I am assistant professor at the department of Computer Science at UNH with a focus on text-based machine learning and information retrieval as well as data science on watersheds.
Previously I was a Post-doctoral Research Scientist at the Data and Web Science Group of Mannheim University, working with Prof. Simone Paolo Ponzetto. Before that I was a Research Scientist at the Center for Intelligent Information Retrieval (CIIR) working with Bruce Croft at University of Massachusetts. Before that I did a post-doc with Andrew McCallum. I graduated from Max Planck Insititute for Informatics in Saarbruecken, Germany in January 2011.
In Fall 2020 I will be teaching a new course: Machine Learning for Sequences and Text. The topic is on machine learning models that learn from data with sequential nature (think: text, genomes etc). Covering Conditional Random Fields as well as neural networks Bi-LSTMs and transformers. The course is designed to be orthogonal for Marek Petrik's "Machine Learning" class. (Which is NOT a prereq) The only overlap is logistic regression, which the new course will cover at a different level. The course is temporarily listed as CS780 (03) and CS880 (03). It will serve as an alternative prereq for the implementation-intensive data science seminar CS953 in Spring 2021. Catalog entry for CS780 (03): https://courses.unh.edu/class/202010/16907 The course catalog lists a recitation (F), which is a mistake: There is no separate recitation in this course.
See teaching page for more information about my courses offered at UNH
Computational Social Science Summer School Lecture 2018 on “What is in my documents?”.
Conference tutorial on Utilizing Knowledge Graphs for Text-centric Retrieval at ICTIR 2016, WSDM 2017, SIGIR 2017. (Literature Overview).
I was giving a keynote at SPIRE in 2020 on How to Automatically Create Relevant Articles.
Since 2020, I serve on the Steering Committe of the Northeast Big Data Innovation Hub.
Since 2020, I am a member of the NIST TAC-KBP Scientific Advisory Board
Since 2019, I am Associate Editor for the ACM Transactions on Information Systems (TOIS)
From 2016 to 2019 I was the ACM SIGIR Student Affairs Chair.
I was giving a keynote at ECIR in 2017 on Retrieving Knowledge from the Webs.
I am coordinating the TREC Complex Answer Retrieval track at the Text REtrieval Conference.
I am organizing the KG4IR workshop Series at SIGIR 2017 and 2018 and a presenter of the conference tutorial for Utilizing Knowledge Graphs for Text-centric Retrieval. I am guest-editing the KG4IR Special Issue of the Information Retrieval Journal.
I received a best paper award at JCDL 2018 for our work on Entity Aspect Linking.
Together with Adam Wymore, I am a co-PI on the UNH CoRE Pilot Research Partnership on “Watershed Informatics: Integrating Big Data to Understand Watersheds in a Changing World”.
I am reviewing for different venues ranging from information retrieval (SIGIR, CIKM, ICTIR), natural language processing (ACL, ACL, KDD, EMNLP, NAACL), machine learning (ICML, NIPS, UAI), and data mining (KDD, CIKM).
I am interested in Text Retrieval, Extraction, Machine Learning, and Analysis (TREMA).
I also cover research areas Biomedical NLP/IR, Question Answering and Answer-Passage Retrieval, Topic Models for Graph Structured Data
My research is placed in the intersection between Information Retrieval and Information Extraction, where I am striving towards a deep integration rather than a pipelined combination. My tool of choice are graphical models, often generative probabilistic models. This pattern underlies all the different facets of my research, where some are detailed in the following:
From 2017-2019, I coordinated the Complex Answer Retrieval track at the Text Retrieval Conference (TREC). It is an international evaluation track on how can retrieve the most best passages and and entities on topics about popular science and society. For more information about the data, task and evaluation, please see the official TREC Complex Answer Retrieval site.
