115 McLaughlin Hall
CEE, Systems and Transportation
UC Berkeley, CA 94720
Phone: +1 510 984 8696
Alexei holds a Ph.D. in computer science from EPFL, Switzerland, following his research in machine learning methods and computer vision that he carried out at IDIAP Research Institute in Martigny, Switzerland. He then worked on remote sensing and spatial data mining at the University of Lausanne (UNIL). Most recently, he held a position of a Science Foundation Ireland (SFI) Stokes Lecturer with the National Centre for Geocomputation (NCG).
Research areas:machine learning, spatial data mining, computational social science, urban mobility, smart cities
DOE SMART program, Urban Science Lead, LBNL, with PIs Prof Alexandre Bayen and Dr Anand Gopal
NSF CRISP: Multi-scale Infrastructure Interactions with Intermittent Disruptions: Coastal Flood Protection, Transportation and Governance Networks, with PI Prof Mark Stacey and Prof Samer Madanat
NASA SMARTNAS NRA. Big Data Analytics for Aeronautics. PI.
NASA NextGen CTD Research. Similar Historical Days and Air Traffic Flow Management Response Strategies, with PI Prof Mark Hansen.
Route inference, a.k.a. The MegaCell team of the Connected Corridors, with PI Prof Alexandre Bayen.
BayLearn'17 is forthcoming. Bay Area Machine Learning Symposium was held in October 2016, keep an eye on 2017 announcements.
Fall 2017 CE88: Data Science for Smart Cities. Enroll early! This is a 2 unit connector to the Foundations of Data Science, data8.org. There are no formal pre-requisites so you can also take it independently of Data8 (backgorund comparable to a junior standing in any engineering major is desirable in this case).
Fall 2017 CE263N: Scalable Spatial Analytics. Here is a sample course syllabus. Enroll early!
Recent Papers - recommended to my studentsYin M., Sheehan M., Feygin S., Paiement J.-F. and Pozdnoukhov A., A Generative Model of Urban Activities from Cellular Data. IEEE Transactions in ITS (to appear), 2017 [ - activity-based model]
Feygin S. and Pozdnoukhov A., Peer Pressure Enables Actuation of Mobility Lifestyles. (in review), 2017 [ - social influence]
Zhang D., Cao J., Tang D., Feygin S. and Pozdnoukhov A., Connected Population Synthesis for Urban Simulation. (in review), 2017
Mohanty S. and Pozdnoukhov A., Dynamic Departure Time Estimation. (in review), 2017
Lin Z., Yin M., Sheehan M., Feygin S. Paiement J.-F. and Pozdnoukhov A., Deep Generative Models of Urban Mobility. (in review), 2017
Hegde V., Krnjajic M., Pozdnoukhov A., Unsupervised Event Detection with an Infinite Poisson Mixture Model. IEEE BigData Congress, 2015
Pozdnoukhov, A., Campbell, A., Feygin, S., Yin, M., and Mohanty, S., The SmartBay Project: Connected Mobility in the San Francisco Bay Area. In The Multi-Agent Transport Simulation: MATSim, edited by Horni, A., Nagel, K., and Axhausen, K., 2015, in press.
Wu C., Yadlowsky S., Thai J., Pozdnoukhov A., Bayen A., Cellpath: fusion of cellular and traffic sensor data for route flow estimation via convex optimization. Int Symp on Transportation and Traffic Theory (ISTTT) and Transportation Research: Part C, Volume 59, October 2015, Pages 111–128. [ - route inference]
Yadlowsky S., Thai J., Wu C., Pozdnoukhov A., Bayen A., Link Density Inference from Cellular Infrastructure. Transportation Research Board (TRB) 94th Anuual Annual Meeting, Transportation Research Record (TRR), 2015 [ - traffic density]
Coffey C., Pozdnoukhov A., Temporal Decomposition and Semantic Enrichment of Mobility Flows, LBSN'13 at 21st ACM SIGSPATIAL GIS'2013, 2013 [ - mobility analytics, trip purpose]
Tarasov A., Kling F., Pozdnoukhov A., Prediction of User Location Using the Radiation Model and Social Check-ins, UrbComp'13 at ACM SIGKDD, 2013
McArdle G., Furey E., Lawlor A., Pozdnoukhov A., Using Digital Footprints for a City-scale Traffic Simulation, ACM TIST. 2013
Kaiser C., Pozdnoukhov A., Enabling Real-time City Sensing with Kernel Stream Oracles and MapReduce, Pervasive and Mobile Computing, Volume 7, Issue 5, pp 708-721. 2013 [ - ML for streaming spatial data, MapReduce]
M. Batty, K. W. Axhausen, F. Giannotti, A. Pozdnoukhov, A. Bazzani, M. Wachowicz, G. Ouzounis, Y. Portugali. Smart Cities of the Future. The European Physical Journal Special Topics, Volume 214, Issue 1, pp 481-518. 2012
Kling F., Pozdnoukhov A., When a City Tells a Story: Urban Topic Analysis, In proc of the 20th ACM SIGSPATIAL GIS, 2012 (Best Poster Award runner up). [ - urban dynamics, functional areas]
Tuia, D., Pozdnoukhov, A., Foresti, L. and Kanevski, M. Active Learning for Monitoring Network Optimization, In Spatio-Temporal Design: Advances in Efficient Data Acquisition (eds J. Mateu and W. G. Mueller), John Wiley & Sons. 2012
McArdle G., Furey E., Lawlor A., Pozdnoukhov A., City-scale Traffic Simulation From Digital Footprints, UrbComp'12 at ACM SIGKDD, 2012 [ - mobility, agent-based]
Coffey C., Nair R., Pinelli F., Pozdnoukhov A., Calabrese F. Missed Connections: Quantifying and Optimizing Multimodal Interconnectivity in Cities. IWCTS of the 20th ACM SIGSPATIAL GIS, 2012
McGrath R., Coffey C., Pozdnoukhov A., Habitualisation: localisation without location data, Nokia MDC challenge at PERVASIVE'2012, 2012
Lawlor A., Coffey C., McGrath R., Pozdnoukhov A., Stratification structure of urban habitats, Pervasive Urban Apps at PERVASIVE'2012, 2012
Foresti L., Kanevski M., Pozdnoukhov A. Kernel-based Mapping of Orographic Rainfall Enhancement in the Swiss Alps as Detected by Weather Radar. IEEE Transactions on Geoscience and Remote Sensing, Issue 99, pp 1-14 2012.
