14-18 JANUARY 2019, CAPE TOWN, SOUTH AFRICA

AFIRM: ACM SIGIR/SIGKDD Africa Summer School on Machine Learning for Data Mining and Search

Call for Participation

We invite African students and researchers to participate in the First Africa Summer School on Machine Learning for Data Mining and Search, sponsored by ACM SIGIR and SIGKDD, hosted at the University of Cape Town, and presented by leading international researchers.

The mission of the school is to enable students to learn about modern research challenges and methods in information retrieval and data mining; to stimulate scientific research and collaboration in these fields; and to grow a community of researchers, students, and industry professionals working on information retrieval and data mining across Africa with collaborations all around the world.

The target audience is junior faculty from institutions across Africa and advanced graduate students in Africa, with the vision that attendees take their new insights back to their home institutions to grow a vibrant research community in information retrieval and data mining.

The workshop will offer a week of lectures and labs for an audience of up to 50 students. Each day will centre around a broad theme in information retrieval and data mining and consist of lectures on aspects of that theme and hands-on lab time. The program will also include keynote addresses, panels, poster sessions and social events.

SPEAKERS

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Daniel Campos is a Program Manager at Microsoft USA. He joined Microsoft in 2015 and Bing in 2017 where he has been working on offline relevance judgments, metrics, and applied research for document ranking. He has also been building MSMARCO dataset and exploring how the worlds of AI, Question Answering, and Information Retrieval all are connected.. He is currently pursuing his MS in Computational Linguistics at the University of Washington and received his BS in Computer Science from Rensselaer Polytechnic Institute in 2015 where he focused on multi-lingual NLP.

Daniel Campos Microsoft AI & R and University of Washington, USA

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Ben Carterette is an Associate Professor at the University of Delaware and a Senior Research Scientist and Lab Lead at Spotify Research. His research is on experimentation in search and recommender systems, novelty in search results, and user search sessions. He has published nearly a hundred papers, won several best paper awards, been awarded national research grants, and graduated four PhD students. He has chaired conferences such as the ACM International Conference on Web Search and Data Mining (WSDM) in 2014 and the ACM International Conference in the Theory of Information Retrieval (ICTIR) in 2016, co-coordinated tracks for the Text Retrieval Conference (TREC) for 10 years, and in 2016 was elected to the position of Treasurer for the ACM SIGIR Executive Committee.

Benjamin Carterette (AFIRM 2019 Dean and Moderator) Spotify Research and University of Delaware, USA

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Nick Craswell is a Principal Group Applied Science Manager at Microsoft USA. On the product side his team is responsible for a variety of relevance metrics at Bing, using online A/B testing to measure the utility of the system, as well as offline relevance judgments to monitor relevance and trustworthiness of results. His science team currently works on new search technology such as next-generation search data/metrics, how to optimize this using machine learning, and how to make information seeking more conversational. He joined Microsoft in Cambridge UK in 2004 and moved to Seattle in 2009 to work more directly on product development. He received his PhD from the Australian National University in 2000 and worked at CSIRO before joining Microsoft.

