个人简介

肖峰系西南财经大学人工智能与管理科学研究中心主任，大数据研究院副院长，教授、博士生导师、国家杰出青年基金、国家自然科学基金优秀青年基金获得者，入选国家级青年人才，四川省学术和技术带头人。研究方向主要包括人工智能算法与数据挖掘、复杂交通系统建模优化、金融风控与量化交易、区块链等。先后主持和参与了NSFC-RGC香港-内地联合基金，国家重点研发计划，NSFC-广东大数据科学中心项目等10余项重要国家和省部级课题。在管理科学与工程、交通科技及数据挖掘领域著名国际期刊和会议如Transportation Science，Transportation Research Part A、B、C、D、E, IEEE TKDE、ISTTT等发表论文70余篇。研究团队与香港科技大学，香港理工大学，美国加州大学伯克利分校、戴维斯分校，加拿大多伦多大学，英国利兹大学，清华大学等国内外著名高校保持着密切合作和访学交流关系。

教育背景

美国加州大学戴维斯分校，土木与环境工程系，博士后，2007-2011

香港科技大学，土木工程交通工程专业, 2004-2007，博士

清华大学，土木工程交通工程专业, 2001-2004，硕士

清华大学，土木工程结构工程,1997-2001，学士

科学研究

进行中项目：

n 项目主持人，国家杰出青年科学基金资助项目（72025104）：城市交通系统博弈建模与定价优化，280万，2021~2025;

n 参与，国家重点研发计划“综合交通运输与智能交通”专项（2018YFB1600902）：可计算城市多模式交通网络模型及承载能力分析方法，40万，2019~2021;

n 项目主持人，NSFC-广东大数据科学中心项目（U1811462）课题三：构建地方金融运行动态及区域性系统性风险等智能监测与预警系统，400万，2019~2022；

n 项目主持人，国家自然科学基金国际(地区)合作与交流项目NSFC-RGC (内地-香港)（71861167001）：基于网约车平台数据和人工智能算法的乘客流动性分析，100万，2019~2022；

n 项目主持人，四川省应用基础研究面上项目（2018JY0254）：基于城市交通多源数据与人工智能算法的居民出行特征分析，10万，2018-2019；

已结题项目：

n 项目主持人，国家自然科学基金优秀青年科学基金项目（71622007）：交通系统建模与管理优化，130万，2017~2019（结题后评估：优秀）；

n 子课题负责人，国家自然科学基金重点项目（71431003）：低碳导向型城市交通系统优化与管理，230万，2015-2019；

n 项目主持人，中央高校基本科研业务费创新团队项目（JBK170501）：城市交通数据挖掘与智能决策，30万，2017~2019；

n 子课题负责人，国家社科基金重大项目（13&ZD175）：城市地铁系统脆弱性评价及控制策略研究，80万，2014～2018；

n 项目主持人，成都恒图科技有限责任公司，基于端对端（End-to-end）循环神经网络算法的医疗语音识别，2017；

n 项目主持人，山东省城市商业银行联盟，基于深度学习的银行账户交易风险预警系统，2018；

n 项目主持人，成都市科技惠民技术研发项目：基于手机信令数据的成都市交通出行分析系统，20万，2017~2018；

n 项目主持人，山东省城市商业银行联盟，基于机器学习算法的银行卡磁条交易风险控制模型，2017；

n 项目主持人，成都市创新环境优化工程软科学研究项目：基于视频识别的人群集会风险评估与控制策略研究，2016.01-2016.12；

n 项目主持人，国家博士点基金项目（新教师类，20120184120017）：具有信用评分机制的出租车派送系统研究，2013～2015；

n 项目主持人，国家自然科学基金青年科学基金项目（71201135）：基于可交易信用证券的道路拥堵收费模型和缓堵策略研究，2013～2015 （结题后评估：特优）；

