Tianyou (Theo) Lai

I am Tianyou Lai (Theo), from Xicheng, Beijing, an MS student in Artificial Intelligence Systems Management at Carnegie Mellon University. My research connects reliable learning systems, model evaluation, and human–AI interaction with applied machine learning in healthcare, industrial inspection, physical inverse design, forecasting, and energy systems.

In research, I work across model design, dataset preparation, training, and experimental evaluation. In industry, I have interned in product data, consulting analytics, quantitative research, startup data science, and data engineering.

Education

• Carnegie Mellon University - MS in Artificial Intelligence Systems Management, Aug. 2026 - Dec. 2027 (expected)
• Lanzhou University - BS in Data Science & Big Data Technology, Sep. 2021 - Jul. 2025; GPA: 87.34/100
• The University of Texas at Austin - Exchange Program in Software Engineering, Jan. 2024 - Feb. 2024; GPA: 4.0/4.0

Publications

• TRACE: Training-time Report-guided and Clinically Ordered Concept Editing*. ACM International Conference on Multimedia (ACM MM) 2026, accepted. DOI: 10.1145/3767308.3836433.
• FREDNet: A Frequency and Decomposed-Spatial Network for Industrial Defect Signal Detection*. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2026. DOI: 10.1109/ICASSP55912.2026.11462834.
• A Review of Federated Learning under Data Heterogeneity. Expert Systems, 2026. DOI: 10.1111/exsy.70271.
• Deep Learning-Based Inverse Design of Broadband Metasurface Polarization Converter. AIP Advances, 2025. DOI: 10.1063/5.0281453.
• A Modularity-Enhanced Echo State Network for Nonlinear Wind Energy Predicting. Energies, 2025. DOI: 10.3390/en18071858.

* (Co-)First author. The full author lists and research summaries are on the Research & Projects page.

Professional Experience

• Data Science Intern, Sichuan DeepGraph Intelligent Technology (Sep. 2024 - Feb. 2025): cleaned and preprocessed data in Python, queried complex datasets with Ultipa XAI — a financial graph database serving financial institutions — and assisted with data-analysis algorithm optimization.
• Data Engineer Intern, Lanzhou Bronze Ding Intelligent Technology (Mar. 2024 - Sep. 2024): organized 20+ datasets and labeled 10k+ entries using Python and SQL; deployed MySQL and Hadoop; produced seven analysis reports with Matplotlib and Seaborn.
• Quantitative Research Intern, Guotai Junan Futures (Mar. 2024 - Apr. 2024): developed a Python futures trading system, debugged C++ and Python CTP-API implementations with Simnow, and implemented TWAP and VWAP algorithms with TA-Lib.
• Tax and Business Consulting Intern, Zhongzheng Tiantong CPA Tax Department (Jul. 2023 - Sep. 2023): processed data with Python and SQL, prepared Tableau reports, and analyzed client financials, risks, and market trends.
• Product Data Engineer Intern, Feitian Technologies (Jul. 2022 - Jan. 2023): supported product databases and intelligent password-system testing with Python, SQL, and C/C++; completed 30+ performance tests and prepared 10+ blockchain report summaries.

Research Appointment

• Research Assistant, Shenzhen University (Oct. 2025 - May 2026): nuclear sensor online monitoring and energy-system AI, including Mamba-In (co-first author; under review at EAAI) and the critical-heat-flux review in preparation for Energy.

Academic Service

• Reviewer: ICASSP 2027, ACM MM 2026, IJCNN 2026, Open Journal of Signal Processing.
• IEEE Member, 2025–present.

Skills and Honors

• Technical skills: Python (PyTorch, TensorFlow), Java, SQL, C/C++, HTML, CSS, JavaScript; Tableau, ECharts; Linux, Ceph, HDFS, OpenStack, Docker, Kubernetes, Hadoop, Hive, Spark.
• Languages: Mandarin (native); English.
• Honors: Lanzhou University academic, internship, and international exchange scholarships; undergraduate honors thesis (2025); three-time University Basketball Championship (2022-23, 2023-24, 2024-25).

Interests

• Basketball: currently taking a break from playing while recovering from knee surgery.
• Billiards: enjoying both the hot streaks and the cold spells.
• Fun facts: I have visited nearly every province in China and explored Europe on two trips of two weeks each. I have also completed several 5 km+ hiking and mountaineering trips, though a knee injury cost me the chance to attempt a 7 km peak. My travel wish list keeps growing.