Google Scholar, DBLP


  1. Saket Sathe, Charu Aggarwal, Horst Samulowitz, Deepak Turaga. Feature-Engineered Random Forests. SIAM SDM, 2024.
  2. Saket Sathe, Charu Aggarwal. Nearest Neighbor Classifiers versus Random Forests and Support Vector Machines. IEEE ICDM, 2019. [slides]
  3. Liang Duan, Charu Aggarwal, Shuai Ma, Saket Sathe. Improving Spectral Clustering with Deep Embedding and Cluster Estimation. IEEE ICDM, 2019. Best of ICDM 2019
  4. Saket Sathe, Charu Aggarwal, Xiangnan Kong, Xinyue Liu. Kernel-Based Feature Extraction For Collaborative Filtering. IEEE ICDM, 2017. [slides]
  5. Saket Sathe and Charu Aggarwal. Similarity Forests. ACM SIGKDD, 2017. [slides]
  6. Jinghui Chen, Saket Sathe, Charu Aggarwal, Deepak Turaga. Outlier Detection with Autoencoder Ensembles. SIAM SDM, 2017.
  7. Sue A. Chen, Arun Vishwanath, Saket Sathe. Data-driven characterisation of solar PV panel performance. IEEE ISGT Europe, 2017.
  8. Saket Sathe and Charu Aggarwal. Subspace Outlier Detection in Linear Time with Randomized Hashing. IEEE ICDM, 2016. [slides] Best of ICDM 2016
  9. Saket Sathe and Charu Aggarwal. LODES: Local Density Meets Spectral Outlier Detection. SIAM SDM, 2016.
  10. Xinyue Liu, Charu Aggarwal, Yu-Feng Li, Xiangnan Kong, Xinyuan Sun, Saket Sathe. Kernelized Matrix Factorization for Collaborative Filtering. SIAM SDM, 2016.
  11. Lianhua Chi, Saket Sathe, Bo Han, Yun Wang. A Novel Method for Assessing Event Impacts on Event-Driven Time Series. DMS Workshop (co-located with ICDM 2016).
  12. Sue Ann Chen, Arun Vishwanath, Saket Sathe. What is happening to my watts? A data-driven study of solar panel performance. DSFEW Workshop (co-located with KDD 2016).
  13. Tian Guo, Saket Sathe, Karl Aberer. Fast Distributed Correlation Discovery Over Streaming Time-Series Data. CIKM 2015.
  14. Oshini Goonetilleke, Saket Sathe, Timos Sellis, Xiuzhen Zhang. Microblogging Queries on Graph Databases: An Introspection. GRADES 2015 Workshop (co-located with SIGMOD 2015).
  15. Saket Sathe, Timos Sellis, Karl Aberer. On Crowdsensed Data Acquisition using Multi-Dimensional Point Processes. ICDE Workshops, 2015.
  16. Nguyen Quoc Viet Hung, Saket Sathe, Duong Chi Thang, Karl Aberer. Towards Enabling Probabilistic Databases for Participatory Sensing. CollaborateCom 2014. (acceptance: 20%) Best Paper Runner-up
  17. Saket Sathe, Roie Melamed, Peter Bak, Shivkumar Kalyanaraman. Enabling Location-Based Services 2.0: Challenges and Opportunities. IEEE MDM 2014.
  18. Saket Sathe, Arthur Oviedo, Dipanjan Chakraborty, Karl Aberer. EnviroMeter: A Platform for Querying Community-Sensed Data. VLDB 2013. (demo)
  19. Saket Sathe, Karl Aberer. AFFINITY: Efficiently Querying Statistical Measures on Time-Series Data. IEEE ICDE, 2013. [talk]
  20. Sebastian Cartier, Saket Sathe, Dipanjan Chakraborty, Karl Aberer. ConDense: Managing Data in Community-driven Mobile Geosensor Networks. IEEE SECON, 2012. [talk]
  21. Saket Sathe, Sebastian Cartier, Dipanjan Chakraborty, Karl Aberer. Effectively Modeling Data from Large-area Community Sensor Networks. ACM/IEEE IPSN, 2012. (poster paper)
  22. Saket Sathe, Hoyoung Jeung, Karl Aberer. Creating Probabilistic Databases from Imprecise Time-Series Data. IEEE ICDE, 2011. [talk] [teaser]
  23. K. Aberer, S. Sathe, D. Chakraborty, A. Martinoli, G. Barrenetxea, B. Faltings, L. Thiele. OpenSense: Open Community Driven Sensing of Environment. ACM SIGSPATIAL IWGS, 2010, (co-located with GIS 2010). [talk]
  24. H. Jeung, S. Sarni, I. Paparrizos, S. Sathe, K. Aberer, N. Dawes, T. Papaioannou, M. Lehning. Effective Metadata Management in Federated Sensor Networks. IEEE SUTC, 2010. (invited paper) [talk]
  25. E. Ioannou, S. Sathe, N. Bonvin, A. Jain, S. Bondalapati, G. Skobeltsyn, C. Niederee, Z. Miklos. Entity Search with NECESSITY. WebDB, 2009. (co-located with PODS/SIGMOD) (demo).
  26. Saket Sathe and Uday Desai. Cell-phone Based Microcredit Risk Assessment using Fuzzy Clustering. IEEE ICTD, 2006.
  27. Saket Sathe. A Novel Bayesian Classifier using Copula Functions. Unpublished Manuscript, 2006 [arXiv]


