Wenjin Tao Ph.D.
Mechanical Engineering, Robotics, Industrial AI

LinkedIn / Google Scholar / GitHub

Biography

Dr. Wenjin Tao is the Technical Product Lead/Mechanical Engineer at Foxconn iAI leading efforts on exploring smart manufacturing technologies and delivering transformative solutions from 0-1 to solve previously unsolvable problems to meet business needs.

He received his PhD degree in the Innovative Smart & Additive Manufacturing (ISAM) Laboratory at Missouri University of Science and Technology, advised by Prof. Ming C. Leu. During his PhD study, he was focusing on smart manufacturing system boosted by deep learning & artificial intelligence. His research interests include smart manufacturing, Cyber-Physical System (CPS), Additive Manufacturing (AM) and design optimization.

Before he joined Missouri S&T, he received his Master and Bachelor degrees in Mechanical Engineering at Beijing Inistitute of Technology.

He is a recipient of 2018 IISE DAIS Track Best Paper Award. He has been a student member of IEEE, IISE and SIAM. Meanwhile, he is a lifelong learner, DIY enthusiast, and passionate about all kinds of new technology like flying car, self-driving car, etc.

Interests

  • Robotics
  • Machine Learning and Deep Learning for Human-Centered Intelligent Manufacturing
  • Time-Series Signal/Image Recognition
  • Time-Frequency/Spatial-Temporal Data Analysis
  • Artificial Intelligence

Education

  • Ph.D. in Mechanical Engineering
    Missouri University of Science and Technology
  • M.S. in Mechanical Engineering
    Beijing Institute of Technology
  • B.S. in Mechanical Engineering
    Beijing Institute of Technology

R&D Projects

Field Robotics

This game-changing robotic platform employs self-driving technology and zero-emission power solutions to reduce labor and fuel costs, increase margins, and minimise the carbon footprint. The platform supports a variety of specialized tool attachments that fits field tasks year-round, such as lawn mowing, weed control, snow removal, salt spreading, and more.

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Low-Cost Ventilator Prototype

This project is to develop a low-cost ventilator in response to this COVID-19 pandemic. The goal is to contribute to the society, show our capability, and build up the platform for future AI functions with potential business. The ventilator has the properties: low-cost, standard parts should be accessible without quoting, customized parts should be printable by a 3D printer, and easy to assemble.

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Mask Defect Detection and Sorting System

This is an automated quality control solution that uses computer vision and machine learning to inspect face masks in real-time. It detects various defects and automatically sorts masks into pass/fail categories, improving inspection efficiency while maintaining quality records for production tracking.

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Pin Defect Detection System

This project utilizes deep learning algorithms to detect bent pins among thousands of pins in electronic components. The system automatically identifies and marks defective pin locations while triggering alerts for quality control. Additionally, it allows comprehensive quality traceability throughout the manufacturing process.

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FOLO: Human Operation Instruction, Digitization and Optimization

FOLO provides on-site smart work instructions for operators to follow. Engineers can create SOPs in a process builder by drag and drop. It records critical production data, and is able to connect external hardware.

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OPTIMO: AI Powered Software that Digitizes Human Operations for Performance Measurements and Optimization

Optimo implements an end-to-end industrial vision system that streams and stores IP camera feeds, enabling real-time monitoring, time-motion analysis, and AI model development. The modular platform includes a dashboard for visualization and analytics to optimize industrial operations.

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Worker Activity Recognition Using IMU and sEMG Signals with Convolutional Neural Networks

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In a smart manufacturing system involving workers, recognition of the worker’s activity can be used for quantification and evaluation of the worker’s performance, as well as to provide onsite instructions with augmented reality. In this paper, we propose a method for activity recognition using Inertial Measurement Unit (IMU) and surface electromyography (sEMG) signals obtained from a Myo armband.

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This research work is supported by the National Science Foundation grant CMMI-1646162 and also by the Intelligent Systems Center at Missouri University of Science and Technology.

