Research Assistant Professor Department of Mechanical and Energy Engineering

Tongda Zhang received his Ph.D. degree in Electrical Engineering of Stanford in 2016 with a focus of data mining, machine learning based human behavior understanding. In 2011, He graduated as the Outstanding Graduates from Tsinghua University with a Bachelor degree of Automation and obtained his Master degree in Electrical Engineering at Stanford University in 2013. In Stanford University, Dr. Zhang has worked in several labs and research centers at Stanford, such as PBL Lab (Problem/Project/Product/Process/People Based Learning Lab), AIR Lab (Ambient Intelligence Research Lab), CDR (The Center for Design Research) CARS and CHIME Lab (Communication between Humans and Interactive Media Lab). As a research assistant, he participated in many research projects including “Brain wave analysis based human mental behavior understanding during international meetings”, “Sensor topology modeling and analysis, hotspot modeling based human behavior capturing” and “Auto driving simulation course’s design and establishment”. He founded several companies as a primary partner. His future research will mainly focus on data mining and machine learning based pattern recognition and understanding regarding intelligent environment, fin-tech, industrial engineering.

Personal Profile


◆ Data mining and machine learning based pattern recognition and understanding

◆ Artificial intelligence based system modeling and optimization

◆ Big data based manufacturing system performance analysis and decision making

Publications Read More

◆ [Journal Paper] Tongda, Zhang, R., Fruchter and M., Frank, “Are They Paying Attention? A Model-Based Method to Identify Individuals’ Mental States”, Computer, IEEE, 2017(

◆ [Dissertation] Zhang, Tongda. Pattern Learning in Smart Homes and Offices Using Motion Sensor and Mind Wave Data: Unsupervised Approaches. Diss. Stanford University, 2016.(

◆ [Journal Paper] Tongda Zhang, W. Fu, J. Ye, and M. Fischer, “Learning movement patterns of the occupant in smart home environments: an unsupervised learning approach.”, Journal of Ambient Intelligence and Humanized Computing:1-14 2016 (

◆ [Book Chapter] Mohamed E., Tongda Zhang, Wilfried Philips and Hamid Aghajan, A Data Fusion Approach for Identifying Lifestyle Patterns in Elderly Care, Active and assisted living: technologies and applications, ISBN:978-1-84919-987-2, IET 2016(

◆ [Journal Paper] Sun Xiao, Tongda Zhang, Yueting Chai and Yi Liu, “Localized Ambient Solidity Separation (LASS) Algorithm Based Computer User Segmentation”, Computational Intelligence and Neuroscience,2015,Volume 2015 (2015), Article ID 829201 (

◆ [Conference Paper] Johns, M., Miller, D.B., Sun, A.C., Baughman, S., Zhang, T., & Ju, W. “The Driver has Control: Exploring Driving Performance with Varying Automation Capabilities”, Proc. Driving Assessment 15 June 22-25, 2015 Salt Lake City, UT(

◆ [Journal Paper] Tongda Zhang, Xiao Sun, Yueting Chai and Hamid Aghajan, “A look at task-switching and multi-tasking behaviors: From the perspective of the computer usage among a large number of people”, Computers in Human Behavior}, 2015, DOI: 10.1016/j.chb.2015.03.012 (

◆ [Journal Paper] Tongda Zhang, K.B. Wong and Hamid Aghajan, “Concurrent activation events based trajectory propagation in smart environments ”, Journal of Ambient Intelligence and Humanized Computing, Springer, 2014, DOI: 10.1007/s12652-014-0240-0 (

◆ [Book Chapter] K.B. Wong, Tongda Zhang, and Hamid Aghajan, “Data Fusion with a Dense Sensor Network for Anomaly Detection in Smart Homes”, Human Behavior Understanding in Networked Sensing, Springer, ISBN:978-3-319-10806-3 (Print) 978-3-319-10807-0 (Online), 2014(

◆ [Journal Paper] Tongda Zhang, Xiao Sun, Yueting Chai and Hamid Aghajan, “Human Computer Interaction Activity Based User Identification ”, International Journal of Machine Learning and Computing, Vol. 4, No. 4, August 2014. DOI: 10.7763/IJMLC.2014.V4.436 (

◆ [Journal Paper] K.B. Wong, Tongda Zhang, and Hamid Aghajan, “Extracting Patterns of Behavior from a network of Binary Sensors”, Journal of Ambient Intelligence and Humanized Computing, Springer}, 2014, DOI:10.1007/s12652-014-0246-7 (

◆ [Book Chapter] K.B. Wong, Tongda Zhang, and Hamid Aghajan, “Inference of Wellness Indicators and Patterns of Behavior in Elderly Care Applications using Long-Term Sensor Network Observations”, Sensor Networks for Sustainable Development, CRC Press}, ISBN:9781466582064, 2014(

◆ [Journal Paper] Tongda Zhang, Haomiao Jiang, Zhouxiao Bao, and Yingfeng Zhang, “Characterization and Edge Sign Prediction in Signed Networks,” Journal of Industrial and Intelligent Information, Vol. 1, No. 1, pp. 19-24, March 2013. doi: 10.12720/jiii.1.1.19-24(

◆ [Journal Paper] Zhang, Y., Xu, F., Zhang, Tongda. and Wu, C., “Application of electro-mechanical impedance sensing technique for online aging monitoring of rubber” Intelligent Automation & Soft Computing,18.8 (2012): 1101-1109(

◆ [Book Chapter] Zhang, Yuxiang, Liuyi Ma, Tongda Zhang, and Fuhou Xu, “Tracking of Human Arm Based on MEMS Sensors”, Computer and Computing Technologies in Agriculture IV, pp. 597-606. Springer Berlin Heidelberg, 2011 DOI:10.1007/978-3-642-18336-2-73 ISBN:9783642183355(

◆ [Conference Paper] Tongda Zhang, Liuyi Ma “Natural interaction technology based on the union of hand and writing-pen”, The 1st International Conference on Computer Technology and Application and Computer Education of the University and college (ICTAE 2010)2010

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