Old News
A list of old news, moved here from the home page, mostly for my personal records.
- SDM'23: my idea on Statistically-sound Knowledge Discovery from Data is accepted for the new Blue Sky track at SIAM SDM'23. See you in Minneapolis!
- ACM TIST: with Giulia and Gianmarco from CentAI, we published the journal version of our KDD'21 paper on approximately counting subgraphs.
- ECML PKDD'23: I'm the PhD Forum Chair, together with Illka Velaj. If you are a PhD student, please consider submitting a poster (when submission open in May).
- ACM TKDD: The journal version of Bavarian, our algorithm for betweennes centrality approximation with variance-aware Rademacher averages will appear in ACM TKDD. We show a novel analysis of the variance of the estimators, a discussion about using matrix multiplication, and much more.
- DMKD/DAMI: The journal version of our WSDM'21 paper on adding edges to reduce polarization in graphs will be included in the DMKD/DAMI special issue on Bias and Fairness. In this version, we show a new algorithm that modifies edge weights, thus being less intrusive.
- ICDM'22: Another collaboration with Giulia and Gianmarco from CentAI has been accepted. We present a more representative null model for testing the significance of data mining results from transactional datasets, and Alice, an algorithm to sample from this null model. See you in Orlando for ICDM'22!
- DMKD/DAMI (ECML PKDD'22): Another work by the Data* Mammoths has been accepted: Steedman and Stefan developed SPEck, a set of Monte-Carlo procedures for efficiently mining statistically-significant sequential patterns according to different null models, using exact sampling, rather than approximate sampling. It appears in the DMKD/DAMI special issue for ECML PKDD'22.
- MDS'22: My talk on Scalable Algorithms for Hypothesis Testing has been accepted for presentation at the "new" (as the 2020 edition was canceled) SIAM Conference on Mathematics of Data Science, which has a super strong program.
- TKDD: the extended version of MCRapper was accepted to ACM TKDD. An elegant algorithm to compute Rademacher averages for families of function with a natural poset structure, which are omnipresent in pattern mining. Nice collab with Leonardo, Cyrus, and Fabio.
- AAAI'22: the Data* Mammoths' work on parallel algorithms for cube sampling was accepted for publication as a student abstract/poster to AAAI'22. Fun work by brilliant undergraduate researchers: it started with Shukry's honors thesis, and Alex and Stefan brought it to completion.
- SDM'22: I'm excited and honored to be PC-chair of SIAM SDM'22, together with the great Vagelis Papalexakis, and a wonderful OC. Looking forward to receiving interesting submissions on data mining, knowledge discovery, and its statistical aspects.
- KDD'21: Two papers accepted in the research track: Bavarian, on betweenness centrality approximation, and MaNIACS, on approximating the frequent subgraphs in a large graph through sampling.
- WSDM'21: RePBubLik wins a Best Paper Award Honorable Mention! Yay!
- KTH talk (2/18): Giving a talk about RePBubLik at KTH. Thank you Aris and Stefan for inviting me!
- TKDD: TipTap, our work on maintaining frequent subgraphs in fully-dynamic edge graph streams has been accepted to ACM TKDD. Nice work using reservoir sampling and random pairing, with Gianmarco, Cigdem, and Anis.
- Fidelity (10/28): giving a talk on MCRapper at Fidelity, thank you Serdar for inviting me.
- WSDM'21: RePBubLik: Reducing the Polarized Bubble Radius with Link Insertions was accepted to WSDM'21, a venue dear to me. Joint work with the Brown crew: Shahrzad Haddadan, Cristina Menghini, and Eli Upfal.
- UMass talk (10/6): I'll be giving a talk on MCRapper at the Theory seminar. Thanks Cameron for inviting me!
- NeurIPS'20: our paper (w/ soon-to-be-PhD-extraordinaire Cyrus Cousins) "Sharp uniform convergence bounds through empirical centralization" was accepted. This work is theoretical and fun!
- NSF Grant: My project on Scalable and Iterative Statistical Testing of Multiple Hypotheses on Massive Datasets has been funded! Thanks NSF! I really look forward to the work ahead.
