In short

I am a Staff Autonomy Engineer and Technical Lead Manager at Aurora Innovation, Inc. in the Perception group. Prior to Aurora I worked in the same role at Uber ATG in the Perception/Prediction group, until the company was acquired by Aurora. Before ATG I worked as a Research Scientist at Yahoo Labs in the Targeting Science group. I received PhD in Computer Science from the Department of Computer & Information Sciences, Temple University, under mentorship of prof. Slobodan Vucetic. Previously, I received B.Sc. and M.Sc. in Electrical Engineering in 2007 and 2009, respectively, from University of Novi Sad, Serbia. For more info see my CV.

News

April 2021: I am co-organizing the workshop on Visual Detection, Recognition and Prediction at Altitude and Range, held in conjuction with ICCV 2021.
Other workshops I am currently co-organizing:
Past workshops I co-organized:

March 2021: I am co-organizing AVVision, an Organized Session held as a part of IROS 2021.

January 2021: I am co-organizing AVVision, a Special Session held as a part of ICIP 2021.

October 2020: I gave a keynote talk on Uber ATG research at UberML'20, Uber's annual internal Machine Learning conference.

September 2020: I will give a keynote talk on Uber ATG research at Workshop on Autonomous Vehicle Vision, organized as a part of WACV 2021. (update: see the video recording here)

September 2020: I gave a keynote talk on Uber ATG research at Ai Day 2020, organized by VinAi research in September 2020.

July 2020: I will give an invited talk on Uber ATG research at Auto.AI USA conference in March 2021. (update: conference postponed to July 2021 due to the pandemic)

July 2020: I will give an invited talk on Uber ATG research at Workshop on Benchmarking Trajectory Forecasting Models, organized as a part of ECCV 2020.

June 2020: Our MultiXNet model performing joint end-to-end object perception and motion prediction was featured on VentureBeat, as well as l'Automobile (Italy), Motorpasion (Spain), SiecleDigital (France), and other websites throughout the world.

May 2020: I will give an invited talk on Uber ATG research at Workshop on AI for Autonomous Driving, organized as a part of ICML 2020.

April 2020: Our SC-GAN trajectory predictor that uses Generative Adversarial Networks (GANs) to improve movement prediction of traffic actors was featured on VentureBeat, as well as IEEE Innovation at Work, 4ever Science (Russia), ETAuto.com (India), Analytics India Magazine, ZME Science, and other websites throughout the world.

September 2019: I gave an invited talk at PyData Córdoba on Perception and Prediction at Uber ATG.

September 2018: I gave a keynote talk at PyData Córdoba on Self-Driving Cars & AI: Transforming our Cities and our Lives.

June 2014: Our World Cup predictor based on the analysis of millions of Tumblr posts was featured on Yahoo! Labs, Yahoo! Sports, MarketWatch, and other websites throughout the world.

August 2013: Our work "Semi-Supervised Learning for Integration of Aerosol Predictions from Multiple Satellite Instruments" received an Outstanding Paper Award at IJCAI 2013, AI and Computational Sustainability Track.

May 2013: BudgetedSVM, a C++ toolbox for large-scale non-linear classification, is available for download.


Research

I am interested in several areas of Machine Learning and Data Mining. I have worked on problems related to object perception and motion prediction in self-driving vehicles, computational advertising, bioinformatics, learning on low resources, spatio-temporal problems in remote sensing, data visualization, object matching. The complete list of my publications is given below, along with a source code and a PDF-version of a paper where available.
NOTE: To peruse papers published by the IEEE, one must adhere to the terms of the following IEEE copyright notice.

