A photo at StarveRock

Boyang Wang - Résumé

• Ph.D. in Electrical Engineering with 6+ years research and project experience.

• Experienced in adapting signal processing and machine learning algorithms in system hardware and software design to solve real-world problems.

• Work on communication protocols for ultrasonic signal transmission was commended by Sigma Xi as ‘pioneering’ and ‘leading to a breakthrough in the subject.’ Received award from Sigma Xi/IIT.

• 29 publications including IEEE journal papers, sponsored conference papers, and technical reports.

• Mentored and instructed over 30 graduate students and research projects.

• A real doer, fast learner, and communicative teammate, who is innately curious and adaptive to new knowledge and techniques.

PERSONAL DETAILS

Github	https://github.com/bwang40
Email	bwang40@hawk.iit.edu
Website	https://bwang40.github.io/BoyangWang/
LinkedIn	https://www.linkedin.com/in/wang-boyang/
Phone	+1(312)-714-8770

EDUCATION

Time	Degree	Major	School
(2015–Now)	PhD Candidate	Electrical Engineering	Illinois Institute of Technology
(2013–2015)	M.S.	Electrical Engineering	Illinois Institute of Technology
(2009–2013)	B.S.	Information Engineering	Beijing Institute of Technology

RESEARCH INTERESTS

• Embedded Digital Systems

• System-on-Chip Hardware & Software co-deisgn

• Signal Processing

• Communication Systems

• Artificial Intelligence (AI) and Machine Learning

SKILLS

• Languages: Python, MATLAB, C, C++, ASM, VHDL, Verilog

• Software: Microsoft Office Toolsets, AutoCAD, Fusion360, LaTex

EXPERIENCE

Research Assistant Illinois Institute of Technology (2015-2020)

• Worked on research topics including ultrasonic signal processing, embedded systems, hardware & software codesign, and artificial intelligence (AI).

• Instructed and directly involved in 30+ student projects, including 5+ graduate thesis projects and four teams who developed prize-winning projects. To maximize efficiency and teamwork, I arranged plans, work schedules, and meetings and ensured students stayed motivated during their projects.

Teaching Assistant Illinois Institute of Technology (2015-2020)

• Mastered all course materials and helped students with learning.

• Evaluated assignments, project reports, and lab reports from students, liaising with professors on student progress.

• Educated students on lab materials for experiments and helped debug circuits/programs.

• Modules: AI in Smart Grid, RF Integrated Circuits, Application Software Design, Cyber Security, Embedded System and FPGA Design, Microcomputer and Embedded Computing, Computer Architecture, Embedded Digital Systems for Time-Frequency Distributions, Circuit Analysis, Engineering Electronics.

Research Student Argonne National Laboratory (2017-2018)

• Led the development of a reconfigurable and high-performance ultrasonic communication testbed platform using the ZYNQ APSoC (All Programmable System-on-Chip). The system consists of multiple functional blocks including: central controller, high-speed signal converters, power amplifier for transmission, low noise amplifier for receiving, and backend PC for overall control.

• Used machine learning algorithms to enhance communication robustness and performance by designing optimal deconvolutional channel equalizer.

RESEARCH PROJECTS

Reconfigurable Ultrasonic NDT System based on ZYNQ APSoC (2015-2019)

• Designed an ultrasonic NDT signal acquisition and processing platform based on all programmable SoC (APSoC). With the FPGA on the APSoC, the system is fully reconfigurable, and allows for real-time signal processing. Received award from the IEEE International Ultrasonics Symposium.

• The system can generate high voltage pulses for exciting ultrasonic transducers, receive low voltage ultrasonic backscattered echoes sampled at 250 MSPS, and process and transmit the acquired data to a host computer.

• Implemented hardware acceleration IP cores on FPGAs for real-time signal processing such as SSP and DWT with Xilinx design toolsets.

• Managed a high-speed data path on the FPGA to deserialize data from ADC, buffer and transmit data to the DDR memory with the help of a DMA.

• Programmed the ARM A9 processor on ZYNQ APSoC for overall system control. Project was awarded Best Student Paper at the 2019 IEEE International Ultrasonics Symposium.

Statistical Signal Analyzing and Processing based on Artificial Intelligence (2016-2019)

• Combined conventional signal processing algorithms and machine learning algorithms to optimize computation efficiency, ease of implementation, and algorithm accuracy.

• Utilized artificial intelligence algorithms for ultrasonic signal processing, adapted multilayer perceptron neural networks for grain size estimation and target echo detection.

• Implemented multilayer perceptron neural network in TensorFlow to detect MECG and FECG signals from the abdominal ECG signals acquired using non-invasive sensors.

Data Compression using Wavelet Packet Transform Optimized by Convolutional Autoencoder (2020)

• Built a Convolutional Autoencoder using wavelet packet transform architecture and transfer learning from the optimal mother wavelet coefficients.

• Models built with this method provided enhanced compression accuracy without affecting compression ratios.

• The algorithm was the first of its kind and demonstrated excellent performance on computation efficiency and compression performances.