- SDM'21: I will be the Tutorial Chair and a member of the Senior PC for SIAM SDM'21. Always glad to be of service to the knowledge discovery, data mining, and statistics communities.
- KDD'20: MCRapper, our work on computing the Monte Carlo Empirical Rademacher Average on poset families for approximate pattern mining has been accepted as a full paper in the research track. Join work with the statistics-datamining gang: Leonardo Pellegrina, Cyrus Cousins, and Fabio Vandin.
- TKDD: The extended version of MiSoSouP, our algorithm for mining interesting subgroups through sampling with pseudodimension has been accepted to the TKDD special issue for the best papers of KDD'18. Joint work with great colleague Fabio Vandin.
- DMKD: Very honored to become a member of the editorial board of Data Mining and Knowledge Discovery journal, one of the top venues in my area of research.
- MDS'20: My talk on Algorithms for Scalable Hypothesis Testing has been accepted for presentation at the new SIAM Conference on Mathematics of Data Science, which has a super strong program.
- SDM'20: We'll present our tutorial on Statistical Hypothesis Testing and Pattern Mining at SIAM SDM'20, a great event bringing together computer scientists and statisticians.
- NetSciI@NEU (11/8): I'll be giving a talk at the Network Science Institute at Northeastern University. Thank you Tina for inviting me: the place and people there are wonderful and do super cool work.
- MassMutual Research Bytes(11/5): I'll be giving a talk on making better use of data through hypothesis testing and statistical learning theory. Thank you Nick for inviting me.
- BU (10/25): I'll be giving a talk at Boston University. Thank you Evimaria for inviting me.
- MHC (10/16): I'll be giving a talk at Mount Holyoke College. Thanks to Valerie for inviting me.
- CaStleD'19: I'm giving a talk on CaDET at CaStleD'19 in Bertinoro. Thank you Fabio for inviting me.
- ECML PKDD: CaDET, our algorithm for interpretable conditional density estimation using decision trees has been accepted to the special issue of Machine Learning for ECML PKDD'19. Joint work with thinker-extraordinaire PhD student Cyrus Cousins.
- GPG key: I updated my GPG key, which had expired. The keys did not change, only the expiration date.
- ACM KDD: SPuManTE, our work on unconditional multiple hypothesis testing for combinatorial patterns has been accepted to KDD'19. Joint work with thought leader Fabio Vandin and amazing Ph.D. student Leonardo Pellegrina.
- ACM KDD: Our tutorial on multiple hypothesis testing and statistically-sound pattern mining (2-pager) has been accepted to ACM KDD'19. See you in Anchorage, AK!
- KAIS: an extended version of ProSecCo: Progressive Sequence Mining with Convergence Guarantees was invited to the special issue of KAIS for the best papers of IEEE ICDM'18.
- ACM TKDD: an extended version of MiSoSouP was invited to the special issue of ACM TKDD for the best papers of KDD'18.
- ICERM: Happy to give a talk about pseudodimension for data analysis at the Data Science in Low-dimensional Spaces workshop taking place at ICERM. Even more excited to hear about exciting research from others.
- Teaching: in my first semester at Amherst College, I'm teaching Data Mining and Intro to CS 1. Thrilled to be working closely with brilliant students again.
- PCs and editorial board: glad to serve on the PC for ICML'19, ACM KDD'19, NetSci'19, and IJCAI'19, and on the guest editorial board of the Data Mining and Knowledge Discovery journal for ECML PKDD'19.
- SDM'19: I'm serving as co-chair of the Doctoral Forum for SIAM SDM'19. Very excited to help with the organization, as I won the best student poster award at this event in 2014.
- ICDM'18: ProSecCo: Progressive Sequence Mining with Convergence Guarantees was recognized as the best student paper award runner-up of IEEE ICDM'18. Congrats to superstar undergrad Sacha Servan-Schreiber and postdoc Emanuel Zgraggen!
- New job: In January 2019 I will be joining the computer science department at Amherst College as an assistant professor.
