Nemanja Djuric / Немања Ђурић

In short

I am a Principal Software Engineer and Technical Lead Manager at Aurora Innovation, Inc. in the Perception group. Prior to Aurora I worked as a Staff Autonomy Engineer and Technical Lead Manager 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

August 2024:
I regularly co-organize workshops and events on interesting topics at various conferences. Past events I co-organized:

• AdKDD 2024 (summary), a workshop held in conjuction with KDD 2024.
• The sixth workshop on Precognition: Seeing through the Future, held in conjuction with CVPR 2024.
• AdKDD 2023 (summary, proceedings), a workshop held in conjuction with KDD 2023.
• The fifth workshop on Precognition: Seeing through the Future, held in conjuction with CVPR 2023.
• The panel on "Artificial Intelligence for Autonomous Driving", organized as a part of IEEE CAI 2023.
• The third AVVision workshop, held in conjuction with ECCV 2022.
• AdKDD 2022 (summary), a workshop held in conjuction with KDD 2022.
• The fourth workshop on Precognition: Seeing through the Future, held in conjuction with CVPR 2022.
• The second AVVision workshop (summary), held in conjuction with ICCV 2021.
• AVVision, an Organized Session held as a part of IROS 2021.
• AdKDD 2021 (summary), a workshop held in conjuction with KDD 2021.
• The third workshop on Precognition: Seeing through the Future, held in conjuction with CVPR 2021.
• AVVision, a Special Session held as a part of ICIP 2021.
• AdKDD 2020, a workshop held in conjuction with KDD 2020.
• The second workshop on Precognition: Seeing through the Future, held in conjuction with CVPR 2020.
• AdKDD 2019, a workshop held in conjuction with KDD 2019.
• Precognition: Seeing through the Future, held in conjuction with CVPR 2019.
• 2018 Edition of AdKDD and TargetAd, a workshop held in conjuction with KDD 2018.
• 2017 Edition of AdKDD and TargetAd, a workshop held in conjuction with KDD 2017.
• TargetAd 2016: Ad Targeting at Scale (summary), a workshop held in conjuction with WSDM 2016.
• TargetAd 2015: Ad Targeting at Scale (summary), a workshop held in conjuction with WWW 2015.

November 2022: Check out the blog I co-authored that is describing an approach to detection of emergency vehicles taken at Aurora.

June 2022: I gave an invited talk on end-to-end perception and prediction at Auto.AI USA conference in June 2022. See here the interview I gave for the conference before my talk.

March 2022: I received an Honorable Mention in the AI 2000 Most Influential Scholar Annual List (list of world’s top 100 researchers) for the area of Information Retrieval and Recommendation, in a list compiled by ArnetMiner.

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)

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] [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

1. Improved Tracking of Articulated Vehicles in Self-Driving Applications Using Phantom Observations
   Xu, C., Kingston, P., Djuric, N.
   IEEE International Conference on Intelligent Transportation Systems (ITSC), Bilbao, Spain, 2023.
   [pdf] [slides] [bibtex]
2. Convolutions for Spatial Interaction Modeling
   Su, Z., Wang, C., Bradley, D., Vallespi-Gonzalez, C., Wellington, C. K., Djuric, N.
   IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), New Orleans, USA, 2022.
   [pdf] [appendix] [slides] [poster] [bibtex]
3. 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
   IEEE Winter Conference on Applications of Computer Vision (WACV), Waikoloa, USA, 2022.
   arXiv preprint:2008.11901, 2020.
   [pdf] [poster] [bibtex]
4. Temporally-Continuous Probabilistic Prediction using Polynomial Trajectory Parameterization
   Su, Z., Wang, C., Cui, H., Djuric, N., Vallespi-Gonzalez, C., Bradley, D.
   IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic, 2021.
   [pdf] [slides] [bibtex]
5. Uncertainty-Aware Estimation of Vehicle Orientation for Self-Driving Applications
   Cui, H., Chou, F.-C., Charland, J., Vallespi-Gonzalez, C., Djuric, N.
   IEEE International Conference on Intelligent Transportation Systems (ITSC), Indianapolis, USA, 2021.
   [pdf] [slides] [bibtex]
6. 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.
   [pdf] [slides] [bibtex]
7. 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.
   [pdf] [slides] [bibtex]
8. 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] [slides] [bibtex] [video]
9. 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] [poster] [bibtex]
10. Growing Adaptive Multi-hyperplane Machines
    Djuric, N., Wang, Z., Vucetic, S.
    International Conference on Machine Learning (ICML), Vienna, Austria, 2020.
    [pdf] [appendix] [slides] [code] [bibtex]
11. 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] [slides] [code] [bibtex]
12. 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] [slides] [bibtex]
13. 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] [slides] [bibtex]
14. 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.
    [pdf] [slides] [bibtex]
15. 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] [slides] [poster] [bibtex] [video]
16. 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] [code] [bibtex]
17. 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]
18. 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]
19. 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]
20. 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]
21. 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]
22. 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]
23. 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]
24. 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]
25. 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]
26. 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] [slides] [bibtex]
27. 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]
28. 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]
29. 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]
30. 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]
31. 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] [bibtex]
32. 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]
33. Frugal Traffic Monitoring with Autonomous Participatory Sensing
    Coric, V., Djuric, N., Vucetic, S.
    SIAM Conference on Data Mining (SDM), Philadelphia, PA, 2014.
    [pdf] [bibtex]
34. 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] [bibtex]
35. 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] [bibtex]
36. 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]
37. 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] [poster] [bibtex]
38. Convex Kernelized Sorting
    Djuric, N., Grbovic, M., Vucetic, S.
    AAAI Conference on Artificial Intelligence (AAAI), Toronto, Canada, 2012.
    [pdf] [slides] [code] [bibtex]
39. 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]
40. 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] [slides] [code] [bibtex]