Track overview papers:
L.Dietz, M.Verma, F.Radlinski, N.Craswell (2017). TREC Complex Answer Retrieval Overview. In TREC. year 1
L.Dietz, B.Gamari, J.Dalton, N.Craswell (2018), TREC Complex Answer Retrieval Overview. In TREC. year 2
L.Dietz, B.Gamari, J.Foley (2019), TREC CAR Y3: Complex Answer Retrieval Overview. In TREC. year 3
Together with my students I am working on methods to automatically, and in a query-driven manner, retrieve materials from the Web and compose Wikipedia-like articles. Especially for information needs, where the user has very little prior expert knowledge about, the web search paradigm of 10 blueToe hyperlinks is not sufficient. Instead we envision to provide a synthesis of the Web materials that strives to mimick the comprehensiveness of Wikipedia articles. We limit ourselves to a content-only setting where query-log, click, or session information is not available. Consequently, we aim to maximize the utility of information retrieval models in combination with methods from natural language processing. A particular emphasis is to utilize information from structured knowledge resources such as Wikipedia, Freebase, or DBpedia together with text-based reasoning on general document and Web corpora.
An early feasibility study was presented at AKBC 2014, a later demo presented at the ESAIR workshop at CIKM 2015 (demo). The method paper for the demo is under submission (information available on request).
Closely related work on reranking entities for web queries was presented at CIKM 2015 (appendix) as well as work on using relation extraction in information retrieval presented at [ECIR 2016 (supervised relations)][relevant-relation-ecir2016 and SIGIR 2017 (OpenIE)
The project was awarded with an Amazon AWS in education research grant and a stipdend by the Eliteprogramm for Postdoktorandinnen und Postdoktoranden of the Baden-Württemberg Stiftung.
Together with Jeff Dalton, I am studying how to effectively leverage Knowledge Bases such as Wikipedia and Freebase in ad hoc document retrieval. In a first step, documents and queries are enriched with links to the knowledge base. During the retrieval stage, these links can be used as an additional vocabulary as well as in feedback-based query expansions. For instance entities that are linked from the query are expected to also be linked in relevant documents. However, we may compensate for errors in the entity linking stage by also considering terms from the entities’ article text, as well as name variants. An additional option are feedback methods, where documents retrieved in a preliminary pass are inspected for entity links to update the belief on which entities are relevant for the query. We also use the feedback documents to build an entity-context model to understand how each entity is related to the query.
This work was presented at SIGIR 2014.
With Federico Nanni, I am working on building document collections for events. We found that entity links are too unspecific, as the same entity can be mentioned in different contexts (we call them entity aspects). In our JCDL 18 paper on entity aspect linking, we demonstrated that such aspects can be harvested section headings of the entity’s Wikipedia article. To post-process entity links, we propose a method for entity-aspect linking to refine the entity link with aspect information. When applied to retrieval problems, aspect linking improved the accuracy of rankings and classifications. This work received a best paper award at JCDL 2018.
Entity linking refers to a problem setting where the algorithm is given a string in a document and has to predict which Wikipedia entity it refers to. Our solution involved a retrieval model that incorporates the string itself, and surrounding entity mentions to predict entity candidates as a ranking. We show that this model is an approximation to state-of-the-art models which optimize a joint assignment of mentions to entities. This solution can be further refined with supervised re-rankers but also provides reasonable performance “out-of-the-box”.
The code is available as part of the KB-Bridge project.
In order to monitor a stream of news and social documents for stories involving one or more target entities. We tap on symmetric relationships in our Entity Linking approach both retrieve relevant documents (KB to text) and entity link them (text to KB) with the same underlying model. This requires to integrate low-level NLP algorithms into a retrieval framework.
We participate with this solution in TREC KBA 2012 and TREC KBA 2013. A paper on time-aware IR-based evaluation is published at [TAIA 2013] (streameval/index.html). The time-aware evaluation methods are used to analyze our KBA 2013 results with results presented at in our 2013 talk at TREC.
I further work on “senti-PRF”, a pseudo relevance feedback approach to optimize retrieval for opinionated questions. Published at CIKM 2013.
I am still interested in unsupervised algorithms for identifying shared aspects and quantifying influence in social networks. Work on symmetric networks is published at ICWSM 2012 ( Code & Supplement ) and asymmetric networks at ICML 2007 (talk – Supplement).
My PhD thesis was mainly focused on topic models and other generative models for data with link structure.
Pooja Oza. Pooja is working on integrated entity and text ranking. She received a CEPS fellowship.
Sepideh Koohfar. Sepideh is working on data science for storm event analysis in watersheds.