Journal papers

  1. Large-Scale Discovery of Disease-Disease and Disease-Gene Associations
    Gligorijevic, Dj., Stojanovic, J., Djuric, N., Radosavljevic, V., Grbovic, M., Kulathinal, R. J., Obradovic, Z.
    Nature Scientific Reports, vol. 6, article no. 32404, 2016.
    [pdf] [nature.com] [bibtex]
  2. Modeling Healthcare Quality via Compact Representations of Electronic Health Records
    Stojanovic, J., Gligorijevic, Dj., Radosavljevic, V., Djuric, N., Grbovic, M., Obradovic, Z.
    IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), vol. 14, no. 3, pp. 545-554, 2016.
    [pdf] [IEEE Xplore] [bibtex]
  3. Semi-Supervised Combination of Experts for Aerosol Optical Depth Estimation
    Djuric, N., Kansakar, L., Vucetic, S.
    Artificial Intelligence, vol. 230, pp. 1-13, 2016.
    [pdf] [ScienceDirect] [bibtex]
  4. Gaussian Conditional Random Fields for Aggregation of Operational Aerosol Retrievals
    Djuric, N., Radosavljevic, V., Obradovic, Z., Vucetic, S.
    IEEE Geoscience and Remote Sensing Letters, vol. 12, no. 4, pp. 761-765, 2014.
    [pdf] [appendix] [IEEE Xplore] [bibtex]
  5. BudgetedSVM: A Toolbox for Scalable SVM Approximations
    Djuric, N., Lan, L., Vucetic, S., Wang, Z.
    Journal of Machine Learning Research (JMLR), 14(Dec):3813-3817, 2013.
    [pdf] [code] [webpage] [JMLR] [bibtex]
  6. Supervised Clustering of Label Ranking Data using Label Preference Information
    Grbovic, M., Djuric, N., Guo, S., Vucetic, S.
    Machine Learning Journal (MLJ), pp. 1-35, 2013.
    [pdf] [Springer] [bibtex]
  7. A Large-scale Evaluation of Computational Protein Function Prediction
    Radivojac, P., Clark, W. T., ..., Toppo, S., Lan, L., Djuric, N., Guo, Y., Vucetic, S., Bairoch, A., Linial, M., Babbitt, P. C., et al.
    Nature Methods, vol. 10, no. 3, pp. 221-229, 2013.
    [pdf] [nature.com] [bibtex]
  8. MS-kNN: Protein Function Prediction by Integrating Multiple Data Sources
    Lan, L., Djuric, N., Guo, Y., Vucetic, S.
    BMC Bioinformatics, vol. 14 (suppl. 3):S8, 2013.
    [pdf] [BMC] [bibtex]
  9. Traffic State Estimation from Aggregated Measurements using Signal Reconstruction Techniques
    Coric, V., Djuric, N., Vucetic, S.
    Transportation Research Record: Journal of the Transportation Research Board, Traffic Flow Theory and Characteristics, no. 2315, pp. 121-130, 2012.
    [pdf] [TRB] [bibtex]
  10. Travel Speed Forecasting by Means of Continuous Conditional Random Fields
    Djuric, N., Radosavljevic, V., Coric, V., Vucetic, S.
    Transportation Research Record: Journal of the Transportation Research Board, Network Modeling, no. 2263, pp. 131-139, 2011.
    [pdf] [slides] [poster] [TRB] [bibtex]