Granted patents

1. Systems and Methods for Sensor Data Processing and Object Detection and Motion Prediction for Robotic Platforms
   Mohta, A., Chou, F.-C., Vallespi-Gonzalez, C., Becker, B. C., Djuric, N.
   US Patent no. 12,007,728, 2024.
   [pdf]
2. Trajectory Prediction for Autonomous Devices
   Djuric, N., Yalamanchi, S., Haynes, G. C., Huang, T.-K.
   US Patent no. 11,851,087, 2023. (continuation of the earlier patent)
   [pdf]
3. Object Motion Prediction and Autonomous Vehicle Control
   Djuric, N., Radosavljevic, V., Nguyen, T., Lin, T.-H., Schneider, J., Cui, H., Chou, F.-C., Huang, T.-K.
   US Patent no. 11,835,951, 2023. (continuation of the earlier patent)
   [pdf]
4. Systems and Methods for Training Predictive Models for Autonomous Devices
   Cui, H., Wang, J., Yalamanchi, S., Moorthy, M., Chou, F.-C., Djuric, N.
   US Patent no. 11,762,391, 2023. (continuation of the earlier patent)
   [pdf]
5. Motion Prediction for Autonomous Devices
   Djuric, N., Cui, H., Nguyen, T., Chou, F.-C., Lin, T.-H., Schneider, J., Bradley, D. M.
   US Patent no. 11,635,764, 2023.
   [pdf]
6. Personalizing Ride Experience based on Contextual Ride Usage Data
   Djuric, N., Radosavljevic, V.
   US Patent no. 11,488,277, 2022. (continuation of the earlier patent)
   [pdf]
7. Systems and Methods for Training Predictive Models for Autonomous Devices
   Cui, H., Wang, J., Yalamanchi, S., Moorthy, M., Chou, F.-C., Djuric, N.
   US Patent no. 11,442,459, 2022.
   [pdf]
8. Trajectory Prediction for Autonomous Devices
   Djuric, N., Yalamanchi, S., Haynes, G. C., Huang, T.-K.
   US Patent no. 11,420,648, 2022.
   [pdf]
9. Computerized System and Method for Augmenting Search Terms for Increased Efficiency and Effectiveness in Identifying Content
   Bhagwan, V., Carpenter, B., Grbovic, M., Sharp, D., Radosavljevic, V., Djuric, N.
   US Patent no. 11,263,664, 2022.
   [pdf]
10. Object Motion Prediction and Autonomous Vehicle Control
    Djuric, N., Radosavljevic, V., Nguyen, T., Lin, T.-H., Schneider, J., Cui, H., Chou, F.-C., Huang, T.-K.
    US Patent no. 11,112,796, 2021. (continuation-in-part of the earlier patent)
    [pdf]
11. 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.
    [pdf]
12. 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.
    [pdf]
13. Personalizing Ride Experience based on Contextual Ride Usage Data
    Djuric, N., Radosavljevic, V.
    US Patent no. 10,482,559, 2019.
    [pdf]
14. Neural Network System for Autonomous Vehicle Control
    Djuric, N., Houston, J.
    US Patent no. 10,452,068, 2019.
    [pdf]