n 项目主持人，中央高校科研业务费科技创新项目：逐日动态交通流建模及其优化控制问题，2014-2015；

n 项目主持人，四川省应用基础计划项目（2013JY0037）：以出租车智能派送系统为核心的LBS交互式移动平台，2013～2014；

n 项目主持人，中央高校专题研究项目（SWJTU11ZT12）：城市绿色交通规划理论与系统设计，2011~2013；

n 项目主持人，深圳市龙岗区货运OD矩阵反推及预测，2011；

n Credit-based pricing on multi-class network. 加州大学戴维斯分校可持续发展交通研究中心项目, April 2010-April 2011. $12,000.

n The optimal coarse toll for heterogeneous commuters in the morning commute. 加州大学戴维斯分校可持续发展交通研究中心项目, April 2009-April 2010. $12,000.

n Evaluation of I-5 closure in downtown Sacramento. 美国加州政府交通部项目. May 2008-Jan 2009. $249,988.

n Provision of road capacity through privately built roads: capacity, pricing and competition issues. 美国加州政府交通部创新项目基金, Jan.01-Dec.31, 2008. $25,000.

n Evaluation and comparison of different strategies for Fifth Street Corridor Improvement. 加州大学戴维斯分校可持续发展交通研究中心项目, 2008. $12,000.

n 九广西铁与周边公交系统的整合研究, 2007;

n Lung Yuk Tau 12A 住宅小区交通影响分析, 2007;

n 大连软件园二期交通影响分析, 2007.

研究成果

[1] Zhang, D., Xiao, F., Kou, G., Luo, J. and Yang, F., 2023. Learning Spatial-Temporal Features of Ride-Hailing Services with Fusion Convolutional Networks. Journal of Advanced Transportation, 2023.

[2] Wan, Y., Xiao, F. and Zhang, D., 2022. Early-stage phishing detection on the Ethereum transaction network. Soft Computing, pp.1-13.

[3] Yan, X., Kou, G., Xiao, F., Zhang, D. and Gan, X., 2022. Region-based demand forecasting in bike-sharing systems using a multiple spatiotemporal fusion neural network. Soft Computing, pp.1-14.

[4] Liu, X., Yang, H. and Xiao, F., 2022. Equilibrium in taxi and ride-sourcing service considering the use of e-hailing application. Transportmetrica A: Transport Science, 18(3), pp.659-675.

[5] Li, P., Tian, L., Xiao, F. and Zhu, H., 2022. Can day-to-day dynamic model be solved analytically? New insights on portraying equilibrium and accommodating autonomous vehicles. Transportation research part B: methodological, 166, pp.374-395.

[6] Feng, S., Ke, J., Xiao, F. and Yang, H., 2022. Approximating a ride-sourcing system with block matching. Transportation Research Part C: Emerging Technologies, 145, p.103920.

[7] Fan, W., Tang, Z., Ye, P., Xiao, F. and Zhang, J., 2022. Deep Learning-Based Dynamic Traffic Assignment With Incomplete Origin–Destination Data. Transportation Research Record, p.03611981221123805.

[8] Zhang, Z., Zhai, G., Xie, K. and Xiao, F., 2022. Exploring the nonlinear effects of ridesharing on public transit usage: A case study of San Diego. Journal of Transport Geography, 104, p.103449.

[9] Fan, W. and Xiao, F., 2022. Managing bottleneck congestion with tradable credits under asymmetric transaction cost. Transportation Research Part E: Logistics and Transportation Review, 158, p.102600.

[10] Dapeng, Z. and Xiao, F., 2021. Dynamic auto-structuring graph neural network: a joint learning framework for origin-destination demand prediction. IEEE Transactions on Knowledge and Data Engineering.

[11] Xiao, F. and Ke, J., 2021. Pricing, management and decision-making of financial markets with artificial intelligence: introduction to the issue. Financial Innovation, 7, pp.1-3.