Conference papers and preprints

  1. MultiXNet: Multiclass Multistage Multimodal Motion Prediction
    Djuric, N., Cui, H., Su, Z., Wu, S., Wang, H., Chou, F.-C., San Martin, L., Feng, S., Hu, R., Xu, Y., Dayan, A., Zhang, S., Becker, B. C., Meyer, G. P., Vallespi-Gonzalez, C., Wellington, C. K.
    IEEE Intelligent Vehicles Symposium (IV), Nagoya, Japan, 2021.
    arXiv preprint:2006.02000, 2020.
    [arXiv] [bibtex]
  2. Convolutions for Spatial Interaction Modeling
    Su, Z., Wang, C., Bradley, D., Vallespi-Gonzalez, C., Wellington, C. K., Djuric, N.
    arXiv preprint:2104.07182, 2021.
    [arXiv] [bibtex]
  3. Ellipse Loss for Scene-Compliant Motion Prediction
    Cui, H.*, Shajari, H.*, Yalamanchi, S., Djuric, N.  *authors contributed equally
    IEEE International Conference on Robotics and Automation (ICRA), Xi'an, China, 2021.
    arXiv preprint:2011.03139, 2020.
    [pdf] [bibtex]
  4. Multi-Modal Trajectory Prediction of NBA Players
    Hauri, S., Djuric, N., Radosavljevic, V., Vucetic, S.
    IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa, USA, 2021.
    [pdf] [supplementary] [bibtex]
  5. Improving Word Embeddings through Iterative Refinement of Word- and Character-level Models
    Ha, P., Zhang, S., Djuric, N., Vucetic, S.
    International Conference on Computational Linguistics (COLING), Barcelona, Spain, 2020.
    [pdf] [bibtex]
  6. Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving
    Fadadu, S.*, Pandey, S.*, Hegde, D., Shi, Y., Chou, F.-C., Djuric, N., Vallespi-Gonzalez, C.  *authors contributed equally
    arXiv preprint:2008.11901, 2020.
    [arXiv] [bibtex]
  7. Growing Adaptive Multi-hyperplane Machines
    Djuric, N., Zhuang, W., Vucetic, S.
    International Conference on Machine Learning (ICML), Vienna, Austria, 2020.
    [pdf] [appendix] [code] [bibtex]
  8. Improving Movement Predictions of Traffic Actors in Bird's-Eye View Models using GANs and Differentiable Trajectory Rasterization
    Wang, E.*, Cui, H.*, Yalamanchi, S., Moorthy, M., Chou, F.-C., Djuric, N.  *authors contributed equally
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), San Diego, USA, 2020.
    [pdf] [bibtex]
  9. Long-term Prediction of Vehicle Behavior using Short-term Uncertainty-aware Trajectories and High-definition Maps
    Yalamanchi, S., Huang, T.-K., Haynes, G. C., Djuric, N.
    IEEE International Conference on Intelligent Transportation Systems (ITSC), Rhodes, Greece, 2020.
    [pdf] [bibtex]
  10. Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
    Chou, F.-C., Lin, T.-H., Cui, H., Radosavljevic, V., Nguyen, T., Huang, T.-K., Niedoba, M., Schneider, J., Djuric, N.
    IEEE Intelligent Vehicles Symposium (IV), Las Vegas, USA, 2020.
    [pdf] [bibtex]
  11. Deep Kinematic Models for Kinematically Feasible Vehicle Trajectory Predictions
    Cui, H., Nguyen, T., Chou, F.-C., Lin, T.-H., Schneider, J., Bradley, D., Djuric, N.
    IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020.
    arXiv preprint:1908.00219, 2019.
    [pdf] [bibtex] [arXiv]
  12. Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving
    Djuric, N., Radosavljevic, V., Cui, H., Nguyen, T., Chou, F.-C., Lin, T.-H., Singh, N., Schneider, J.
    IEEE Winter Conference on Applications of Computer Vision (WACV), Snowmass Village, USA, 2020.
    arXiv preprint:1808.05819, 2018.