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]

Workshop papers

1. End-to-End Deep Learning Models for Gap Identification in Maize Fields
   Waqar, R., Grbovic, Z., Khan, M., Pajevic, N., Stefanovic, D., Filipovic, V., Panic, M., Djuric, N.
   Workshop on 'Agriculture-Vision: Challenges & Opportunities for Computer Vision in Agriculture' at IEEE/CVF Conf. on Computer Vision and Pattern Recognition (V4A), Seattle, USA, 2024.
   [pdf] [bibtex]
2. Exploration of Data Augmentation Techniques for Bush Detection in Blueberry Orchards
   Culjak, B., Pajevic, N., Filipovic, V., Stefanovic, D., Grbovic, Z., Djuric, N., Panic, M.
   Workshop on 'Precognition: Seeing through the Future' at IEEE/CVF Conf. on Computer Vision and Pattern Recognition (Precognition), Seattle, USA, 2024.
   [pdf] [bibtex]
3. Detection of Active Emergency Vehicles using Per-Frame CNNs and Output Smoothing
   Fan, M., Bidstrup, C., Su, Z., Owens, J., Yang, G., Djuric, N.
   Workshop on 'Vision-Centric Autonomous Driving' at IEEE/CVF Conf. on Computer Vision and Pattern Recognition (VCAD), Vancouver, Canada, 2023.
   [pdf] [poster] [bibtex]
4. Bush Detection for Vision-based UGV Guidance in Blueberry Orchards: Data Set and Methods
   Filipovic, V., Stefanovic, D., Pajevic, N., Grbovic, Z., Djuric, N., Panic, M.
   Workshop on 'Precognition: Seeing through the Future' at IEEE/CVF Conf. on Computer Vision and Pattern Recognition (Precognition), Vancouver, Canada, 2023.
   [pdf] [poster] [slides] [bibtex]
5. 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. (extended version published at ITSC 2021)
   [pdf] [slides] [bibtex]
6. 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] [slides] [bibtex]
7. 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. (extended version published at IROS 2021)
   [pdf] [slides] [bibtex]
8. 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]
9. 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 IV 2020)
   [pdf] [poster] [bibtex]
10. 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]
11. 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]
12. How much do age and gender affect news topic preferences?
    Djuric, N., Grbovic, M., Görür, D., Radosavljevic, V.
    Workshop on 'Data Science for News Publishing' at ACM SIGKDD Conference on Knowledge Discovery and Data Mining (NewsKDD), New York City, USA, 2014.
    [pdf] [bibtex]
13. Learning from Pairwise Preference Data using Gaussian Mixture Model
    Grbovic, M., Djuric, N., Vucetic, S.
    Workshop on 'Preference Learning' at European Conference on Artificial Intelligence (PL-ECAI), Montpellier, France, 2012.
    [pdf] [bibtex]
14. 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] [slides] [bibtex]
15. Random Kernel Perceptron on ATTiny2313 Microcontroller
    Djuric, N., Vucetic, S.
    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]

Graduate theses

• Doctoral dissertation: Big Data Algorithms for Visualization and Supervised Learning
  Temple University, Philadelphia, USA, 2013.
  [pdf] [slides] [bibtex]
• Master thesis: Short-range Packet-oriented Radio Link
  University of Novi Sad, Novi Sad, Serbia, 2009.
  [pdf (in Serbian)] [pdf (summary, in Serbian)] [slides (in Serbian)]

Teaching

I was a Teaching Assistant at Temple University in the following courses:

Spring 2012

• CIS 0835 - Cyberspace and Society (with prof. Abbe Forman; Dreamweaver)

Fall 2011

• CIS 3203/9603 - Artificial Intelligence (with prof. Longin Jan Latecki; joint undergraduate and graduate course)
• CIS 2107 - Computer Systems and Low-Level Programming (with prof. John Fiore; Assembly and C)
• CIS 0835 - Cyberspace and Society (with prof. Wendy Urban; Dreamweaver)