Jordan Ramsdell. Jordan is working on joint entity and text retrieval.
Shubham Chatterjee. Shubham is working on Entity-support passage retrieval.
Sumanta Kashyapi. Sumanta is working on topic extraction for complex answer retrieval.
Matt Magnusson. Matt is working on word embeddings for entity recognition and aspect linking.
Robert Litschko (co-advised). Robert is working on neural methods for cross-lingual retrieval.
… your name here? …
Nithin Sivakumar (Masters Project): Document classification approaches to Complex Answer Retrieval. Graduated 2019.
Jordan Ramsdell (Masters Project): Sequential Dependence Models for Document and Entity Retrieval. Fullfilled 2018, continued into Ph.D.
Amina Kadry (Masters Thesis): Using ClausIE, an unsupervised relation extraction to find good explanation of entity-relevance. - Graduated 2017.
Thomas Stach (Masters Thesis): Wikipedia Reconstruction - How to compose Wikipedia articles out of text passages? - Graduated 2016.
Team project (multiple students): Supporting large-scale meeting facilitation - automated clustering of participant-contributed ideas. Finished 2016.
James Lemieux (Senior Thesis): Optical Music Recognition. Graduated 2019.
Capstone Project (Benjamin Gildersleeve, Haiyao Ni, Andrew Porter): Data Science for Storm Events in Watersheds. Co-sponsored with Adam Wymore from the Department of Natural Resources and the Environment. Fall 2019 - Spring 2020.
Madinson Clark-Turner. High Level Robot Learning using the Temporal Features of Human Demonstrated Sequential Tasks. University of New Hampshire. Ongoing
Sebastian Arnold. Robust Entity and Aspect Extraction for Enterprise Applications. University of Fribourg. Ongoing.
Bahram Behzadian. Feature Selection by Singular Value Decomposition for Reinforcement Learning. University of New Hampshire. Ongoing.
Reazul Hasan Russel. Probabilistic Reinforcement Learning. University of New Hampshire. Ongoing.
Federico Nanni. Federico was working on consolidation, tracking, and summarization of historical events in text.
Bence Cserna, University of New Hampshire. Graduated 2019.
Lydia Weiland. Lydia is working on understanding the message of iconic images we often find in news articles. (Mannheim University, Thesis co-advisor). Graduated 2018.
Kai Hui, Max-Planck Institute for Computer Science, 2017, soon at SAP Berlin. (Committee Member)
Shiri Dori-Hacohen, University of Massachusetts, 2017. Startup founder.
Michael Schuhmacher, Mannheim University, 2016. Now at Data Scientist at Springer Nature, soon at BASF.
Jeffrey Dalton, University of Massachusetts, Ph.D. 2014, now professor at University of Glasgow.
The vision of HIPstIR is that early stage information retrieval (IR) researchers get togetherto develop a future for non-mainstream ideas and research agendas inIR. Important priorresearch can be discussed in the form of reading groups. A future vision of what IR can (orshould) be—and how to get there—must be developed. It is like SWIRL (Moffat et al., 2005,Allan et al., 2012, Culpepper et al., 2018) in spirit but focusing ontopics that may otherwisebe considered “niche”, “alternative”, “indie”, or “left field”. An explicit goal of this workshop isto foment collaboration and cross-group fertilization. The hopeis that participation will giverise to conference workshop topics and joint paper projects. Primaryfocus is on early stageresearchers that are anywhere between defending their PhD within one year to one year intobeing a tenured professor or a senior scientist, but few senior people may also be invited
We hope more folks will branch off and organize HIPstIR’s all over the place. HIPstIR is public domain / CC0.
Laura Dietz, Ben Gamari, Jeff Dalton, Manisha Verma, Prasenjit Mitra, Nick Craswell. TREC Complex Answer Retrieval at the Text REtrieval Conference. 2016–2018. - www - dataset - Mailinglist - TREC homepage
TREC CAR concluded in 2019. Thanks to all the participants! – Dear Reviewers: Please keep on mind that TREC CAR offered multiple tasks whose numbers are not comparable.
