个人简历

工作经历：
11/2018，南方科技大学机械与能源工程系，研究助理教授
12/2017 创始人 矩阵未来（北京）科技有限公司
公司由中信集团百万人民币投资并由中信双创孵化，公司主要方向聚焦于大数据分析、整合和量化决策生成技术的研发，并将该技术应用于能源和中小企业征信等不同垂直传统行业的现有场景
09/2014--04/2016 研究助理, PBL Lab (Problem/Project/Product/Process/People Based Learning Lab), 斯坦福大学
使用Neurosky收集的真实国际会议的参与者的脑电波数据构建了心理工作负荷的混合高斯模型（mental workload gaussian mixture model）；并使用该模型完成了对国际会议参与者的群体心理行为的可视化研究与解读
06/2015--09/2015 软件工程师, 谷歌[X]实验室（Google[x]） 美国加州硅谷
参与了谷歌热全球网络计划（Project Loon）
02/2013--09/2015 研究助理, AIR实验室 (Ambient Intelligence Research Lab), 斯坦福大学（Stanford University）
主要研究方向为基于PIR传感器网络的人类行为轨迹以及行为热点建模分析，生活模式提取和解读，异常事件检测与预警
02/2014–06/2014 研究助理, CDR(The Center for Design Research), 斯坦福大学（Stanford University）
设计并参与自动驾驶汽车的驾驶员心理研究课题（Auto Driving Car Project）, 基于EEG和眼球追踪数据对人在自动驾驶模拟器中的行为反应时间序列进行建模和解读。
06/2013--02/2014 研究助理, DPR Construction. 美国加州硅谷
基于RFID打卡数据的建筑工地多个项目方效率评估分析系统的研究和搭建，并使用该系统完成了对旧金山大学医院建筑项目的来自上百个承包商的建筑工人的效率跟踪和评估
06/2013--12/2013 研究助理, CHIME Lab(Communication between Humans and Interactive Media Lab), 斯坦福大学
参与并负责了“丰田自动驾驶司机行为研究（Toyota Automation Driving Study）”项目，设计并搭建了全球首个360度屏幕丰田自动驾驶行为研究原型和模拟轨道
02/2013–06/2013 研究助理, PBL Lab (Problem/Project/Product/Process/People Based Learning Lab), 斯坦福大学
通过使用FitBit、Neurosky和Kinect收集了跨国远程会议多个参与方的心率、脑电波和上半身行为时间同步数据；并使用收集的数据构建了参会者的参会效率、专注度和参与程度评估模型

学习经历：
2016年3月，美国斯坦福大学电子工程专业，博士。
2013年6月，美国斯坦福大学电子工程专业，硕士。
2011年6月，清华大学自动化专业, 学士

研究领域

基于数据挖掘和机器学习的行为识别与理解
基于人工智能的系统建模与优化
基于大数据的制造系统关系性能分析与决策

近期论文

Tongda, Zhang, R., Fruchter and M., Frank, “Are They Paying Attention? A Model-Based Method to Identify Individuals' Mental States”, Computer, IEEE, 2017(http://ieeexplore.ieee.org/abstract/document/7888422/)

Zhang, Tongda. Pattern Learning in Smart Homes and Offices Using Motion Sensor and Mind Wave Data: Unsupervised Approaches. Diss. Stanford University, 2016.(https://searchworks.stanford.edu/view/11616852)
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 (http://link.springer.com/article/10.1007/s12652-016-0367-2)

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(http://www.theiet.org/resources/books/healthcare/acassliving.cfm)

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 (http://dx.doi.org/10.1155/2015/829201)

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(http://drivingassessment.uiowa.edu/sites/default/files/DA2015/papers/060.pdf)
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 (http://www.sciencedirect.com/science/article/pii/S0747563215001983)
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 (http://link.springer.com/article/10.1007\\%2Fs12652-014-0240-0)

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(http://link.springer.com/book/10.1007\\%2F978-3-319-10807-0)
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 (http://www.ijmlc.org/papers/436-M0013.pdf)
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 (http://link.springer.com/article/10.1007/s12652-014-0246-7)

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(http://www.crcpress.com/product/isbn/9781466582064)
Tongda Zhang, Haomiao Jiang, Zhouxiao Bao, and Yingfeng Zhang, \