ResearchGateAbout Me
Here is Siming Deng (Larry Deng).
I am a graduate student in the Department of Electrical and Systems Engineering (ESE) at the Penn Engineering of the University of Pennsylvania. Prior to joining Penn, I gained valuable research experiences as a Research Assistant at Shenzhen University under the supervision of Dr. Jun Zhang. My work focused on Nonparametric Statistics, Distortion Measurement Error Models, and Large Sample Theory. I developed and analyzed advanced statistical methods, conducted large-scale simulations, and applied these techniques to real-world datasets, resulting in five SCI publications.
Work Experience
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Research Assistant @ Big Data Institute, Shenzhen University
Supervised by Distinguished Professor Joshua Zhexue Huang. Carried out optimizations on data processing and clustering algorithms by leveraging distributed approximate computing techniques. -
Software Development Intern @ Bank of China
Involved in the deployment and fine-tuning of large language models in internal banking systems. -
Software Engineer Intern @ Apple Inc.
Developed AI agent tools for iPhone hardware testing, enhancing automated diagnostics workflows and improving large-scale test efficiency.
If you are interested in any aspect of me, I am always open to discussions and collaborations. Feel free to reach out to me at - siming_deng_stat [at] 163.com
I am actively seeking a PhD position for 2025 Fall admission. If you have any information, please contact me. Thank you!
Research Interests
- Machine Learning
- Nonparametric Statistics
My current research focuses on addressing critical challenges in measurement error modeling and unobservable variable estimation, particularly in multiplicative distortion frameworks. Through theoretical advancements in calibration methods and simulation optimization, I have contributed to improving the accuracy of correlation coefficient estimation under complex industrial scenarios.
News and Updates
First-Author Paper: Innovative covariance-based framework: symmetry assessment and exponentiality testing under multiplicative distortion measurement Errors Now Officially Published in Communications in Statistics - Simulation and Computation
Excited to have received an offer from Apple!
Thrilled to have received an offer from UPenn Engineering!
First-Author Paper: A New Logarithmic Multiplicative Distortion for Correlation Analysis Now Officially Published in Statistical Analysis and Data Mining (JCR Q1)