Laura Dietz. How to Automatically Create Relevant Articles. Keynote at SPIRE 2020: 27th International Symposium on String Processing and Information Retrieval. 2020. Slides
Laura Dietz, Chenyan Xiong, and Edgar Meij. Proceedings of the First Workshop on Knowledge Graphs and Semantics for Text Retrieval and Analysis (KG4IR 2017) co-located with the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017), Shinjuku, Tokyo, Japan, August 11, 2017. CEUR Workshop Proceedings 1883, CEUR-WS.org 2017 - proceedings - contents - www - Mailinglist
Laura Dietz, Alexander Kotov, and Edgar Meij. Tutorial on Utilizing Knowledge Graphs in Text-centric Information Retrieval. In Proceedings of the Conference on Web Search and Data Mining (WSDM). 2017. Slides and Bibliography - Mailinglist
Laura Dietz, Alexander Kotov, and Edgar Meij. Tutorial on Utilizing Knowledge Bases in Text-centric Information Retrieval. Proceedings of the 2016 ACM on International Conference on the Theory of Information Retrieval. 5-5. 2016. Slides and Bibliography - Mailinglist
Kling, Christoph Carl; Posch, Lisa; Bleier, Arnim; Dietz, Laura. Topic model tutorial: A basic introduction on latent dirichlet allocation and extensions for web scientists. Proceedings of the 8th ACM Conference on Web Science. 10-10. 2016. paper - slides, animations and ressources
I retired from Women in IR in 2018 and passed on the batton to Suzan Verberne and Nazli Goharian.
Laura Dietz and Sudeshna. Women in IR Session. SIGIR 2018. – I retired from my organizational role. I highly appreciate Nazli Goharian and Suzan Verberne for taking over.
Laura Dietz, Elinor Brondwine, Shiri Dori-Hacohen, and Ellen Voorhees. Women in IR. In ACM SIGIR Forum, vol. 50, no. 2, pp. 15-17. ACM, 2017. - article
Shiri Dori-Hacohen, Myungha Yang, and Laura Dietz. Women in IR Session. SIGIR 2016. Pisa, Italy. - annoucement
Shiri Dori-Hacohen. Women in IR - Women’s lunch. ICTIR 2015. Northampton, MA, USA
Women in IR - inaugural meeting. SIGIR 2015. Santiago de Chile, Chile.
L.Dietz. Retrieve-and-generate: How to Automatically Create Relevant Articles. CIIR Talk Series. University of Massachusetts. February 2021. – Slides (open in your web browser)
L. Dietz. ENT-Rank: Finding Relevant Entities through Text and Knowledge Graphs. Invited talk at LTI Colloquium Carnegie Mellon University, September 11, 2020. – Slides (open in your web browser and use cursor keys to navigate)
L. Dietz. ENT-Rank: Finding Relevant Entities through Text and Knowledge Graphs. Invited talk at NEC Heidelberg, July 2, 2020. – Slides (open in your web browser and use cursor keys to navigate)
L.Dietz. Retrieving Complex Answers through Knowledge Graphs and Text. CLIP Seminar. University of Maryland. March 2018. Slides (open in your browser)
L.Dietz. Retrieving Complex Answers through Knowledge Graphs and Text. Georgetown University. August 2017. Slides (open in your browser)
L. Dietz. Retrieving Knowledge from the Web. Data Science Seminar at UNH. 2017. Slides (open in your browser)
Dietz, Laura. Query-specific Wikipedia Construction. Invited talk at ILPS at Amsterdam University, The Netherlands. November 5, 2015.
Dietz, Laura. Query-specific Wikipedia Construction and Network Topic-Models. Invited talk at GESIS Leibnitz-Institut fuer Sozialwissenschaften (Computational Social Science Seminar), Cologne, Germany. September 17, 2015.
Dietz, Laura. Network Topic Models. Invited talk at Heidelberg University (Stat NLP Colloquium). May 22, 2015.