- Invited talks: on 11/26 I am giving a guest lecture at Harvard, for the COMPSCI-134 Networks talk, invited by Michael Mitzenmacher and Yaron Singer. I will also be speaking at Google Research NY on 4/12, on MiSoSouP, thanks to Alessandro Epasto for the invite.
- ICDM'18: Our work "ProSecCo: Progressive Sequence Mining with Convergence Guarantees" has been accepted as full paper at IEEE ICDM'18. This result is joint work with amazing Brown CS undergradSacha Servan-Schreiber and star MIT postdoc Emanuel Zgraggen.
- Dagstuhl: Very happy to attend the Automating Data Science workshop in the very-conducive-to-collaboration environment of Dagstuhl at the beginning of October.
- AAAI'19: Happy to join the PC of AAAI'19, one of the longest running conferences in computer science and a leading conference for AI.
- HLF'18: I have been selected as a Young Researcher for the Heidelberg Laureate Forum! Really excited to go meet brilliant minds of all ages in September.
- FouLarD'18: I'm co-organizing FouLarD'18, a workshop on the foundations of learning from data, together with Mehryar Mohri, Alessandro Panconesi, and Eli Upfal. It will take place in Bertinoro, Italy, in September 2018.
- Sharpe ratio TR: my technical report on the Sharpe ratio is now available. The Sharpe ratio is a fundamental metric to evaluate investment strategies. This literature survey is part of the Two Sigma Technical Report series.
- KDD'18: MiSoSouP, our algorithm for subgroup discovery using random sampling and pseudodimension has been accepted for long presentation at KDD'18. Joint work with superstar co-author Fabio Vandin. Very happy that all the work we put in this paper paid off.
- ACM TKDD: ABRA, our work (with Eli) on approximating betweenness centrality with Rademacher averages was accepted for publication in ACM TKDD.
- IEEE ICDM'18: I'm serving on the PC of IEEE ICDM'18, which will be in Singapore in November.
- ECML PKDD'18: Happy to serve on the PC of ECML PKDD'18, my "home" conference in many ways, and a great venue for algorithmic data science.
- Talk at Harvard: On 5/7 I talk about Sampling-based Approximation Algorithms for Data Analysis using Rademacher Averages at the Theory of Computation Seminar at Harvard. Thanks to Mike Mitzenmacher for inviting me.
- Grace Hopper'18: I'm proud to be serving on the program commitee for the Data Science track of the Grace Hopper Celebration, the premier event for women technologists.
- ACM CIKM'18: I'm on the PC of ACM CIKM'18, which takes place in Turin in October.
- ACM KDD'18: I'll be serving on the PC of ACM KDD'18, the major conference on data mining.
- Teaching at Brown CS: I'm teaching CSCI 1951-G Optimization Methods in Finance again in Spring'18. So rewarding to be in class with brilliant students again!
- SIAM SDM'18: I'll be the sponsorship co-chair for SIAM SDM'18. I'm excited to contribute to the organization of this great conference stressing the importance of theory in data mining.
- Visiting NII: From 11/12 to 11/22 I'll be visiting Yuichi Yoshida at the National Institute of Informatics in Tokyo, Japan, where I will also give a talk. I'm thrilled to spend a wiki with Yuichi, who is an incredibly smart, world-class researcher combining theory and data mining.
- PC memberships: I joined the PCs of ACM CIKM'17 and IEEE ICDE'18. Looking forward to reviewing more works at the intersection of data management and data analytics.
- New GPG/PGP key: I revoked my old GPG key and created a new one (ASCII-armored file).
- WWW'18: I'll be in the PC for the next (World Wide) Web Conference.
- NYU: On May 17 I'm giving a talk on ABRA at the NYU Center for Data Science.
- Dagstuhl: I am giving a talk on Rademacher Averages and ABRA at the Probabilistic Methods in the Design and Analysis of Algorithms at Schloss Dagstuhl.
- Grace Hopper'17: I am a member of the Scholarship review committee for this wonderful event.
- ACM TKDD: the extended version of TRIÈST has been accepted for publication.
- ECML PKDD'17: I joined the PC. This year the conference takes place in Skopje, Macedonia.