Nick Craswell Microsoft Research, USA

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Maarten de Rijke is University Professor of Artificial Intelligence and Information Retrieval at the University of Amsterdam. He holds MSc degrees in Philosophy and Mathematics (both cum laude), and a PhD in Theoretical Computer Science. He worked as a postdoc at CWI, before becoming a Warwick Research Fellow at the University of Warwick, UK. He joined the University of Amsterdam in 1998, and was appointed full professor in 2004. He is a member of the Royal Netherlands Academy of Arts and Sciences (KNAW) and a recipient of a Pioneer Personal Innovation grant, the Tony Kent Strix Award, the Bloomberg Data Science Research Award, the Criteo Faculty Research Award, the Google Faculty Research Award, the Microsoft PhD Research Fellowship Award, and the Yahoo Faculty and Research Engagement Program Award as well as a large number of NWO grants.
He is the director of the newly established Innovation Center for Artificial Intelligence and a former director of Amsterdam Data Science.
De Rijke leads the Information and Language Processing Systems group at the Informatics Institute of the University of Amsterdam, one of the world’s leading academic research groups in information retrieval. His research focus is at the interface of information retrieval and artificial intelligence, with projects on online and offline learning to rank, on recommender systems, and on conversational search.
A Pionier personal innovational research incentives grant laureate (comparable to an advanced ERC grant), De Rijke has helped to generate over 65MEuro in project funding. With an h-index of 69 he has published over 750 papers, published or edited over a dozen books, is editor-in-chief of ACM Transactions on Information Systems, co-editor-in-chief of Foundations and Trends in Information Retrieval and of Springer’s Information Retrieval book series, (associate) editor for various journals and book series, and a current and former coordinator of retrieval evaluation tracks at TREC, CLEF and INEX. Recently, he was co-chair for SIGIR 2013, general co-chair for ECIR 2014, WSDM 2017, and ICTIR 2017, co-chair “web search systems and applications” for WWW 2015, short paper co-chair for SIGIR 2015, and program co-chair for information retrieval for CIKM 2015. He is the general chair for FAT*2020.
The retrieval and language technology developed by De Rijke’s research group is being used by organizations around the Netherlands and beyond, and has given rise to various spin-off initiatives.
Information and Language Processing Systems group
Innovation Center for Artificial Intelligence

Maarten de Rijke University of Amsterdam, The Netherlands

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Nicola Ferro (http://www.dei.unipd.it/~ferro/) is associate professor in computer science at the University of Padua, Italy. His research interests include information retrieval, its experimental evaluation, multilingual information access and digital libraries. He is the coordinator of the CLEF evaluation initiative, which involves more than 200 research groups world-wide in large-scale IR evaluation activities. He was the coordinator of the EU Seventh Framework Programme Network of Excellence PROMISE on information retrieval evaluation. He is associate editor of ACM TOIS and was general chair of ECIR 2016.

Nicola Ferro Department of Information Engineering, University of Padua, Italy

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Joshua A. Kroll is a computer scientist studying the relationship between governance, public policy, and computer systems. As a Postdoctoral Research Scholar at the School of Information at the University of California at Berkeley, Joshua's research focuses on how technology fits within a human-driven, normative context and how it satisfies goals driven by ideals such as fairness, accountability, transparency, and ethics. He is most interested in the governance of automated decision-making systems, especially those using machine learning. His paper "Accountable Algorithms" in the University of Pennsylvania Law Review received the Future of Privacy Forum's Privacy Papers for Policymakers Award in 2017. Joshua's previous work spans accountable algorithms, cryptography, software security, formal methods, Bitcoin, and the technical aspects of cybersecurity policy. He also spent two years working on cryptography and internet security at the web performance and security company Cloudflare. Joshua holds a PhD in computer science from Princeton University, where he received the National Science Foundation Graduate Research Fellowship in 2011.

Joshua Kroll School of Information, University of California at Berkeley, USA

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Maria Maistro (http://www.dei.unipd.it/~maistro/) is a post-doctoral researcher in computer science at the University of Copenhagen, Denmark. She took her master degree in Mathematics at the University of Padua, in Italy, specializing her studies in probability and stochastic financial methods, operational research, and optimal control theory. Then she took her PhD in computer science with a thesis on the exploitation of user signals and stochastic models to improve information retrieval systems and evaluation. Her research interests deal with evaluation in information retrieval, especially in including users in the evaluation process, click log analysis and user modeling, and learning to rank. She was involved in the organization of CENTRE@CLEF 2018 and CENTRE@NTCIR-14 on the reproducibility of experiments in information retrieval.