J. Ramsdell, L.Dietz. A Large Test Collection for Entity Aspect Linking. CIKM 2020. Paper (in press) - Dataset
B. Gamari, L. Dietz. “Alligator Collector: A Latency-Optimized Garbage Collector for Functional Programming Languages”. 2020 ACM SIGPLAN International Symposium on Memory Management (ISMM 2020), June 16, 2020, London, UK. 2020. pdf – appendix
S. Chatterjee, L.Dietz. Why does this Entity matter?: Support Passage Retrieval for Entity Retrieval. Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval. ICTIR 2019. paper – appendix
J. Dalton, S. Naseri, L. Dietz, J. Allan. Local and Global Query Expansion for Hierarchical Complex Topics. European Conference on Information Retrieval. 2018.
F. Nanni, B. Mitra, M. Magnusson, L. Dietz. Benchmark for Complex Answer Retrieval. In International Conference on Theory in Information Retrieval (ICTIR). 2017. – preprint available on ArXiv.
A. Kadry, L. Dietz. Open Relation Extraction for Support Passage Retrieval: Merit and Open Issues. In Proceedings of the 40th Annual International ACM SIGIR conference (SIGIR). 2017. Paper - Poster - Online Appendix
F. Nanni, N. Marinov, S.P. Ponzetto, L. Dietz. Building Entity-Centric Event Collections For Supporting Research in Political and Social History. In Proceedings of Digital Humanities 2017 - Book of Abstracts. 2017. Paper
F. Nanni, Y. Zhao, S.P. Ponzetto, L. Dietz. Enhancing Domain-Specific Entity Linking in DH. In Proceedings of Digital Humanities 2017 - Book of Abstracts. 2017. Paper
F. Nanni, S. Ponzetto, L. Dietz. Building Entity-Centric Event Collections. In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). 2017.
F. Nanni, N. Marinov, S. Ponzetto, L. Dietz. Building Entity-Centric Event Collections for Supporting Research in Political and Social History. In Digital Humanities (DH). 2017.
F. Nanni, Y. Zhao, S. Ponzetto, L. Dietz. Enhancing Domain-Specific Entity Linking in DH. In Digital Humanities (DH). 2017.
Weiland, Lydia; Hulpus, Ioana; Ponzetto, Simone Paolo; Dietz, Laura. Using Object Detection, NLP, and Knowledge Bases to Understand the Message of Images. Proceedings of the International Conference on Multimedia Modeling (MMM), 405-418, 2017.
Weiland, Lydia; Hulpus, Ioana; Ponzetto, Simone Paolo; Dietz, Laura. Understanding the message of images with knowledge base traversals. Proceedings of the 2016 ACM on International Conference on the Theory of Information Retrieval. 199-208. 2016.
Nanni, Federico; Dietz, Laura; Faralli, Stefano; Glavaš, Goran; Ponzetto, Simone Paolo. Capturing interdisciplinarity in academic abstracts. D-lib magazine, 22, 9/10, Corporation for National Research Initiatives. 2016.
Nanni, Federico; Dietz, Laura; Faralli, Stefano; Glavas, Goran, Ponzetto, Simone Paolo. Capturing Interdisciplinarity in Academic Abstracts. Workshop on Mining Scientific Publications at JCDL, 2016.
Schuhmacher, Michael; Roth, Benjamin; Ponzetto, Simone Paolo; Dietz, Laura. Finding Relevant Relations in Relevant Documents. In Proceedings of European Conference on Information Retrieval (ECIR), 2016. .pdf
Dietz, Laura; Schuhmacher, Michael. An Interface Sketch for Queripidia: Query-driven Knowledge Portfolios from the Web. Proceedings of the Workshop for Exploiting Semantic Annotations in IR (ESAIR) at CIKM, 2015. .pdf – demo
Schuhmacher, Michael; Dietz, Laura; Ponzetto, Simone Paolo. Ranking Entities for Web Queries Through Text and Knowledge. Proceedings of ACM International Conference on Information and Knowledge Management (CIKM), 2015. .pdf – appendix
Dietz, Laura; Schuhmacher, Michael; Ponzetto, Simone Paolo. Queripidia: Query-specific Wikipedia Construction. In Proceedings fo the Automatic Knowledge Base Construction Workshop (AKBC) at NIPS 2014. .pdf
Dietz, Laura. Entity Linking wth Document Retrieval and Vice Versa. Invited talk at University of Illinois, Urbana-Chamaign, USA. October 22, 2014.
