CV

PhD in Data Science

• Major: Deep Learning, Signal Processing, and 5G/6G Communications

MS in Electrical and Computer Engineering

• Major: Machine Learning, Optimization and Signal Processing

Research Fellow and Lecturer

• Designing and implementing efficient Deep Learning and Tiny ML for drones.
• Designing & Developing end-to-end machine learning pipelines for large-scale, multi-modal data.
• Mentoring a cross-functional team of data scientists and engineers, fostering collaboration and innovation in project development.
• Teaching Signal Processing and Machine Learning.
• Mentored 4 graduate & 6 undergraduate researchers.

Summer Research Internship

• Worked on adversarial attacks against graph neural network based wireless communications.

Summer Research Internship

• Worked on graph based machine learning for efficient resource allocation in wireless communications.

Teaching Assistant

• CS/DS 541 (Deep Learning) - Spring 2021
• DS/MA 517 (Mathematical Foundations For Data Science) - Spring 2020, Fall 2021, Fall 2022
• DS 2010 (DATA SCIENCE II; MODELING AND DATA ANALYSIS) - Fall 2020
• ECE 2310 (DISCRETE-TIME SIGNAL AND SYSTEM ANALYSIS) - Spring 2019
• ECE 2311 (CONTINUOUS-TIME SIGNAL AND SYSTEM ANALYSIS) - Spring 2019

Summer Graduate Research Internship (Funded by Ford)

• Worked on efficient computer vision for self-driving cars.
• Deep Learning and Raspberry Pi

Data Scientist

• Led development of advanced models, enhancing predictive accuracy by 30% using ensemble methods and deep learning.
• Integrated machine learning technologies across departments, increasing project efficiency by 20%.

• Travel Award for IEEE USNC-URSI conference attendance.

• Charles Kao Best Paper Award, IEEE WOCC, NJ, USA