[12] Wang, Z., Safdar, M., Zhong, S., Liu, J. and Xiao, F., 2021. Public preferences of shared autonomous vehicles in developing countries: a cross-national study of Pakistan and China. Journal of Advanced Transportation, 2021, pp.1-19.

[13] Kou, G., Yang, P., Peng, Y., Xiao, H., Xiao, F., Chen, Y. and Alsaadi, F.E., 2021. A cross-platform market structure analysis method using online product reviews. Technological and Economic Development of Economy, 27(5), pp.992-1018.

[14] Chen, X.M., Chen, X., Zheng, H. and Xiao, F., 2021. Efficient dispatching for on-demand ride services: Systematic optimization via Monte-Carlo tree search. Transportation Research Part C: Emerging Technologies, 127, p.103156.

[15] Tu, W., Xiao, F., Li, L. and Fu, L., 2021. Estimating traffic flow states with smart phone sensor data. Transportation research part C: emerging technologies, 126, p.103062.

[16] Li, L., Lo, H.K., Huang, W.* and Xiao, F., 2021. Mixed bus fleet location-routing-scheduling under range uncertainty. Transportation Research Part B 146, 155-179.

[17] Yang, H.T.*, Zhang, Z.L., Fan, W.B. and Xiao, F., 2021. Optimal Design for Demand Responsive Connector Service Considering Elastic Demand. IEEE Transactions on Intelligent Transportation Systems. doi: 10.1109/TITS.2021.3054678.

[18] Liu, X.H., Yang, H.T.* and Xiao, F., 2021. Equilibrium in Taxi and Ride-sourcing Service Considering the Use of E-hailing Application. Transportmetrica A: Transport Science, 1-22.

[19] Zhong, S.P., Gong, Y.H., Zhou, Z.J., Cheng, R. and Xiao, F.*, 2021. Active learning for multi-objective optimal road congestion pricing considering negative land use effect. Transportation Research Part C 125, 103002.

[20] Ye, H.B., Xiao, F.*, Yang, H., 2021. Day-to-day dynamics with advanced traveler information. Transportation Research Part B 144, 23-44.

[21] Zhang, D.P., Xiao, F.*, Shen, M.Y. and Zhong, S.P., 2021. DNEAT: A Novel Dynamic Node-Edge Attention Network for Origin-destination Demand Prediction. Transportation Research Part C 122, 102851.

[22] Yan, X., Kou, G., Xiao, F., Zhang, D. and Gan, X., 2020. Demand Forecasting in Bike-sharing Systems Based on A Multiple Spatiotemporal Fusion Network. arXiv preprint arXiv:2010.03027.

[23] Yan, X., Kou, G., Xiao, F., Zhang, D. and Gan, X., 2020. Predicting Hourly Demand in Station-free Bike-sharing Systems with Video-level Data. CoRR.

[24] Liu, X., Ding, Y.*, Tang, H. and Xiao, F., 2020. A data mining-based framework for the identification of daily electricity usage patterns and anomaly detection in building electricity consumption data. Energy and Buildings, 110601.

[25] Ke, J.T., Xiao, F.*, Yang, H. and Ye, J.P., 2020. Learning to delay in ride-sourcing systems: a multi-agent deep reinforcement learning framework. IEEE Transactions on Knowledge and Data Engineering. doi: 10.1109/TKDE.2020.3006084.

[26] Chen, Jia; Kou, Gang; Peng, Yi; Chao, rui; Xiao, Feng; Alsaadi, Fawaz E，2020. Effect of Marketing Messages and Consumer Engagement on Economic Performance: Evidence from Weibo. Internet Research. https://doi.org/10.1108/INTR-07-2019-0296.

[27] Gan Wan, Gang Kou*, Tie Li, Feng Xiao, Yang Chen, 2020. Pricing policies in a Retailer Stackelberg O2O green supply chain. Sustainability 12(8), 3236.