Multi-View Recognition of Complex Hand Gesture

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  • Considering the challenges of the ASL alphabet recognition task, we choose CNN as the basic model to build the classifier because of its powerful learning ability that has been shown
  • To fully exploit the 3D information provided by depth images, we develop a novel multi-view augmentation strategy. It generates more views from different perspectives, in order to augment the perspective variations that cannot be achieved using traditional image augmentation methods
  • To solve the interclass similarity issues caused by perspective variations and partial occlusions, we first make predictions for all individual views and then fuse information from them for the final prediction
  • Design and develop a real-time demo of American Sign Language (ASL) alphabet recognition [demo]
  • Establish and Publish a dataset of ASL alphabet [dataset]

American Sign Language Alphabet Recognition Using Leap Motion Controller

Design of Lattice Structure for Additive Manufacturing

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Additive Manufacturing (AM) technology provides new opportunities to automatically and flexibly fabricate parts with complicated shapes and architectures that could not be produced by conventional manufacturing processes, thus enabling unprecedented design flexibilities and application opportunities.

The lattice structure possesses many superior properties to solid material and conventional structures. It is able to integrate more than one function into a physical part, which makes it attractive to a wide range of applications. With AM technology the lattice structure can be fabricated by adding material layer-by-layer directly from a Computer-Aided Design (CAD) model, rather than the conventional processes with complicated procedures.

AM lattice structures have been intensively studied for more than ten years with significant progress having been made. This paper reviews and discusses AM processes, design methods and considerations, mechanical behavior, and applications for lattice structures enabled by this emerging technology.

Design of Lattice Structure for Additive Manufacturing

Design of Lattice Structure for Additive Manufacturing

Other Projects

I think getting hands dirty is the best way to learn. Here lists some interesting projects I’ve done.

Robotics

Self-Driving Car

Semantic Segmentation

Semantic Segmentation

Semantic Segmentation

Semantic Segmentation

Semantic Segmentation

Semantic Segmentation

Deep Learning

Flying Car

Artificial Intelligence

Publications

Journal Papers

  1. Tao, W., Lai, Z. H., Leu, M. C., Yin, Z., & Qin, R. (2019). A Self-Aware and Active-Guiding Training System for Worker-Centered Intelligent Manufacturing. Manufacturing Letters. (Accepted)
  2. Tao, W., Leu, M. C., & Yin, Z. (2019). Multi-Modal Recognition of Worker Activity for Human-Centered Intelligent Manufacturing. (Submitted to the Journal of Manufacturing Systems)
  3. Tao, W., Moniruzzaman, M., Leu, M. C., Yin, Z., & Qin, R. (2019). Attention-Based Sensor Fusion for Human Activity Recognition Using IMU Signals. (Submitted to the journal of Information Fusion)
  4. Lai, Z. H., Tao, W.*, Leu, M. C., & Yin, Z. (2019). Smart Augmented Reality Instructional System for Mechanical Assembly Towards Worker-Centered Intelligent Manufacturing. (Submitted to the Journal of Manufacturing Systems)
  5. Tao, W., Leu, M.C. and Yin, Z., 2018. American Sign Language alphabet recognition using Convolutional Neural Networks with multiview augmentation and inference fusion. Engineering Applications of Artificial Intelligence, 76, pp.202-213. Preprint Cite
  6. Shen, J., Li, G., Yan, W., Tao, W., Xu, G., Diao, D., & Green, P. (2018). Nighttime driving safety improvement via image enhancement for driver face detection. IEEE Access, 6, 45625-45634.
  7. Wei, C., Chen, G., Luan, Z., Tao, W.* (2016). Optimization on the Hydrodynamic Groove Geometry of Rotary Seals for Automotive Transmissions. Transactions of Beijing Institute of Technology 36 (1), 25-30.
  8. Qiao, J., Tao, W., & Sun, B. (2012). Design for the Braking System of a FSAE Racing Car [J]. Chinese Journal of Automotive Engineering, 2.
  9. Wei, W., Tao, W., & Yan, Q. (2010). Exploratory discussion on virtual laboratory teaching information platform system based on visual simulation technique. Experimental Technology and Management, 27(3), 78-81.

