Hello! I'm Kejiang Qian, a Ph.D. student in Machine Learning Systems at the University of Edinburgh. I am an aspiring ML scientist specializing in the intersection of ML theory & algorithm and its multi-domain applications. My passion lies in leveraging AI in complex decision-making processes across diverse real-world scenarios.

I believe in the power of AI technology to transform society into more sustainable, equitable, and efficient environments. My research is not just about algorithmic side; it is about making a tangible impact on society and improving the quality of life. I am dedicated to shaping the future of socioeconmic development through innovative, human-centered AI technology.

Kejiang_profile

Research Interests

Deep Learning: Machine Learning Theory, Algorithmic Game Theory, Deep Reinforcement Learning, Large Language Model
Urban Computing: Spatial Data Analysis, Network Data Analysis, Urban System Simulation & Modeling, Spatio-temporal Data Mining
Blockchain Technology: Decentralized Autonomous Organization (DAO), On-chain Governance, Token Economy Modeling, Tokenization

Technical Skills

Programming: Python, R, JavaScript
Data Science and Machine Learning: scikit-learn, PyTorch, Keras, Tensorflow, NLTK, D3.js, Tableau, Deck.gl
Agent-based Simulation: GAMA Platform, NetLogo, Vensim
Web Development: React, HTML, CSS, Flask
Design: AutoCAD, Revit, Adobe PR, Figma, Miro
Spatial Data Analysis: ArcGIS, QGIS, GeoDa, Geographical Detector, Geopandas, OpenStreetMap, Pysal
Network Data Analysis: Spaghetti, NetworkX, OSMnx
Tools: Git, Linux, LaTex

Experience

Honorary Health Inequality Analyst, King’s College Hospital NHS Foundation Trust London, London, United Kingdom, May 2023 - Nov 2023

  • Data Scientist for Healthcare Service: Worked on large hospital datasets to understand the patient population’s demographics, characteristics, and health demands using machine learning and spatial analysis approaches, helping the hospital tailor its services to better meet the needs of its patients.

Affiliated Researcher, City Science Lab @ Shanghai - MIT Media Lab, Shanghai, China, Oct 2021 - Current

  • Research on blockchain technology: Worked on blockchain technology to encode regulations of communities and cities, such as decarbonized transportation policy and prosocial urban planning into smart contract to foster a transparent and decentralized urban environment.
  • Incentive policy and tokenomics design: Developed mechanisms of incentive and token economy to incentivize prosocial behavior and community engagement in real estate development. It aims to benefit communities and provide dynamic and participatory solutions in urban development.
  • Decentralized autonomous organization (DAO) simulation: Developed agent-based simulation for the feasibility study of DAO in real estate development at Kendall Square, focusing on the collective decision-making process and on-chain asset management.
  • Urban simulation: Developed agent-based simulation for human mobility and urban development in New York City and Kendall Square based on U.S. census data and national household trip data, respectively.
  • Data analytics: Develop machine learning technologies to analyze human mobility and the performance of transportation system.
  • Human-computer interaction: Designed and developed an interactive platform for urban data analysis and visualization using JavaScript, React Native and D3.js.

AI/ML Intern, Kinhub, London, UK, Jan 2021 - Mar 2021

  • Conversational AI system: Worked on training and testing conversational AI system, Kami chat-bot, to have interactive dialogues with users for improving mental well-being of women and children using Rasa framework and Python.
  • Data preparation and processing: Developed a Latent Dirichlet Allocation (LDA) model to extract topics of documentations and label them for chat-bot learning.

Selected Publications

Please see my Google Scholar for updated list.