Farmer C., Pozdnoukhov A., Building streaming GIScience from context, theory, and intelligence. Position paper, Big Data Age workshop at GIScience'2012 (our manifesto to GIScience), 2012
Tuia D., Joost S., Pozdnoukhov A. Active multiple kernel learning of wind power resources, Machine Learning for Sustainability at NIPS'11, 2011
Pozdnoukhov A., Kaiser C. Scalable Local Regression for Spatial Analytics, Proc of the 19th ACM SIGSPATIAL GIS'2011, 2011 Long paper: [ - locally linear, streaming]
Pozdnoukhov A., Kaiser C. Space-Time Dynamics of Topics in Streaming Text, LBSN at 19th ACM SIGSPATIAL GIS'2011, 2011 (Best Paper Award). [ - LDA and MMPP]
Pozdnoukhov A., Kaiser C. Area-to-point Kernel Regression on Streaming Data, Geostreaming at 19th ACM SIGSPATIAL GIS'2011, 2011
Coffey C., Pozdnoukhov A., Calabrese F. Time of Arrival Predictability Horizons for Public Bus Routes, Computational Transportation Science workshop at 19th ACM SIGSPATIAL GIS'2011, 2011
Walsh F., Pozdnoukhov A., Spatial structure and dynamics of urban communities, Pervasive Urban Applications at PERVASIVE'2011, 2011
Pozdnoukhov, A., Matasci, G., Kanevski, M., and Purves, R.S. Spatio-temporal avalanche forecasting with Support Vector Machines. Nat. Hazards Earth Syst. Sci., 11, 367-382, 2011.
Foresti L., Pozdnoukhov A. Exploration of alpine orographic precipitation patterns with radar image processing and clustering techniques. Meteorological Applications, John Wiley & Sons, DOI 10.1002/met.272, 2011.
Foresti L., Tuia D., Kanevski M. and Pozdnoukhov A. Learning wind fields with multiple kernels. Stochastic Environmental Research and Risk Assessment, Volume 25, Number 1, pp. 51-66, 2011
Pozdnoukhov A., Spatial extensions to kernel methods, Proc. of the 18th ACM SIGSPATIAL GIS (short paper), 2010
Pozdnoukhov A., Walsh F., Exploratory Novelty Identification in Human Activity Data Streams, ACM SIGSPATIAL International Workshop on GeoStreaming at 18th ACM SIGSPATIAL GIS, 2010
Pozdnoukhov A., Walsh F., Kaiser F., Statistical Machine Learning from VGI, Position paper at Role of Volunteered Geographic Information in Advancing Science Workshop at GIScience'10, 2010.
Kaiser C., Walsh F., Farmer C. and Pozdnoukhov A., User-centric time-distance representation of road networks. In Springer LNCS proc. of the GIScience'10 (full paper). 2010
Tuia D., Ratle F., Pozdnoukhov A., Camps-Valls G. Multisource Composite Kernels for Urban-Image Classification. IEEE Geoscience and Remote Sensing Letters, Volume 7, Number 1, pp. 88-92, 2010.
Pozdnoukhov A., Dynamic network data exploration through semi-supervised functional embedding. In Proc of the 17th ACM SIGSPATIAL GIS, 2009 [ - Deep Learning]
Pozdnoukhov A., Bengio S. From Samples to Objects: Invariances in Kernel Methods. Pattern Recognition Letters Journal, Volume 27, Issue 10, pp. 1087-1097. 2006.
|SFI Research Frontiers Programme: Learning Human Spatial Dynamics. Principle Investigator, (2011-2015).|
|SFI StratAG: Strategic Research Cluster in Advanced Geotechnologies. Co-PI, Scalable Statistical Learning project lead, Coordinator of the City-Scale Demonstrator (2011-2013).|
|GMorphs: Contextual morphing of GMaps (Google Research Award 2010). Principle Investigator.|
Supervisor, an IBM PhD Fellowship Award to Cathal Coffey.
Data Analytics for Smarter Driving (Scalable Data Analytics Award 2010). Co-PI with PI Tim McCarthy.
|COSMIC: Complexity in Spatial Dynamics (ERA-NET on Complexity). Co-investigator with CASA-UCL (M. Batty), VU Amsterdam (P. Nijkamp), and University of St.Andrews (S. Fotheringham) (2010-2012).|
|Marie-Curie ITN Geocrowd: Creating Geospatial Knowledge World. Scientist in charge at NUIM (2011-2014).|
|Kanevski M., Pozdnoukhov A., Timonin V. Machine Learning Algorithms for Geospatial Data. Theory, Applications and Software. 377pp. EPFL press, 2009. Link|