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Ruichen Wang

Welcome to My Site

 

About Me

I am a Ph.D. student in the Department of Electrical and Computer Engineering at the University of Maryland, College Park, supervised by Professor Dinesh Manocha. I obtained my Bachelor's degree in Astrophysics from Peking University in 2015, and my Master's degree in Electrical Engineering from New York University in 2017. My current research interests include but not limited to millimeter waves, machine learning and the fast dynamic ray tracing.

 

Education

 

PhD University of Maryland, College Park

Sep 2018 - Now

I am currently working towards the doctorate degree of Electrical Engineering at UMD. I was in the SIG group with Professor K. J. Ray Liu from 2018 fall to 2020 summer and moved to GAMMA group with Professor Dinesh Manocha from 2020 fall.

MS New York University

Sep 2015 - May 2017

During my master's study, I was focusing on propagation models. I did mmWave measurements with Professor Ted Rappaport in 2016, in urban areas in NY and rural areas in VA. My thesis advisor, Professor I-Tai Lu helped me build a new propagation model at UHF accounting for street openings in urban street canyons.

BS Peking University

Sep 2011 - Jul 2015

Learning physics is fun and challenging. I studied pulsar stars with Professor Renxin Xu in the department of astronomy, and further did undergraduate dissertation on radio telescope feed design for pulsar star studies with Dr. Shengjin Jin in National Astronomical Observatories of China.

My Experience

 

Research Assistant

OriginWirelessAI, Maryland

Sep 2019 - July 2020

  • Analyzed 2-person sleep monitoring with commercial WiFi devices, collected and processed several weeks' sleep data, enhanced data processing with phase boosting techniques, and implemented unsupervised clustering methods for sleep stage classification.

  • Analyzed possible mmWave approaches for blood oxygen level detections. Conducted experiments to evaluate breathing rate and oxygenation relationship during sleep.

  • Performed liquid classification at mmWave. Implemented neural networks to classify different types of drinks with training data collected by TI chips. Further investigated methods to distinguish different sugar levels in solutions by mmWave radar.

  • Studied acoustic sensing in sleep monitoring. Implemented the LLAP acoustic distance sensing application.  

Research Internship

OriginWirelessAI, Maryland

May 2019 - Aug 2019

  • Implemented C++ version Walk Detection algorithm and got it working on the tracking system

  • Collected breathing data for sleep monitoring system test and analyzed sleeping data

  • Helped with Origin-Bot builds on existing wifi models 

Research Engineer 

Intelligent Fusion Technology, Maryland

May 2017 - Apr 2018

  • Analyzed ray tracing algorithms and developed programmes for ray tracing simulation in mmWave.

  • Investigated air-to-air and ground-to-air communication links.

  • Arranged plans and setups for mmWave UAV network measurements.

  • Helped applying machine learning to current propagation analysis, which improved the computing time and prediction accuracy.

Research Assistant & Teaching Assistant

NYU Wireless Center, New York

Jul 2016 - May 2017

  • Participated in 2016 NYU Wireless summer campaign for outdoor mmWave measurements. 

  • Based on data from industry, built a new propagation model accounting for street openings, clear improvements compared to current popular models.

Student Research Assistant

National Astronomical Observatories of China, Beijing

Sep 2014 - May 2015

  • Simulated the corrugated horn antenna model in High-Frequency Structural Simulator (HFSS), and expanded the original low-frequency model to a higher frequency, which was selected as a candidate feed antenna model for Five-hundred-meter Aperture Spherical Radio Telescope (FAST).

Workspace

Publications

 
  1. MacCartney Jr, G. R., Sun, S., Rappaport, T. S., Xing, Y., Yan, H., Koka, J., Wang, R., & Yu, D. (2016, October). Millimeter wave wireless communications: New results for rural connectivity. In Proceedings of the 5th Workshop on All Things Cellular: Operations, Applications and challenges (pp. 31-36).

  2. C. N. Macwan, J. S. Lu, I-Tai Lu, Ruichen Wang, Ya Hui Wu and J. A. Blaha, "Extension of the ITU-R P.1411-8 urban path loss models to high antennas," 2017 IEEE Long Island Systems, Applications and Technology Conference (LISAT), Farmingdale, NY, USA, 2017, pp. 1-5. 

  3. Ruichen Wang, I-Tai Lu, M.S. Thesis, A New Line-Of-Sight Propagation Model Accounting For Street Openings In Urban Street Canyons, 2017.

  4. Wang R, Xiong W, Xu Y, et al. Comprehensive radio frequency link analysis of ground-to-air/air-to-air communication in urban and rural scenarios[C]//2018 IEEE Aerospace Conference. IEEE, 2018.

  5. Wang R, Lu J, Xu Y, et al. Intelligent path loss prediction engine design using machine learning in the urban outdoor environment[C]//Sensors and Systems for Space Applications XI. International Society for Optics and Photonics, 2018, 10641: 106410J.

My Hobbies

 

Chess

I started playing chess at the age of five. I have earned many champions along the way. In 2003, I was select to participate in the World Youth Chess Championship on behalf of China.
During my master's study in New York, I was a member of the Marshall Chess Club and played games in many local tournaments.

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Yangqin

In the first year of primary school, I met my Yangqin teacher Dr. Chen and became his first and the last student. I was awarded the first prize in the Global Chinese Music Festival in 2010. In college at PKU, I played leading Yangqin in the orchestra of Chinese Musical Institute (CMI) for four years, directed by Professor Bryan Bi. In 2012, we were invited to perform at the University of Edinburgh and Canongate Kirk.

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Phone on Desk

Let’s Connect

 

©2018 by Ruichen Wang.