    [pdf] [poster] [bibtex] [arXiv]
  13. Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks
    Cui, H., Radosavljevic, V., Chou, F.-C., Lin, T.-H., Nguyen, T., Huang, T.-K., Schneider, J., Djuric, N.
    IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, 2019.
    [pdf] [poster] [bibtex]
  14. Analyzing Uber's Ride-Sharing Economy
    Kooti, F., Grbovic, M., Aiello, L. M., Djuric, N., Radosavljevic, V., Lerman, K.
    International World Wide Web Conference (WWW), Perth, Australia, 2017.
    [pdf] [slides] [bibtex]
  15. Network–Efficient Distributed Word2vec Training System for Large Vocabularies
    Ordentlich, E., Feng, A., Grbovic, M., Yang, L., Cnudde, P., Djuric, N., Radosavljevic, V., Owens, G.
    International ACM Conference on Information and Knowledge Management (CIKM), Indianapolis, USA, 2016.
    [pdf] [bibtex]
  16. Travel the World: Analyzing and Predicting Booking Behavior using E-mail Travel Receipts
    Djuric, N., Grbovic, M., Radosavljevic, V., Savla, J., Bhagwan, V., Sharp, D.
    International World Wide Web Conference (WWW), Montreal, Canada, 2016.
    [pdf] [bibtex]
  17. Smartphone App Categorization for Interest Targeting in Advertising Marketplace
    Radosavljevic, V., Grbovic, M., Djuric, N., Bhamidipati, N., Zhang, D., Wang, J., Dang, J., Huang, H., Nagarajan, A., Chen, P.
    International World Wide Web Conference (WWW), Montreal, Canada, 2016.
    [pdf] [bibtex]
  18. Scalable Semantic Matching of Search Queries to Ads in Sponsored Search Advertising
    Grbovic, M., Djuric, N., Radosavljevic, V., Silvestri, F., Baeza-Yates, R., Feng, A., Ordentlich, E., Yang, L., Owens, L.
    International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Pisa, Italy, 2016.
    [pdf] [slides] [bibtex] [blog]
  19. ParkAssistant: An Algorithm for Guiding a Car to a Parking Spot
    Djuric, N., Grbovic, M., Vucetic, S.
    Transportation Research Board 95th Annual Meeting (TRB), Washington, D.C., USA, 2016.
    [pdf] [poster] [bibtex]
  20. Portrait of an Online Shopper: Understanding and Predicting Consumer Behavior
    Kooti, F., Lerman, K., Aiello, L. M., Grbovic, M., Djuric, N., Radosavljevic, V.
    ACM International Conference on Web Search and Data Mining (WSDM), San Francisco, USA, 2016.
    [pdf] [slides] [bibtex] [blog]
  21. E-commerce in Your Inbox: Product Recommendations at Scale
    Grbovic, M., Radosavljevic, V., Djuric, N., Bhamidipati, N., Savla, J., Bhagwan, V., Sharp, D.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Sydney, Australia, 2015.
    [pdf] [slides] [bibtex]
  22. Gender and Interest Targeting for Sponsored Post Advertising at Tumblr
    Grbovic, M., Radosavljevic, V., Djuric, N., Bhamidipati, N., Nagarajan, A.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Sydney, Australia, 2015.
    [pdf] [slides] [bibtex]
  23. Context- and Content-aware Embeddings for Query Rewriting in Sponsored Search
    Grbovic, M., Djuric, N., Radosavljevic, V., Silvestri, F., Bhamidipati, N.
    International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Santiago, Chile, 2015.
    [pdf] [bibtex]
  24. Hierarchical Neural Language Models for Joint Representation of Streaming Documents and their Content
    Djuric, N.*, Wu, H.*, Radosavljevic, V., Grbovic, M., Bhamidipati, N.  *authors contributed equally