[28] Sun, J., Wu, J.Y., Xiao, F., Tian, Y.*, Xu, X.D., 2020. Managing Bottleneck Congestion with Incentives. Transportation Research Part B 134, 143-166.

[29] Kou, G., Yang, P., Peng, Y., Xiao, F., Chen, Y., Alsaadi, F. E., 2019. Evaluation of feature selection methods for text classification with small datasets using multiple criteria decision-making methods. Applied Soft Computing 86, 105836.

[30] Li, L., Lo, H.K.*, Xiao, F., 2019. Mixed Bus Fleet Scheduling under Range and Refueling Constraints. Transportation Research Part C 104，443-462.

[31] Xiao, F.*, Shen, M.Y., Xu, Z.T., Li, R.J., Yang, H. and Yin, Y.F., 2019. Day-to-day Flow Dynamics for Stochastic User Equilibrium and A General Lyapunov Function. Transportation Science 53(3), 683-694.

[32] Xiao, F., Zhang, D., Kou, G. and Li, L., 2019. Learning spatiotemporal features of ride-sourcing services with fusion convolutional network. arXiv preprint arXiv:1904.06823.

[33] Xiao, F., Long, J.C., Li, L.*, Kou, G. and Nie, Y., 2019. Promoting Social Equity with Cyclic Tradable Credits. Transportation Research Part B 121(2019), 56-73.

[34] Li, L., Lo, H.K.*, Xiao, F., Cen, X.K., 2018. Mixed Bus Fleet Management Strategy for Minimizing Overall and Emissions External Costs Transportation. Transportation Research Part D 60, 104-118.

[35] Ge, Y.E.*, Long, J.C., Xiao, F., Shi, Q., 2018. Traffic modeling for low-emission transport. Transportation Research Part D 60, 1-6.

[36] Li, L., Lo, H.K. and Xiao, F., 2018. Optimizing mixed-fleet bus scheduling under range constraint. In CASPT 2018 (Conference on Advanced Systems in Public Transport and Transit Data 2018) (pp. 1-16).

[37] Ye, H.B., Xiao, F.*, Yang, H., 2018. Exploration of day-to-day route choice models by a virtual experiment. Transportation Research Part C 94, 220-235.

[38] Xu, L., Zhang, C., Xiao, F.* and Wang, F., 2017. A Robust Approach to Airport Gate Assignment with a Solution-dependent Uncertainty Budget. Transportation Research Part B 105, 458-478.

[39] Bao, Y., Xiao, F., Gao, Z.H., Gao, Z.Y.*, 2017. Investigation of the traffic congestion during public holiday and the impact of the toll-exemption policy. Transportation Research Part B 104, 58-81.

[40] Ye, H.B., Xiao, F.*, Yang, H., 2017. Exploration of day-to-day route choice models by a virtual experiment. Transportation Research Procedia 23, 679-699.

[41] Xiao, F.*, Yang, H. and Ye, H.B., 2016. Physics of Day-To-Day Network Flow Dynamics. Transportation Research Part B 86, 86-103.

[42] Nie, Y.M. *, Ghamami, M., Zockaie, A. and Xiao, F., 2016. Optimization of Incentive Polices for Plug-in Electric Vehicles. Transportation Research Part B 84, 103-123.

[43] Zhu, J.C., Xiao, F.* and Liu, X.B., 2015. Taxis in road pricing zone: should they pay the congestion charge? Journal of Advanced Transportation 49(1), 96-113.

[44] Xiao, F. and Zhang, H.M.*, 2014. Pareto-Improving Toll and Subsidy Scheme on Transportation Networks. European Journal of Transport and Infrastructure Research 14(1), 46-65.

[45] Xiao, F.* and Zhang, H.M., 2014. Pareto-Improving and Self-Sustainable Pricing for the Morning Commute with Nonidentical Commuters. Transportation Science 48(2), 159-169.