Peer-Reviewed Conference Papers

  1. Al-Amin, M., Tao, W., Doell, D., Lingard, R., Yin, Z., Leu, M. C., & Qin, R. (2019, August). Action Recognition in Manufacturing Assembly using Multimodal Sensor Fusion. 25th International Conference on Production Research Manufacturing Innovation: Cyber Physical Manufacturing, August 9–14, 2019 Chicago, Illinois, USA.
  2. Tao, W., Lai, Z.H., Leu, M.C. and Yin, Z., 2018. Worker Activity Recognition in Smart Manufacturing Using IMU and sEMG Signals with Convolutional Neural Networks. Procedia Manufacturing, 26, pp.1159-1166. Preprint Project Cite
  3. Tao, W., Lai, Z.H., Leu, M.C. and Yin, Z., 2018. American Sign Language Alphabet Recognition Using Leap Motion Controller (IISE Annual 2018, Data Analytics & Information Systems Division Best Track Paper Award) Preprint Project
  4. Wu, S., Tao, W.*, Leu, M. C., & Long, S. (2018). Engine Sound Simulation and Generation in Driving Simulator. In Proceedings of the 2018 Institute of Industrial and Systems Engineers Annual Conference (IISE 2018).
  5. Al-Amin, M., Qin, R., Tao, W., & Leu, M. C. (2018, January). Sensor Data Based Models for Workforce Management in Smart Manufacturing. In Proceedings of the 2018 Institute of Industrial and Systems Engineers Annual Conference (IISE 2018).
  6. Hu, L., Nguyen, N.T., Tao, W.*, Leu, M.C., Liu, X.F., Shahriar, M.R. and Al Sunny, S.N., 2018. Modeling of cloud-based digital twins for smart manufacturing with MT connect. Procedia Manufacturing, 26, pp.1193-1203.
  7. Tao, W., Liu, Y., Sutton, A., Kolan K. and Leu, M.C., 2018. Design of Lattice Structures with Graded Density Fabricated by Additive Manufacturing. Preprint
  8. Tao, W., & Leu, M. C. (2016, August). Design of lattice structure for additive manufacturing. In 2016 International Symposium on Flexible Automation (ISFA) (pp. 325-332). IEEE.

Books & Book Chapters

  1. NX 12 for Engineering Design. Leu, M. C., Tao, W.*, Ghazanfari, A., & Kolan, K. (2017). Department of Mechanical and Aerospace Engineering, Missouri University of Science and Technology. eBook
  2. Manufacturing Assembly Simulations in Virtual and Augmented Reality. Tao, W., Lai, Z. H., & Leu, M. C. (2018). Augmented, Virtual, and Mixed Reality Applications in Advanced Manufacturing. Accepted Draft
  3. Virtual Bone Surgery. Leu, M. C., Tao, W., Niu, Q., & Chi, X. (2018). In Virtual Prototyping & Bio Manufacturing in Medical Applications (2nd Edition). Springer, Boston, MA under review

Patents

  1. A Novel Method for Analyzing the Wear of Rotary Seal with Micro-textured Contacting Surface. Wei, C., Zhao, Y., Hu, J., Yuan, S., & Tao, W. (2015). CN104679990A
  2. A Novel Optimization Method for Designing of Rotary Seal in Automotive Transmission. Wei, C., Hu, J., Tao, W., & Chen, G. (2014). CN103955581A
  3. A Novel Rotary Seal with Wavy Contacting Surface for Automotive Transmissions. Hu, J., Tao, W., Yuan, S., & Wei, C. (2012). CN102797854A
  4. A Self-adaptive Deformable Wing for Racing Cars. Xiang, C., Xu, B., Tao, W., & Lou, R. (2011). CN102248968B

Google Scholar for a full list.

Teaching & Mentoring Experience

I am a teaching instructor for the following courses at Missouri University of Science and Technology

  • Fall 2018: ME 5763: Computer Aided Design: Theory and Practice / Course Site / Book / YouTube Channel / Vimeo
  • Fall 2017: ME 5763: Principles And Practice Of Computer Aided Design
  • Fall 2016: ME 5763: Principles And Practice Of Computer Aided Design

Invited Talk

  • Human Behavior Understanding for Worker-Centered Intelligent Manufacturing. Xi’an University of Technology, Dec. 2018

Reviews

Active Reviewer for

Publons Profile

Honors & Awards

  • Data Analytics & Information Systems Division Best Track Paper Award, IISE Annual 2018
  • NSF Travel Grant, IISE Annual conference, 2018
  • NSF Travel Grant, ISFA conference, 2016
  • Award in the Innovation Cup of Science Popularization, 2012
  • Outstanding Student Leader in the School of Mechanical Engineering at BIT, 2012
  • The Final Champion in 2011 Formula Student Competition China, 2011
  • Qualification Certificate of Automotive Specialized Technique by SAE of China, 2011
  • The Final Champion in 2010 Formula Student Competition China, 2010
  • Beijing Outstanding Graduate, 2010
  • The First Prize of FAST Scholarship, 2010
  • The DEC Scholarship, 2010
  • National Scholarship, 2009
  • The University Award for 6 times at BIT, 2006-2010

Service Activities

Miscellaneous