Maria Maistro University of Copenhagen, Denmark and University of Padua, Italy

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Rishabh Mehrotra's personal site

Rishabh Mehrotra Spotify Research, London, UK (On final programme, but did not present)

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Bhaskar Mitra is a Principal Applied Scientist at Bing in the Microsoft Research Montreal lab. He joined Microsoft in 2006 and Bing—then called Live Search—in 2007. Previously, he has been part of several Microsoft labs in Hyderabad (India), Bellevue (USA), and Cambridge (UK). Over the years in Bing, he worked on several problems related to document ranking, entity ranking, query formulation, and evaluation. His interests include machine learning and information retrieval, and in particular the topic of neural information retrieval (IR). He co-organized multiple workshops and tutorials on neural IR, and also served as a guest editor for the special issue of the Information Retrieval Journal on the same subject. He is currently pursuing a part-time doctorate at University College London under the supervision of Dr. Emine Yilmaz and Dr. David Barber.

Bhaskar Mitra Microsoft and University College London, Canada

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Alejandro Moreo Fernández received a Master degree and a PhD in Computer Sciences and Information Technologies from the University of Granada in 2013. He is a researcher at Istituto di Scienza e Tecnologie dell 'Informazione, which is part of the National Research Council (CNR). His research interests include deep learning and representation learning, with particular focus on transfer learning for text classification.
Contact him at alejandro.moreo@isti.cnr.it

Alejandro Moreo Istituto di Scienza e Tecnologie dell'Informazione, Consiglio Nazionale delle Ricerche, Italy

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Douglas Oard is a Professor at the University of Maryland, College Park (USA), with joint appointments in the College of Information Studies (Maryland’s iSchool) and the University of Maryland Institute for Advanced Computer Studies (UMIACS). His research interests center around the use of emerging technologies to support information seeking by end users, including cross-language retrieval, speech retrieval, e-discovery in civil litigation, and protection of sensitive content during retrieval.
Additional information is available at http://terpconnect.umd.edu/~oard/.

Doug Oard University of Maryland, College Park, USA

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Fabrizio Sebastiani is a Senior Researcher at the Institute for the Science and Technologies of Information of the Italian National Council of Research; formerly he was an Associate Professor at the Department of Pure and Applied Mathematics of the University of Padova, Italy (2005/06) and a Principal Scientist at the Qatar Computing Research Institute (2014/16). He is a Senior Associate Editor for ACM Transactions on Information Systems, an Associate Editor for IEEE Transactions on Affective Computing, Online Social Networks and Media (Elsevier) and PeerJ Computer Science, and a member of the Editorial Boards of the Information Retrieval Journal (Springer) and Foundations and Trends in Information Retrieval (Now Publishers). Of the latter journal he is a former co-Editor-in-Chief and Founding Editor. He has been the General Chair of SIGIR 2016, a Program co-Chair of SIGIR 2008, and (from 2003 to 2007) the Vice-Chair of ACM SIGIR.
His research interests lie at the interface of information retrieval and machine learning, with particular emphasis on text classification and quantification, information extraction, sentiment analysis, and their applications to market research, medical text mining, and e-discovery.
A list of his publications is at https://goo.gl/nfxkFd>.

Fabrizio Sebastiani Istituto di Scienza e Tecnologie dell'Informazione, Consiglio Nazionale delle Ricerche, Italy

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Hussein Suleman is Head of Department and Associate Professor in Computer Science at the University of Cape Town. His research is situated within the Centre for ICT for Development (ICT4D) and the Digital Libraries Laboratory. Hussein's main research interests are in digital libraries, ICT4D, African language information retrieval, cultural heritage preservation, Internet technology and educational technology. He has in the past worked extensively on architecture and interoperability issues related to digital library systems, with a growing emphasis on the relationship between low resource conditions and such architectures. This has evolved into a focus on ICT for development (ICT4D) and its alignment with digital libraries and IR.
More information can be found at http://www.husseinsspace.com/

