, data analysis, academic writing
AI-Assisted Learning & Knowledge Management
Built a personal workflow for literature reading and knowledge organization with AI tools, Zotero, Obsidian, Markdown, and LaTeX, aiming to make coursework and research preparation more traceable.
Capabilities： Reference management, knowledge organization, research communication, learning reflection
Personal Academic Resume Website
Built a bilingual academic resume website with Astro, including portfolio sections, an evidence gallery, project pages, responsive layouts, print-friendly resumes, and automated quality checks.
Capabilities： Component architecture, responsive design, static deployment, information architecture, privacy-aware versioning, CI/CD
ChemAI Lab
A machine learning & quantum chemistry driven chemical research platform. Integrates RDKit, PyTorch, Lightning across 15 subpackages for data, features, modeling, XAI, and QM interfaces.
Capabilities： Python, PyTorch, RDKit, ML Engineering, Project Architecture
Leadership & Service
2024.09 - 2025.06
Class Academic Representative
Responsible for assignment collection and distribution, academic affairs coordination, and supporting course instructors.
2024.09 - 2025.06
Teaching Information Liaison
Responsible for communicating teaching information, collecting course feedback, and facilitating student-teacher communication.
- 2024: Primary organizer of the 1st Baima Campus Freshman Volleyball Cup
- 2024: Participated in the 'Card House' volunteer service activity
- 2025: Participated in the Red Cross voluntary blood donation activity
Research Interests
Organic chemistry as the foundation, computational tools as the extension
My current academic interest starts from organic reaction mechanisms and synthetic strategy, then extends toward computational chemistry and AI-assisted research workflows. I am still at an early undergraduate stage, so I treat this direction as a long-term training path: build a solid chemistry foundation first, then learn modeling, programming, and literature workflows that can support future research.
Organic Synthesis Methodology
Ongoing study of Clayden, March, and related texts, with focus on synthetic strategy and reaction mechanisms
Computational Chemistry / AI-Assisted Synthesis
Long-term interest in reaction prediction, retrosynthetic planning, and molecular property prediction
LLMs + Agent Workflows
Exploring how LLMs can support literature retrieval, reading notes, and research knowledge management
Deep Learning Fundamentals
Studying neural network basics, with interest in graph neural networks for molecular representation learning