- KDD'17: I am a member of the Senior Program Committee. Looking forward to reviewing many good submissions!
- ICDM'16: I'm attending IEEE ICDM'16 in Barcelona from 12/12 to 12/15. Drop me a line if you would like to meet.
- Boston University (11/18): I'm talking about ABRA, hosted by Evimaria Terzi.
- IEEE MIT URTC (11/05): I'm a keynote speaker at the IEEE MIT Undegraduate Technology Conference. My talk will be about algorithmic data science as a way of combining theory and practice. I'm excited and honored to share my point of view with brilliant young minds.
- IEEE ICDE'17: I'm on the PC for next year ICDE.
- WWW'17: I'm on the PC for next year's WWW.
- Carnegie Mellon University (10/24): Giving a talk on TRIÈST at the database group meeting, hosted by Andy Pavlo.
- Network Science Institute @ Northeastern University (10/17): I'm talking about ABRA, hosted by Tina Eliassi-Rad.
- University of Padua (9/26): I'm giving a talk on graph summarization at DEI (Department of Information Engineering). Excited to speak at my alma mater.
- ACM KDD'16: TRIÈST wins the best student paper award (Research track). I feel very honored, and thankful to the PC and to my coauthors (Lorenzo De Stefani (the student), Alessandro Epasto, and Eli Upfal).
- arXiv: a much longer version of TRIÈST is now available.
- ACM WSDM'17: I joined the Program Committee of WSDM'17, a conference I always enjoy so much.
- IEEE ICDM'16: I joined the Program Committee of ICDM'16, which takes place in the most awesome city of Barcelona.
- ACM KDD'16: Two papers of mine (ABRA and TRIÈST) were accepted as full presentations. See you in SF in August!
- ACM CIKM'16: I joined the Program Committee of ACM CIKM'16. Nice event that brings together different communities.
- ECML PKDD'16: I am a member of the Program Committee. This year the conference will be in beautiful Riva del Garda, on Lake Garda, Italy, very close to my hometown Padua!
- SINS'16: I'm giving a talk on ABRA at SINS'16, a workshop on Social Impact through Network Science. It takes place in Venice, in June. Looking forward to meeting many people there!
- GHC'16: I'm so very excited to be part of the PC for the Data Science track at Grace Hopper 2016, the celebration of women in computing.
- arXiv: Two new works on the arXiv, one on approximate counting triangles from streams (joint work with Alessandro Epasto, Lorenzo De Stefani, and Eli Upfal), and one on fully-dynamic betweenness centrality approximation (joint work with Eli Upfal). Sampling rules everything around me, and these two papers show it.
- DAMI/DMKD: Our paper Graph Summarization with Quality Guarantees (joint work with David García-Soriano and Francesco Bonchi) was accepted for publication. Geometric clustering and extremal graph theory get together, and the chemistry is great!
- WWW'16: We are giving our tutorial Centrality Measures on Big Graphs: Exact, Approximated, and Distributed Algorithms (joint work with Francesco Bonchi and Gianmarco De Francisci Morales). I am also a member of the PC and will chair the Social Networks and Graph Analysis 1 session. See you in Montreal!
- ACM KDD'16: I'm a PC member for the Research track. After WSDM'16, another trip to San Francisco to hear about exciting research.
- ACM WSDM'16: Our paper Wiggins: Detecting Valuable Information in Dynamic Networks with Limited Resources (joint work with Eli Upfal and Ahmad Mahmoody) was accepted.
- Brown University: In Spring 2016, I am teaching Optimization Methods in Finance, in the Department of Computer Science. A wonderful area of computer science, with relevant applications. As usual, I will be balancing theory and practice.
- Stevens Institute of Technology: on Thursday 12/10 I will give a guest lecture on Data Mining, hosted by George Valkanas.
- Monash University: On Wednesday 10/28 I'm giving a talk: Travel pictures from another world: Statistical Learning Theory meets Data Mining.
- CIKM'15: On Friday 10/23, I'm presenting a tutorial on VC-Dimension and Rademacher Averages for sampling algorithms.