Hussein Suleman University of Cape Town, South Africa

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Dr. Grace Hui Yang is Associate Professor of Computer Science at Georgetown University. Dr. Yang leads the InfoSense (Information Retrieval and Sense-Making) Lab at Georgetown University, Washington D.C., U.S.A. Dr. Yang’s research interests include dynamic information retrieval, deep reinforcement learning, search engine evaluation, privacy-preserving information retrieval, internet of things, and information organization. Prior to this, she has worked on question answering, ontology construction, near-duplicate detection, multimedia information retrieval, and opinion and sentiment detection. Dr. Yang's research has been supported by Defense Advanced Research Projects Agency (DARPA) and National Science Foundation (NSF). Dr. Yang is a recipient of NSF’s Faculty Early Career Development Program (CAREER) Award. Dr. Yang co-chaired SIGIR 2013 and 2014 Doctoral Consortiums, SIGIR 2017 Workshop, WSDM 2017 Workshop, ICTIR 2017 Workshop, CIKM 2015 Tutorial, ICTIR 2018 Short Paper and SIGIR 2018 Demonstration Paper Program Committees. Dr. Yang served on the editorial board of Information Retrieval Journal from 2014 to 2017. She has served as an area chair/senior program committee member for SIGIR 2014-present, WSDM 2018-present, ECIR 2017- present and for ACL 2016. Dr. Yang also co-organized the Text Retrieval Conference (TREC) Dynamic Domain Track from 2015 to 2017 and led the effort for SIGIR privacy-preserving information retrieval workshops from 2014 to 2016. Dr. Yang obtained her Ph.D. from Carnegie Mellon University in 2011.

Grace Yang Department of Computer Science, Georgetown University, USA

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Emine Yilmaz is a Professor at University College London, Department of Computer Science. She also works as a research consultant for Microsoft. She is the recipient of Bloomberg Data Science Research Award in 2018, the Karen Sparck Jones 2015 Award and the Google Faculty Research Award in 2014. Emine's current research interests include information retrieval, data mining and applications of machine learning. She has published research papers extensively at major venues such as ACM SIGIR, CIKM and WSDM, gave several tutorials as part of top conferences, and organized various workshops. Her research has been widely adopted by the information retrieval community and the sampling methods she has designed for efficient retrieval evaluation have been commonly used and made publicly available by the Text Retrieval Conference (TREC). She has served in various roles including PC Chair for the ACM SIGIR 2018 and ACM ICTIR 2017 Conferences, Practice and Experience Chair for ACM WSDM 2017, and as the Doctoral Consortium Chair for ECIR 2017. She is an elected member of the executive committee of ACM SIGIR and serves as a co-editor-in-chief for the Information Retrieval Journal.

Emine Yilmaz University College London and Microsoft, UK

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Guido Zuccon is a Senior Lecturer at University of Queensland and an ARC DECRA fellow and a Google Faculty Award recipient. He received a Ph.D. in Computing Science from the University of Glasgow in 2012. Before joining the University of Queensland, he has a postdoctoral Research Fellow at CSIRO, and Lecturer and then Senior Lecturer at the Queensland University of Technology. His research interests include formal models of search and evaluation methods, in particular applied to health search.

Guido Zuccon University of Queensland

Final Programme

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Note: Due to unforeseen circumstances, Rishabh Mehrotra did not present. Instead, lectures on the Friday were given by Guido Zuccon (Health Search) and Benjamin Carterette (Music Recommendation); and the Lab session was a continuation of sessions from previous days.

Slides and supporting material

Click here for access to slides and supporting material

Registration is closed.

LOCATION

 
 

Main Venue

Upper Campus
University of Cape Town
Cape Town, South Africa
Directions to get to UCT Upper Campus

 
 

Lecture Venue

Hlanganani Junction
Level 5
Chancellor Oppenheimer Library (Enter through Otto Beit Building)
UCT Upper Campus Map

 
 

Lab Venue

Computer Science Senior Lab
Level 2A
Computer Science Building
UCT Upper Campus Map