OTHER PROEJCTS

Wearable sensor network for human gesture detection based on Artificial Intelligence (2019-2020)

• Created a wearable sensor network for human gesture detection based on AI.

• Helped design and implement an IoT based information collection and analysis system that combined multiple wearable and environmental sensors. Used this to obtain real-time posture data with labels.

• Designed and implemented sequential models for human gesture characterization.

A single Camera 3D microscope detail scanner (2019)

• Designed and implemented microscope deatail scanner.

• Helped design the image stiching and 3D texture reconstruction based on stereo matching.

AWARDS

• Sigma Xi/IIT Student Award for Excellence in University Research (2020)

• Student Paper Competition Winner in the 2019 IEEE International Ultrasonics Symposium (2019)

• Third prize of the 9th “Century Cup” Students’ Extracurricular Academic Science and Technology Works Competition of BIT (2012)

• Excellence Award in Field Rank Students’ Science and Technology Innovation Project (2011)

• First prize in Beijing college students’ Physical Experimental Contest (2010)

HOBBIES

• Jogging, Programming, Crafting

CERTIFICATIONS

• Machine Learning

• Neural Networks and Deep Learning

• Graph Search, Shortest Paths, and Data Structures

• Divide and Conquer, Sorting and Searching, and Randomized Algorithms

PUBLICATIONS

1. Pramod Govindan, Boyang Wang, Pingping Wu, Ivan Palkov, Vidya Vasudevan, and Jafar Saniie. Reconfigurable and programmable system-on-chip hardware platform for real-time ultrasonic testing applications. In 2015 IEEE International Ultrasonics Symposium (IUS), 1–4. IEEE, 2015. doi:10.1109/ULTSYM.2015.0341.

2. Pramod Govindan, Boyang Wang, Prashaanth Ravi, and Jafar Saniie. Hardware and software architectures for computationally efficient three-dimensional ultrasonic data compression. IET Circuits, Devices & Systems, 10(1):54–61, 2016. doi:10.1049/iet-cds.2015.0083.

3. Boyang Wang, Pramod Govindan, and Jafar Saniie. Performance analysis of system-on-chip architectures for ultrasonic data compression. In 2016 IEEE International Ultrasonics Symposium (IUS), 1–4. IEEE, 2016. doi:10.1109/ULTSYM.2016.7728507.

4. Vidya Vasudevan, Boyang Wang, Pramod Govindan, and Jafar Saniie. Design and evaluation of reconfigurable ultrasonic testing system. In 2015 IEEE International Conference on Electro/Information Technology (EIT), 310–313. IEEE, 2015. doi:10.1109/EIT.2015.7293359.

5. Boyang Wang, Pramod Govindan, Thomas Gonnot, and Jafar Saniie. Acceleration of ultrasonic data compression using opencl on gpu. In 2015 IEEE International Conference on Electro/Information Technology (EIT), 305–309. IEEE, 2015. doi:10.1109/EIT.2015.7293358.

6. Boyang Wang. Reconfigurable Ultrasonic Signal Processing System Solution Based on Zynq Platform. PhD thesis, Illinois Institute of Technology, 2015.

7. Boyang Wang and Jafar Saniie. Ultrasonic target echo detection using neural network. In 2017 IEEE International Conference on Electro Information Technology (EIT), 286–290. IEEE, 2017. doi:10.1109/EIT.2017.8053371.

8. Boyang Wang and Jafar Saniie. Ultrasonic flaw detection based on temporal and spectral signals applied to neural network. In 2017 IEEE International Ultrasonics Symposium (IUS), 1–4. IEEE, 2017. doi:10.1109/ULTSYM.2017.8091947.

9. Boyang Wang, Jafar Saniie, Sasan Bakhtiari, and Alexander Heifetz. Architecture of an ultrasonic experimental platform for information transmission through solids. In 2017 IEEE International Ultrasonics Symposium (IUS), 1–4. IEEE, 2017. doi:10.1109/ULTSYM.2017.8092176.

10. Boyang Wang and Jafar Saniie. Fetal electrocardiogram recognition using multilayer perceptron neural network. In 2018 IEEE International Conference on Electro/Information Technology (EIT), 0434–0437. IEEE, 2018. doi:10.1109/EIT.2018.8500232.

11. Won-Jae Yi, Boyang Wang, Bruno Fernandes dos Santos, Eduardo Fonseca Carvalho, and Jafar Saniie. Design flow of neural network application for iot based fall detection system. In 2018 IEEE International Conference on Electro/Information Technology (EIT), 0578–0582. IEEE, 2018. doi:10.1109/EIT.2018.8500179.

12. Boyang Wang, Jafar Saniie, Sasan Bakhtiari, and Alexander Heifetz. Software defined ultrasonic system for communication through solid structures. In 2018 IEEE International Conference on Electro/Information Technology (EIT), 0267–0270. IEEE, 2018. doi:10.1109/EIT.2018.8500306.

13. Jafar Saniie, Boyang Wang, and Xin Huang. Information transmission through solids using ultrasound invited paper. In 2018 IEEE International Ultrasonics Symposium (IUS), 1–10. IEEE, 2018. doi:10.1109/ULTSYM.2018.8579702.

