Marian-Andrei Rizoiu

Professional Webpage

Presenting at the conference ICTAI 2012, November, Athens

Research

My research revolves around artificial intelligence, machine learning and data mining. More specifically, I am interested in Social Media Analysis, Popularity Modelling and Prediction and Online Privacy. Previous interests include knowledge injection into non-supervised learning algorithms, data representation and temporal evolutions.

See more about my research.

News

2016-05-03: Check out our brand new Computational Media lab page.

2016-03-16: Our work got the attention of Wikimedia Research! I presented "Evolution of Privacy Loss on Wikipedia" in the March session of the Monthly Wikimedia Research Showcase. See recording here.

2015-10: Our paper "Evolution of Privacy Loss on Wikipedia" has just been accepted at the WSDM 2016 conference in San Francisco!

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My Publications.

Journals

Conference proceedings

Book chapters

PhD thesis

Masters thesis

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Research topics.

My research revolves around artificial intelligence, machine learning and data mining. More specifically, I am interested in Social Network Analysis, popularity prediction, knowledge injection into non-supervised learning algorithms, data representation and temporal evolutions. I deal with large datasets of complex data (textual, image), often issued from the online social media and my main tools are modeling and simulation, clustering and topic modeling.

A little more details

My current research interest is to model theoretically popularity on online media, as well as estimate the influence of media content and network characteristics on online attention. We established a generative model that predicts online attention, based on an exogenously-driven Hawkes self-exciting processes. We also examine the geographical diffusion of media content over time and the goal is to generate statistical descriptions of content diffusion over time and geographical areas. We are handling very large Twitter datasets (the network), which relate to Youtube videos (the content).

My previous work dealt with how partial expert information can be leveraged into a non-supervised learning algorithm that treats complex data. This complex data is of different natures (text, image), it is temporal and structured, linked to knowledge repository (e.g. ontology) and/or labeled. Semi-supervised clustering is used to model the additional information (structure, labels, time) and to inject the heterogeneous information into the learning algorithm. A series of application emerge from the theoretical research: using the temporal dimension to detect temporal patters and typical evolutions, using the image labels to improve image numerical representation and an automatic topic evaluation using concept trees.

My collaborators

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Involvement in scientific projects

Seminars and invited talks

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Teaching.

Advanced Databases
and Data Mining

ANU Undergraduate

This course is for the third year of undergraduates in the Research School of Computer Science. It presents relational theory and conceptual modelling; privacy and security; statistical databases; distributed databases; data warehousing; data cleaning and integration; and data mining concepts and techniques. I give lectures concerning databases and data warehousing and data cleaning and integration.

Document Analysis
 

ANU Postgraduate

This course is for the third year of undergraduates in the Research School of Computer Science, as well as Honnors students. It presents techniques related to processing online document, such as (A) information retrieval, (B) natural language processing, (C) machine learning for documents, and (D) relevant tools for the Web. I give lectures concerning the machine learning part and the social media and sentiment analysis part.

Numerical Machine Learning

European M2 DMKM

This course is for the second year in the Excellence European Master DMKM. It presents advanced machine learning techniques. Together with S. Lallich , we present association rules mining and class rules mining, ensemble methods (bagging, boosting) and statistical testing procedures (cross-validation, student t-test, etc.).

I give practical lectures for this course.

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Biography.

Since March 2016, I am a Research Fellow with the College of Engineering and Computer Science at the Australian National University in Canberra. I am equally affiliated with the Data61 unit of CSIRO, in the Decision Sciences team.

Previously

Between May 2014 and February 2016,I was a researcher within the National ICT Australia in Canberra Australia, working in the Optimization Research Group. I was equally an adjunct lecturer with the College of Engineering and Computer Science at the Australian National University in Canberra.

Between September 2013 and May 2014, I was a PostDoctoral researcher with the ERIC Laboratory, financed by the ImagiWeb Research Project. I was equally an assistant professor with the DIS Department, at the University Lumière in Lyon.

Between 2009 and 2013, I was a PhD student at the ERIC Laboratory with the University Lumière Lyon2, under the supervision of Stéphane Lallich and Julien Velcin. I defended my PhD thesis on June 24th 2013, with honors "Très Honorable".

In July 2009, I obtained my MSc (graduating first of promotion, with honors.) in Data Mining and Knowledge Management from the Polytechnic School of the University of Nantes, France and wrote my Master’s Thesis on "Textual Data Clustering and Cluster Naming" after an internship at the ERIC Laboratory.

Between 2004 and 2009, I did my undergrad and obtained in September 2009 my Engineer Diploma (double diploma, in parallel with the French Master's) in System and Computer Engineering from the Faculty of Automatic Control and Computers of the Polytechnic University Bucharest, Romania.

In 2004, I did my Scientific Baccalaureate in Mathematics and Computer Science, Romania.

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