    International World Wide Web Conference (WWW), Florence, Italy, 2015.
    [pdf] [slides] [bibtex]
  25. Search Retargeting using Directed Query Embeddings
    Grbovic, M., Djuric, N., Radosavljevic, V., Bhamidipati, N.
    International World Wide Web Conference (WWW), Florence, Italy, 2015.
    [pdf] [bibtex]
  26. Hate Speech Detection with Comment Embeddings
    Djuric, N., Zhou, J., Morris, R., Grbovic, M., Radosavljevic, V., Bhamidipati, N.
    International World Wide Web Conference (WWW), Florence, Italy, 2015.
    [pdf] [bibtex]
  27. queryCategorizr: A Large-Scale Semi-Supervised System for Categorization of Web Search Queries
    Grbovic, M., Djuric, N., Radosavljevic, V., Bhamidipati, N., Hawker, J., Johnson, C.
    International World Wide Web Conference (WWW), Florence, Italy, 2015.
    [pdf] [bibtex]
  28. Hidden Conditional Random Fields with Distributed User Embeddings for Ad Targeting
    Djuric, N., Radosavljevic, V., Grbovic, M., Bhamidipati, N.
    IEEE International Conference on Data Mining (ICDM), Shenzhen, China, 2014.
    [pdf] [slides] [IEEE Xplore] [bibtex]
  29. Non-linear Label Ranking for Large-scale Prediction of Long-Term User Interests
    Djuric, N., Grbovic, M., Radosavljevic, V., Bhamidipati, N., Vucetic, S.
    AAAI Conference on Artificial Intelligence (AAAI), Quebec City, Canada, 2014.
    [pdf] [slides] [poster] [bibtex]
  30. Frugal Traffic Monitoring with Autonomous Participatory Sensing
    Coric, V., Djuric, N., Vucetic, S.
    SIAM Conference on Data Mining (SDM), Philadelphia, PA, 2014.
    [pdf] [bibtex]
  31. Efficient Visualization of Large-scale Data Tables through Reordering and Entropy Minimization
    Djuric, N., Vucetic, S.
    IEEE International Conference on Data Mining (ICDM), Dallas, TX, 2013.
    [pdf] [slides] [poster] [IEEE Xplore] [bibtex]
  32. Distributed Confidence-Weighted Classification on MapReduce
    Djuric, N., Grbovic, M., Vucetic, S.
    IEEE International Conference on Big Data (IEEE BigData), Santa Clara, CA, USA, 2013.
    [pdf] [slides] [code] [IEEE Xplore] [bibtex]
  33. Semi-Supervised Learning for Integration of Aerosol Predictions from Multiple Satellite Instruments
    Djuric, N., Kansakar, L., Vucetic, S.
    International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, 2013.
    Outstanding paper award from AI and Computational Sustainability Track
    [pdf] [slides] [poster] [code] [bibtex]
  34. Multi-prototype Label Ranking with Novel Pairwise-to-Total-Rank Aggregation
    Grbovic, M.*, Djuric, N.*, Vucetic, S.  *authors contributed equally
    International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, 2013.
    [pdf] [bibtex]
  35. Convex Kernelized Sorting
    Djuric, N., Grbovic, M., Vucetic, S.
    AAAI Conference on Artificial Intelligence (AAAI), Toronto, Canada, 2012.
    [pdf] [slides] [code] [bibtex]
  36. Supervised Clustering of Label Ranking Data
    Grbovic, M., Djuric, N., Vucetic, S.
    SIAM Conference on Data Mining (SDM), Anaheim, CA, USA, 2012.
    Best of SDM (selected in the top 10 best papers)
    [pdf] [slides] [bibtex]
  37. Trading Representability for Scalability: Adaptive Multi-Hyperplane Machine for Nonlinear Classification
    Wang, Z., Djuric, N., Crammer, K., Vucetic, S.
    ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), San Diego, CA, USA, 2011.
    [pdf] [code] [bibtex]

