Invited Talks

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

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