| [1] | Federated computation beyond learning, 2024. Talk at FedKDD workshop. |
| [2] | Private data analysis over large populations, 2024. Talk at Birmingham and Cambridge. |
| [3] | An introduction to federated computation, June 2022. Tutorial presented at SIGMOD and the Web Conference. |
| [4] | Mergeable summaries, 2022. PODS 2022 Test-of-time award presentation. |
| [5] | Frequency estimation in local and multiparty differential privacy, May 2021. Invited talk at Distributed and Private Machine Learning Workshop. |
| [6] | New lower and upper bounds for quantile summary algorithms, Nov. 2020. IGAFIT colloquium and Bar-Ilan University Colloquium. |
| [7] | Towards federated analytics with local differential privacy, Oct. 2020. Talk at Facebook and Google. |
| [8] | Scaling up by scaling down, Feb. 2020. Presentation at the Alan Turing Institute workshop on Data Science and AI at Scale. |
| [9] | Distributed private data collection at scale, Jan. 2020. Talks at Amazon Research and Samsung Research, Cambridge. |
| [10] | Local differential privacy: Solution or distraction?, June 2019. Talk at Google Workshop on Federated Learning and Analytics. |
| [11] | Data science and privacy preservation, June 2019. Tutorial at Trust in Data Science Summer School in Ghent. |
| [12] | Distributed private data collection at scale, 2019. Talk at Edinburgh University, University of Washington. |
| [13] | Data summarization for machine learning, Jan. 2019. Talk at Computer Science Research Week 2019, National University of Singapore. |
| [14] | Data summarization and distributed computation, 2018. Keynote talk at PODC 2018. |
| [15] | G. Cormode, S. Jha, T. Kulkarni, N. Li, D. Srivastava, and T. Wang. Privacy at scale: Local differential privacy in practice, 2018. Tutorial at SIGMOD and KDD. |
| [16] | Distributed private data collection at scale, Jan. 2018. Talk at HiPEDs CDT (Imperial). |
| [17] | Locally private release of marginal statistics, Nov. 2017. Talk at Google (Zurich) Algorithms and Optimization Day. |
| [18] | The confounding problem of private data release, Sept. 2017. Talk at EPSRC Workshop on Future Research Directions in Demand Management, Oxford University (CS). |
| [19] | Engineering streaming algorithms, June 2017. Invited talk at Symposium on Experimental Algorithms. |
| [20] | Engineering privacy for small groups, Nov. 2016. Talk at Isaac Newton Institute. |
| [21] | Matching and covering in streaming graphs, Sept. 2016. Invited keynote talk at DISC 2016. |
| [22] | The confounding problem of private data release, Sept. 2016. Invited talk at Heilbronn Conference; WMG; Liverpool University. |
| [23] | Sub-quadratic recovery of correlated pairs, June 2016. Talk at Google Research, Facebook, Simons Institute, Manchester U., LSE. |
| [24] | Compact summaries over large datasets, May 2015. Invited tutorial in PODS 2015 and BICOD 2015. |
| [25] | Trusting the cloud with practical interactive proofs, Apr. 2015. Talk at Google NYC, Bristol, Oxford Algorithms Day, Durham. |
| [26] | The confounding problem of private data release, Mar. 2015. Invited talk at EDBT/ICDT 2015. |
| [27] | Sampling for big data, Aug. 2014. Tutorial at SIGKDD 2014 conference. |
| [28] | Sketches, streaming and big data, July 2014. Summer school on Hashing at University of Copenhagen. |
| [29] | Differentially private mechanisms for data release, March 2014. Talk at Hamilton Institute; Edinburgh University; Yahoo! Research, New York. |
| [30] | Sketch data structures and concentration bounds / mergeable summaries, Sept. 2013. Invited tutorial at Yandex conference. |
| [31] | Streaming, sketching and sufficient statistics, Sept. 2013. Invited tutorial at Big Data Boot Camp, Simons Institute for Theoretical Computer Science, Berkeley. |
| [32] | Summary data structures for massive data, July 2013. Invited talk in Session on Data Streams and Compression, Computability in Europe 2013. |
| [33] | Computing + statistics = data science, June 2013. An introduction to data science for teenagers, IGGY DUX awards, Experience Warwick. |
| [34] | Streaming verification of outsourced computation, May 2013. Talk at Big Data Analytics Workshop, Microsoft Research Cambridge, and University of Warwick. |
| [35] | Building blocks of privacy: Differentially private mechanisms, Apr. 2013. Invited tutorial talk at Privacy Preserving Data Publication and Analysis (PrivDB) workshop. |
| [36] | Privacy and big data: Challenges and promise, Mar. 2013. Invited panel at NYU Abu Dhabi conference on Big Data Systems, Applications, and Privacy. |
| [37] | Current industry trends in computer science research, Mar. 2013. Invited Talk/Panel at NSF Research Experience for Undergraduates PI Meeting. |
