lijingya21@mails.tsinghua.edu.cn
I am a dedicated Industrial Engineering student at Tsinghua University with a strong academic record and hands-on research experience in virtual reality and user experience. My goal is to leverage my skills in data analysis and human factors to drive innovative solutions in technology and design.
Relevant Coursework: Human Factors, Safety Engineering, Essentials of Management, Facilities Planning & Material Handling, Operations Research, Applied Statistics and Data Analytics, Machine Learning and Data, Modeling and Simulation
Relevant Coursework: Introduction to Psychology, Multivariate Analysis, Principles of Supply Chain Management, GPA: 3.84/4.30
Reviewed over 20 research papers for a virtual reality research project on spatial learning and cybersickness. Contributed to experimental design and SOPs. Led data analysis on navigation-related emotions and conducted in-depth qualitative analysis on navigational factors in hospital architecture.
Designed and executed a mixed experimental study with 24 participants (12 deaf and 12 hearing). Evaluated interpreter image sizes as within-group variables and interpretation speed as between-group variables. Conducted subjective and objective evaluations with After-Scenario questionnaires, and utilized mixed-ANOVA, Kruskal-Wallis, and Wilcoxon signed-rank tests for analysis. Concluded larger image sizes improve comprehension for deaf viewers, while medium speed enhances satisfaction across both groups.
Developed and optimized a fault detection algorithm for Autonomous Underwater Vehicles (AUVs) using ANN, CNN, and RNN models. Enhanced RNN with GRU, achieving up to 97% accuracy. Applied data preprocessing techniques, including LabelEncoder, data slicing, and warping. Incorporated Cosine Annealing for learning rate decay and systematic parameter tuning, including dropout, batch normalization, and Xavier initialization.
Upgraded the SEIR (Susceptible Exposed Infected Recovered) model to a SEIUR model, accounting for undetected or unreported cases. Used AnyLogic and Java to implement time-dependent parameter segmentation, improving model responsiveness to evolving epidemic conditions. Formulated new dynamic equations, applied piecewise linear parameters, and automated data-driven updates, significantly improving prediction accuracy in a 70-day simulation.
Studied the effects of pie chart design variables on user performance and preferences with 16 participants. Conducted ANOVA and regression analysis in Python. Found that pie charts with percentages and internal labels improve efficiency, readability, and user satisfaction.
Conducted field research in elderly care institutions, interviewed over 30 stakeholders, and analyzed age-friendly technology and services like 'Time Bank' for solitary seniors. Delivered insights on technology integration in elderly care to the host institution.
Awarded the National Scholarship, ranking 1st out of 52 students for academic excellence.
Received the Comprehensive Excellence Award for achievements in academic excellence, technological innovation, and social practice, ranking 1st out of 52 students.
Led initiatives to promote sign language through campaigns and tutorials, enhancing community engagement. Organized events and coordinated performance rehearsals.
Developed and delivered biology lessons using innovative teaching methods, improving students' understanding of complex biological concepts.