[46] Xiao, F., Qian, Z. and Zhang, H.M.*, 2013. Managing Bottleneck Congestion with Tradable Credits. Transportation Research Part B 56(0), 1-14.

[47] Xiao, F., Shen, W. and Zhang, H.M.*, 2012. The Morning Commute under Flat Toll and Tactical Waiting. Transportation Research Part B 46(10), 1346-1359.

[48] Qian, Z., Xiao, F., Zhang, H.M.*, 2012. Managing morning commute with parking. Transportation Research Part B 46(7), 894–916.

[49] Qian, Z., Xiao, F. and Zhang, H.M.*, 2011. The Economics of Parking Provision for the Morning Commute. Transportation Research Part A, 45(9), 861-879.

[50] Xiao, F., Qian, Z. and Zhang, H.M.*, 2010. Morning commute problem with coarse toll and nonidentical commuters. Networks and Spatial Economics,11 August 2010, 1-27.

[51] Yang, H.* and Xiao, F., 2009. Private road competition and equilibrium with traffic equilibrium constraints. The Journal of Advanced Transportation 43(1), 21-45.

[52] Xiao, F.*, Yang, H., 2008. Efficiency loss of private road with continuously distributed value of time. Transportmetrica 4(1), 19-32.

[53] Xiao, F., Yang, H.* and Guo, X.L., 2007. Bounding the inefficiency of toll competition among congested roads. Transportation and Traffic Theory 2007(ISTTT17) (edited by Richard E. Allsop),Elsevier, 27-54. Imperial College London, UK.

[54] Xiao, F., Yang, H.* and Han, D.R., 2007. Competition and efficiency of private toll roads. Transportation Research Part B 41(3), 292-308.

[55] Xiao, F. and Yang, H.*, 2007. Three-player game-theoretic model over a freight transportation network. Transportation Research Part C 15(4), 209-217.

[56] 刘星委, 刘建玮, 肖峰. 基于深度学习的交通流预测方法可行性研究[J]. 河北交通教育. 2018,(02):45-47+56.

[57] 肖峰*，涂雯雯，陈冬. 基于手机运动传感器数据的交通流拥挤识别[J]. 西南交通大学学报，2016, 51(3):553-562.

[58] 邓雪，肖峰*，郑梦雷. 闯黄灯处罚对交叉口通行效率的影响[J]. 西华大学学报(自然科学版), 2016.7, (04): 108~112.

[59] 张大鹏, 肖峰*. 基于个人空间理论的人群疏散机理研究[J]. 交通运输工程与信息学报, 2016, 14(2):144-152.

[60] 祝进城, 肖峰*, 帅斌. 城市出租车拥挤收费[J]. 吉林大学学报:工学版, 2015, 45(1):89-96.

[61] 郑梦雷, 肖峰*, 朱文熙. 电动汽车充电站规模优化模型研究[J]. 西华大学学报(自然科学版), 2015, 34(5):103-107.

[62] Deng, X., Zhang, M. and Xiao, F., 2014. Design and Application of Intelligent Transportation System Based on The Internet of Things. In ICLEM 2014: System Planning, Supply Chain Management, and Safety (pp. 26-31).

[63] Zhang, M. and Xiao, F.*, 2013. Bus Arrival Time Prediction based on GPS Data. Proceedings of the Fourth International Conference on Transportation Engineering. ASCE Conf. Proc.，2013

[64] Xiao, F.*, 2011. Investment, Pricing, and Efficiency of Private Road with Heterogeneous Trip‐Makers. Proceedings of the Third International Conference on Transportation Engineering. ASCE Conf. Proc. doi:10.1061/41184(419)142.

[65] 肖峰, 缪立新*. 有效性原理在运输定价中的运用[J]. 中国物流与采购, 2003(10):18-19.

[66] 肖峰, 缪立新*. 面临环境挑战的中国物流业[J]. 中国物流与采购, 2003(8):26-27.