14. A Heifetz, R Ponciroli, X Huang, Boyang Wang, Jafar Saniie, S Bakhtiari, and RB Vilim. Ultrasonic link model development. Technical Report, Argonne National Lab.(ANL), Argonne, IL (United States), 2018.

15. Boyang Wang, Jafar Saniie, Sasan Bakhtiari, and Alexander Heifetz. A high-performance communication platform for ultrasonic applications. In 2018 IEEE International Ultrasonics Symposium (IUS), 1–4. IEEE, 2018. doi:10.1109/ULTSYM.2018.8579697.

16. Boyang Wang, Jafar Saniie, Sasan Bakhtiari, and Alexander Heifetz. Ultrasonic communication systems for data transmission. In 2019 IEEE International Conference on Electro Information Technology (EIT), 1–4. IEEE, 2019. doi:10.1109/EIT.2019.8833734.

17. Alejandro Vazquez, Boyang Wang, Guojun Yang, and Jafar Saniie. A single-camera 3d microscope scanner with image stitching and stereo matching. In 2019 IEEE International Conference on Electro Information Technology (EIT), 404–409. IEEE, 2019. doi:10.1109/EIT.2019.8834144.

18. Alexander Heifetz, Jafar Saniie, Xin Huang, Boyang Wang, Dmitry Shribak, Eugene R Koehl, Sasan Bakhtiari, and Richard B Vilim. Final report for transmission of information by acoustic communication along metal pathways in nuclear facilities. Technical Report, Argonne National Lab.(ANL), Argonne, IL (United States), 2019.

19. Boyang Wang and Jafar Saniie. A high performance ultrasonic system for flaw detection. In 2019 IEEE International Ultrasonics Symposium (IUS), 840–843. IEEE, 2019. doi:10.1109/ULTSYM.2019.8926280.

20. Boyang Wang and Jafar Saniie. Multilayer perceptron neural networks for grain size estimation and classification. In 2019 IEEE International Ultrasonics Symposium (IUS), 1643–1646. IEEE, 2019. doi:10.1109/ULTSYM.2019.8925713.

21. Alexander Heifetz, Dmitry Shribak, Xin Huang, Boyang Wang, Jafar Saniie, Jacey Young, Sasan Bakhtiari, and Richard B Vilim. Transmission of images with ultrasonic elastic shear waves on a metallic pipe using amplitude shift keying protocol. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 67(6):1192–1200, 2020. doi:10.1109/TUFFC.2020.2968891.

22. Saumya Gupta, Boyang Wang, Won-Jae Yi, and Jafar Saniie. Design flow of wireless body sensor network for human activity classification using long short-term memory (lstm) neural network. In 2020 IEEE International Conference on Electro Information Technology (EIT), 166–170. IEEE, 2020. doi:10.1109/EIT48999.2020.9208248.

23. Boyang Wang and Jafar Saniie. Learning fir filter coefficients from data for speech-music separation. In 2020 IEEE International Conference on Electro Information Technology (EIT), 245–248. IEEE, 2020. doi:10.1109/EIT48999.2020.9208237.

24. Kaizhen Wei, Boyang Wang, and Jafar Saniie. Faster region convolutional neural networks applied to ultrasonic images for breast lesion detection and classification. In 2020 IEEE International Conference on Electro Information Technology (EIT), 171–174. IEEE, 2020. doi:10.1109/EIT48999.2020.9208264.

25. Andrew Newman, Guojun Yang, Boyang Wang, David Arnold, and Jafar Saniie. Embedded mobile ros platform for slam application with rgb-d cameras. In 2020 IEEE International Conference on Electro Information Technology (EIT), 449–453. IEEE, 2020. doi:10.1109/EIT48999.2020.9208310.

26. Yann Hornych, Javier Cañada Toledo, Boyang Wang, Won-Jae Yi, and Jafar Saniie. Near-ultrasonic communications for iot applications using android smartphone. In 2020 IEEE International Conference on Electro Information Technology (EIT), 407–410. IEEE, 2020. doi:10.1109/EIT48999.2020.9208265.

27. A Heifetz, D Shribak, X Huang, B Wang, J Saniie, R Ponciroli, ER Koehl, S Bakhtiari, and RB Vilim. Transmission of images on high-temperature nuclear-grade metallic pipe with ultrasonic elastic waves. Nuclear Technology, pages 1–13, 2020.

28. B. Wang, J. Saniie, S. Bakhtiari, and A. Heifetz. Ultrasonic communication in solid channels using ofdm. In 2020 IEEE International Ultrasonics Symposium (IUS), volume, 1–3. 2020. doi:10.1109/IUS46767.2020.9251540.

29. X. Zhang, B. Wang, and J. Saniie. Deep convolutional neural networks applied to ultrasonic images for material texture recognition. In 2020 IEEE International Ultrasonics Symposium (IUS), volume, 1–3. 2020. doi:10.1109/IUS46767.2020.9251734.