  1. Liang Duan, Shuai Ma, Charu Aggarwal, Saket Sathe. Improving Spectral Clustering with Deep Embedding, Cluster Estimation and Metric Learning. Knowledge and Information Systems (KAIS), pp. 675-694, 2021.
  2. Saket Sathe, Sayani Aggarwal, Jiliang Tang. Gene Expression and Protein Function: A Survey of Deep Learning Methods. SIGKDD Explorations, 21(2), pp. 23-38, 2019.
  3. Saket Sathe and Charu C. Aggarwal. Subspace Histograms for Outlier Detection in Linear Time. Knowledge and Information Systems (KAIS), pp. 1-25, 2018.
  4. Sue Ann Chen, Arun Vishwanath, Saket Sathe, Shivkumar Kalayanaraman. Shedding Light on the Performance of Solar Panels: A Data-Driven View. SIGKDD Explorations, 17(2), pp. 24-36, 2015.
  5. Charu Aggarwal, Saket Sathe. Theoretical Foundations and Algorithms for Outlier Ensembles. SIGKDD Explorations, 17(1), pp. 24-47, 2015.
  6. Oshini Goonetilleke, Timos Sellis, Xiuzhen Zhang, Saket Sathe. Twitter Analytics: A Big Data Management Perspective. SIGKDD Explorations, 16(1), pp. 11-20, 2014.
  7. Hoyoung Jeung, Hua Lu, Saket Sathe, Man Lung Yiu. Managing Evolving Uncertainty in Trajectory Databases. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2014.


  1. Saket Sathe and Gleb Skobeltsyn. Method of Data Retrieval, and Search Engine using such a Method. EPFL. January 2011 : US 2011/0022600A1
  2. Vinay Kolar, Saket Sathe, Ravindranath Kokku, Shivkumar Kalyanaraman, Spatio-temporal monitoring and prediction of asset health.
  3. Saket Sathe, Marie Ng, Frank Lingtao, Deepak Turaga, Charu Aggarwal. Accurate Temporal Event Prediction using Average Reverse Event Delay.
  4. Arun Vishwanath, Saket Sathe, Sue Ann Chen. System and Method for Data-Driven Collaborative Ad-Insertion in Online Video Streams to Enhance User Experience.
  5. Saket Sathe, Deepak Turaga, Charu Aggarwal. A System and Method for Ease-of-Drive Driving Directions
  6. Arun Vishwanath, Sue Ann Chen, Saket Sathe. System and method to create a contact group using image analytics
  7. Saket Sathe, Deepak Turaga, Horst Samulowitz, Charu Aggarwal. A System and Method for Building Random Feature Transformation Forests
  8. Saket Sathe, Deepak Turaga, Charu Aggarwal, Raju Pavaluri, Yuan-Chi Chang. Enhancing Supervised Ensemble Models using Unsupervised Methods
  9. Kanthi Sarpatwar, Venkata S. Ganapavarapu, Saket Sathe, Roman Vaculin. A System and Method for Efficient Unsupervised Anomaly Detection on Encrypted Data [high-value patent]
  10. Yuan-Chi Chang, Deepak Turaga, Long Vu, Raju Pavaluri, Saket Sathe, Rodrigue Ngueyep. Automated data and label creation for supervised machine learning regression testing
  11. Saket Sathe, Long Vu, Peter Kirchner, Horst Samulowitz. Automated Unsupervised Machine Learning Utilizing Meta-Learning
  12. Long Vu, Saket Sathe, Peter Kirchner, Greg Bramble. Automated Lookback Window Searching
  13. Saket Sathe, Gregory Bramble, Long Vu, Theodoros Salonidis. Distributed resource-aware training of machine learning pipelines [high-value patent]
  14. Girik Malik, Meng Li, Saket Sathe, Yue Zhao. Dynamic Machine Learning Pipeline Selection

Book Chapters

  1. Saket Sathe, Thanasis G. Papaioannou, Hoyoung Jeung, Karl Aberer. A Survey of Model-Based Sensor Data Acquisition and Management. Managing and Mining Sensor Data, ed. Charu Aggarwal, Springer Publishers, 2013.


  1. Saket Sathe. Statistical Models for Querying and Managing Time-Series Data. EPFL PhD Thesis, 2013
  2. Saket Sathe. Methods in Quantitative Risk Management. IIT Bombay, Masters Thesis, 2006.

Technical Reports

  1. Saket Sathe, Karl Aberer. AFFINITY: Efficiently Querying Statistical Measures on Time-Series Data. EPFL Technical Report (180121), 2012.
  2. Sebastian Cartier, Saket Sathe, Dipanjan Chakraborty, Karl Aberer. ConDense: Managing Data in Community-driven Mobile Geosensor Networks. EPFL Technical Report (174752), 2012.
  3. Alexandru Arion, Saket Sathe. Efficient Model-Driven Query Processing Based on Data Regeneration. Advanced Topics in Database Systems, Course Project Report, 2009. (Advisor: Prof. Anastasia Ailamaki)
  4. Saket Sathe. Rumor Spreading in LiveJournal. Dynamical Networks, Course Project Report, 2008. (Advisor: Prof. Martin Hasler)