Tianyi Zhang

Tianyi Zhang, also known as Chloe Zhang, is a student researcher currently pursuing a Master of Science in Machine Learning and Data Science at Northwestern University. She holds a Bachelor of Science degree in Data Science from the University of Rochester, where she concentrated on Computer Science, Statistics, and Mathematics.

Academic and Research Background::

• At the University of Rochester, Tianyi gained significant research experience as a Lab Assistant at the Audio Information Research Lab. Her work involved advanced techniques such as discrete wavelet transforms and Mel-frequency cepstral coefficients for feature extraction. She developed deep learning models using bidirectional LSTM networks and CNNs, focusing on statistical methods for event modeling and beat tracking.1
• In her recent projects, she fine-tuned the Llama 2 model for a table game chatbot, utilizing Quantized Low-Rank Adaptation for efficiency and Retrieval-Augmented Generation for improved context awareness. She also engineered a Multi-Agent System using OpenAI's API to enhance music generation quality.1

Industry Experience::

• Tianyi has practical experience from internships, including a role as a Data Engineer Intern at the Agricultural Bank of China, where she analyzed customer transactions for predictive analytics. More recently, she worked as a quantitative analyst at a fund management company, focusing on performance attribution and factor exploration.1

Technical Skills::

• She is proficient in several programming languages and tools such as Python, SQL, Java, MATLAB, C++, R, and Swift. Additionally, she has experience with data visualization tools like Tableau and machine learning frameworks including TensorFlow, Keras, and PyTorch.1

Tianyi Zhang's diverse skill set and research background position her as an emerging talent in the fields of machine learning and data science.