Workshop papers

  1. Uncertainty-aware Vehicle Orientation Estimation for Joint Detection-Prediction Models
    Cui, H., Chou, F.-C., Charland, J., Vallespi-Gonzalez, C., Djuric, N.
    Workshop on 'Machine Learning for Autonomous Driving' at Conference on Neural Information Processing Systems (ML4AD), virtual, 2020.
    [pdf] [bibtex]
  2. Investigating the Effect of Sensor Modalities in Multi-Sensor Detection-Prediction Models
    Mohta, A., Chou, F.-C., Becker, B. C., Vallespi-Gonzalez, C., Djuric, N.
    Workshop on 'Machine Learning for Autonomous Driving' at Conference on Neural Information Processing Systems (ML4AD), virtual, 2020.
    [pdf] [bibtex]
  3. Temporally-Continuous Probabilistic Prediction using Polynomial Trajectory Parameterization
    Su, Z., Wang, C., Cui, H., Djuric, N., Vallespi-Gonzalez, C., Bradley, D.
    Workshop on 'Machine Learning for Autonomous Driving' at Conference on Neural Information Processing Systems (ML4AD), virtual, 2020.
    [pdf] [bibtex]
  4. Improving Movement Prediction of Traffic Actors using Off-road Loss and Bias Mitigation
    Niedoba, M., Cui, H., Luo, K., Hegde, D., Chou, F.-C., Djuric, N.
    Workshop on 'Machine Learning for Autonomous Driving' at Conference on Neural Information Processing Systems (ML4AD), Vancouver, Canada, 2019.
    [pdf] [poster] [bibtex]
  5. Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
    Chou, F.-C., Lin, T.-H., Cui, H., Radosavljevic, V., Nguyen, T., Huang, T.-K., Niedoba, M., Schneider, J., Djuric, N.
    Workshop on 'Machine Learning for Intelligent Transportation Systems' at Conference on Neural Information Processing Systems (MLITS), Montreal, Canada, 2018. extended version published at IV2020
    [pdf] [poster] [bibtex]
  6. Leveraging Blogging Activity on Tumblr to Infer Demographics and Interests of Users for Advertising Purposes
    Grbovic, M., Radosavljevic, V., Djuric, N., Bhamidipati, N., Nagarajan, A.
    Workshop on 'Making Sense of Microposts' at International World Wide Web Conference (#Microposts), Montreal, Canada, 2016.
    [pdf] [bibtex]
  7. Large-scale World Cup 2014 outcome prediction based on Tumblr posts
    Radosavljevic, V., Grbovic, M., Djuric, N., Bhamidipati, N.
    Workshop on Large-Scale Sports Analytics at ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SportsKDD), New York City, USA, 2014.
    [pdf] [bibtex] [blog1 blog2]
  8. How much do age and gender affect news topic preferences?
    Djuric, N., Grbovic, M., Görür, D., Radosavljevic, V.
    Data Science for News Publishing Workshop at ACM SIGKDD Conference on Knowledge Discovery and Data Mining (NewsKDD), New York City, USA, 2014.
    [pdf] [bibtex]
  9. Learning from Pairwise Preference Data using Gaussian Mixture Model
    Grbovic, M., Djuric, N., Vucetic, S.
    Preference Learning Workshop, European Conference on Artificial Intelligence (PL-ECAI), Montpellier, France, 2012.
    [pdf] [bibtex]
  10. Protein Function Prediction by Integrating Different Data Sources
    Lan, L., Djuric, N., Guo, Y., Vucetic, S.
    Automated Function Prediction SIG 2011 featuring the CAFA Challenge: Critical Assessment of Function Annotations (AFP/CAFA), Vienna, Austria, 2011.
    Top performing team at AFP/CAFA 2011 Protein Function Prediction Assessment
    [pdf] [bibtex]
  11. Random Kernel Perceptron on ATTiny2313 Microcontroller
    Djuric, N., Vucetic, S.
    International Workshop on Knowledge Discovery from Sensor Data at ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SensorKDD), Washington DC, USA, 2010.
    [pdf] [slides] [bibtex]

Granted patents

  1. Object Motion Prediction and Autonomous Vehicle Control
    Djuric, N., Radosavljevic, V., Nguyen, T., Lin, T.-H., Schneider, J.
    US patent no. 10,656,657, 2020.
    [USPTO]
  2. Machine Learning for Predicting Locations of Objects Perceived by Autonomous Vehicles
    Haynes, G. C., Dewancker, I., Djuric, N., Huang, T.-K., Lan, T., Lin, T.-H., Marchetti-Bowick, M., Radosavljevic, V., Schneider, J., Styler, A. D., Traft, N., Wang, H., Stentz, A. J.
    US patent no. 10,579,063, 2020.
    [USPTO]
  3. Personalizing Ride Experience based on Contextual Ride Usage Data
    Djuric, N., Radosavljevic, V.
    US patent no. 10,482,559, 2019.
    [USPTO]
  4. Neural Network System for Autonomous Vehicle Control
    Djuric, N., Houston, J.
    US patent no. 10,452,068, 2019.
    [USPTO]

Book chapters

  1. Distributed Confidence-Weighted Classification on Big Data Platforms
    Djuric, N., Grbovic, M., Vucetic, S.
    In V. Govindaraju, V. Raghavan, C. R. Rao (Editors), "Handbook of Statistics: Big Data Analytics", vol. 33, Elsevier, 2015.
    [ScienceDirect] [bibtex]

Graduate theses


Teaching

I was a Teaching Assistant at Temple University in the following courses:
Spring 2012
Fall 2011