| [38] | Data-driven concerns in private data release, Sept. 2012. Talk at Stevens Institute of Technology; AT&T Labs; UMass Amherst; Rutgers University-Newark; Bell Labs; NYU-Abu Dhabi. |
| [39] | Sketches: Past, present and future, 2012. Invited Panel on Sketching and Streaming at SAMSI Workshop, 2012. |
| [40] | Small summaries for Big Data, 2012. Talk at Duke ARO workshop on Big Data at Large; MSR Cambridge; Princeton. |
| [41] | Continuous distributed monitoring: A short survey, Sept. 2011. Invited keynote at Algorithms and Models for Distributed Event Processing (AlMoDEP). |
| [42] | Some sketchy results, May 2011. Talk at DIMACS Workshop on Algorithms in the Field (8F). |
| [43] | Mergeable summaries, Apr. 2011. Talk at Harvard University; DIMACS; Johns Hopkins; University of Pennsylvania; AT&T Labs; Warwick University. |
| [44] | Data anonymization, Mar. 2011. Guest lecture in 'Dealing with Massive Data' at Columbia University. |
| [45] | Distributed summaries, 2011. Talk at DIMACS workshop on Parallelism: a 2020 vision. |
| [46] | G. Cormode and D. Srivastava. Anonymized data: Generation, models, usage, Mar. 2010. Tutorial at ICDE 2010. |
| [47] | Sipping from the firehose: Streaming interactive proofs for verifying computations, February 2010. Invited talk at Bristol Algorithms Days 2010; University of Maryland. |
| [48] | Progress in data anonymization: from k-anonymity to the minimality attack, February 2010. Talk in Bristol. |
| [49] | Anonymization and uncertainty in social network data, Oct. 2009. Invited talk at DBIR Day 2009 at NYU Poly. |
| [50] | G. Cormode and D. Srivastava. Anonymized data: Generation, models, usage, July 2009. Tutorial at SIGMOD 2009. |
| [51] | Processing graph streams: Upper and lower bounds, June 2009. Talk at Workshop on Algorithms and Models for Complex Networks, Bristol UK. |
| [52] | Finding frequent items in data streams, March 2009. Talk at DIMACS Working group on Streaming, Coding and Compressive Sensing; AT&T Labs; UMass Amherst; Dartmouth College. |
| [53] | On 'selection and sorting with limited storage', Sept. 2008. Talk at Mike66 Workshop celebrating Mike Paterson. |
| [54] | Algorithms for distributed functional monitoring, Aug. 2008. Talk at Dagstuhl Seminar on Sublinear Algorithms. |
| [55] | Data stream algorithms, July 2008. Tutorial at Bristol Summer School on Probabilistic Techniques in Computer Science. |
| [56] | G. Cormode and M. Garofalakis. Streaming in a connected world: Querying and tracking distributed data streams, March 2008. Tutorial at VLDB 2006, SIGMOD 2007, EDBT 2008. |
| [57] | Analyzing web 2.0, blogs and social networks, Dec. 2007. Talk at AT&T Labs. |
| [58] | Computational fundamentals of analyzing and mining data streams, March 2007. Tutorial at Workshop on Data Stream Analysis, Caserta, Italy. |
| [59] | Computing the entropy of a stream, December 2006. AT&T Labs; Bell Labs; DyDAn Center. |
| [60] | A compact survey of compressed sensing, December 2006. Workshop on Algorithms for Data Streams, IIT Kanpur, India. |
| [61] | Biased quantiles, June 2006. Bertinoro. |
| [62] | Cluster and data stream analysis, March 2006. Tutorial at DIMACS Workshop on Data Mining and Epidemiology. |
| [63] | Tracking inverse distributions of massive data streams, July 2005. Network Sampling Workshop in Paris, Bell Labs Research Seminar. |
| [64] | Towards an algorithmic theory of compressed sensing, July 2005. Schloss Dagstuhl. |
| [65] | Summarizing and mining skewed data streams, May 2005. NJIT. |
| [66] | Algorithms for processing massive data at network line speed, March 2004. Talk at U. Iowa; U. Minnesota; Dartmouth; Google; AT&T; CWRU; Poly. |
| [67] | How hard are computer games?, February 2004. Talk at DIMACS. |
| [68] | What's hot, what's not, what's new and what's next, October 2003. Bell Labs; DIMACS Mixer at AT&T Labs. |
| [69] | Zeroing in on the l0 metric, August 2003. DIMACS Workshop on Discrete Metric Spaces and their Algorithmic Applications at Princeton. |
| [70] | Tracking frequent items dynamically, 2003. Institute of Advanced Studies; DIMACS; Stonybrook; U. Pennsylvania. |
| [71] | Algorithmic embeddings for comparing large text streams, June 2002. CCR/DIMACS Workshop/Tutorial on Mining Massive Data Sets and Streams: Mathematical Methods and Algorithms for Homeland Defense. |
| [72] | Embeddings of metrics on strings and permuations, March 2002. Workshop on Discrete Metric Spaces and their Algorithmic Applications in Haifa, Israel; BCTCS. |
| [73] | Short string signatures, September 2000. DIMACS Workshop on Sublinear Algorithms in Princeton, NJ. |
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