Yi-Shin Lin

Ph.D.

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About Me

Welcome to my personal website! I am an experimental psychologist with expertise in statistics and computational modeling. I conduct interdisciplinary research across multiple fields. So far, the areas in which I have participated include double-blinded drug trials, sleep science, visual search, EEG analyses, studies in laboratory-based and natural pedestrian behaviors, machine-learning modeling of drivers’ lane change behaviors, and CCTV-video analyses of road user interactions.

Contact Information

  • Location:

Expertise & Skills

Proficient

Expertise in Experimental and Cognitive Psychology, Decision-Making Models, Applied Statistics, Genetic Algorithms, Approximate Bayesian Computation, Machine Learning Models, Scientific Writing, and Behavioral and EEG Research Methods. Proficient in programming languages such as R (including its packaging ecosystem), Rcpp, C, C++, Python, and MATLAB.

Comfortable

Expertise in Social Psychology, Transport Studies related to pedestrians’ and drivers’ decision-making in road safety, deep neural network-based computer vision, and parallel algorithms. Comfortable with the programming languages such as CUDA and PyTorch.

Familiar

Qualitative Research Methods, TensorFlow, C#, SQL, React, and Next.js.

Professional Experience

Research Fellow at University of Leeds

March 2020–September 2023
  • Work 1: Cognitive Decision-Making in Traffic
    • Independently executed research on decision-making in traffic within a controlled laboratory environment.
    • Resulted in a publication in an internationally renowned journal.
    • Developed software for testing stochastic differential equations (written in C++ and connected to R interface).
  • Work 2: Road-User Interactions at the Microscopic Level
    • Conducted a video-based naturalistic traffic study.
    • Created toolkits for automated extraction of traffic trajectories from multi-day video data.
    • Led to multiple publications in international journals and conference proceedings.
  • Work 3: Collaborative Projects
    • Assisted in demonstrating the application of a machine-learning model (Long-Short Term Memory) for predicting lane-changing behaviors on highways.
    • Summarized meaningful road user interactions using a computation model.
    • Generated new ideas for research grants related to nudging behavior choice.
  • Other Duties
    • Supervised students, reviewed manuscripts, and participated in institutional operations.

Postdoctoral Research Fellow at Tasmania Cognition Lab

September 2015–August 2018
  • HPC Software for Hierarchical Bayesian Inference:
    • Led two projects creating HPC software for cognitive psychologists.
    • Managed an 8-GPU computing server in an elastic cloud environment (similar to GCP and AWS).
    • Impacts:
      • Developed the “parallel PDA” simulation-based method for solving formal probability density functions.
      • Created a tool for conducting Bayesian inference on regular PCs without relying on HPC.
      • Documented these projects in papers published by internationally renowned journals.
  • International Collaborations and Workshops:
    • Assisted lab members in collaborating with prominent computational modeling researchers worldwide.
    • Supported Bayesian Inference workshops in Taiwan and Australia.
  • Conference Speeches:
    • Delivered two speeches at Australian Mathematical Psychology Conferences.

Achievements

PhD

University of Birmingham

Experimental Psychology: My research involved developing a hierarchical Bayesian decision-making model to study visual search.

Master of Art

The City University of New York

Cognitive Neuroscience

BSc

National Taiwan University

Psychology: Recipient of the Dean’s List award with a strong emphasis on research.

Hobbies & Interests

I enjoy water sports, mountaineering and cycling. I have visited several renowned mountains in multple countries. I also obtained the title of entry-level black belt in Shotokan.