Dalton, Jeffrey; Dietz, Laura; Allan, James: Entity Query Feature Expansion using Knowledge Base Links. In Proceedings of the 37th Annual International ACM SIGIR conference, Gold Coast, Queensland, Australia, July 6-11, 2014. .pdf – appendix
Dalton, Jeffrey; Dietz, Laura: UMass CIIR at TAC KBP 2013 Entity Linking: Query Expansion using Urban Dictionary. Text Analysis Conference (TAC), Gaithersburg, MD, USA, November 19-20, 2013. .pdf
Dietz, Laura; Dalton, Jeffrey: UMass at TREC 2013 Knowledge Base Acceleration Track: Bi-directional Entity Linking and Time-aware Evaluation. Text Retrieval Conference (TREC), Gaithersburg, MD, USA, November 20-22, 2013. .pdf
Dietz, Laura and Dalton, Jeffrey: Query-specific Knowledge Sketches: A Joint Retrieval Model for Text, Entities, and Relations. CIIR Technical Report, 2013.
Dietz, Laura; Wang, Ziqi; Huston, Samuel; Croft, W. Bruce: Retrieving Opinions from Discussion Forums. Proceedings of ACM International Conference on Information and Knowledge Management (CIKM), 2013. .pdf
Dietz, Laura; Dalton, Jeffrey; Balog, Krisztian: Time-aware Evaluation of Cumulative Citation Recommendation Systems. Proceedings of SIGIR 2013 Workshop on Time-aware Information Access, TAIA, 2013 .pdf. code & supplement
Dalton, Jeffrey; Dietz, Laura: Constructing Query-Specific Knowledge Bases. Proceedings on the CIKM Workshop on Automated Knowledge Base Construction, 2013. .pdf.
Dalton, Jeffrey; Dietz, Laura: A Neighborhood Relevance Model for Entity Linking. Proceedings of the 10th International Conference in the RIAO series (OAIR), 2013. .pdf
Dietz, Laura: A Neighborhood-Relevance Model for Entity Linking. Mt Holyoke College, South Hadley, MA, USA, 20th of February, 2013. talk view in Web browser!
Dietz, Laura: A Neighborhood-Relevance Modelfor Entity Linking. Machine Learning and Friends Lunch Talk, University of Massachusetts, MA, USA, 14th of February, 2013. talk view in Web browser!
Dalton, Jeffrey; Dietz, Laura: Bi-directional Linkability From Wikipedia to Documents and Back Again: UMass at TREC 2012 Knowledge Base Acceleration Track. In: Proceedings of Text REtrieval Conference (TREC), 2012. .pdf
Dietz, Laura; Gamari, Benjamin; Guiver, John; Snelson, Edward; Herbrich, Ralf: De-Layering Social Networks with Shared Tastes of Friendships. In: Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media (ICWSM), 2012 .pdf – Code & Supplement
Konietzny, Sebastian; Dietz, Laura; McHardy, Alice: Inferring functional modules of protein families with probabilistic topic models. In: BMC Bioinformatics, vol. 12, no. 1, 141+, 2011 .html
Dietz, Laura: Exploiting Graph-Structured Data in Generative Probabilistic Models. PhD Thesis, January 2011. Max Planck Institute for Informatics and Saarland University, 2011 .pdf
Dietz, Laura: Inferring Shared Interests from Social Networks“. In: NIPS Workshop on Computational Social Science and the Wisdom of Crowd : Text and Beyond, 2010 .pdf
Dietz, Laura: Directed Factor Graph Notation for Generative Models. Technical Report, 2010 .pdf – TIKZ macros and algorithms module: .zip - Thanks to Jaakko Luttinen for creating an improved version at github.com/jluttine/tikz-bayesnet !
Dietz, Laura: Modeling Shared Tastes in Online Communities. In: NIPS Workshop on Applications for Topic Models: Text and Beyond, 2009 .pdf
Dietz, Laura ; Dallmeier, Valentin ; Zeller, Andreas ; Scheffer, Tobias: Localizing Bugs in Program Executions with Graphical Models. In: Advances in Neural Information Processing Systems, 2009 .pdf – supplement – project
Dietz, Laura; Bickel, Steffen;Scheffer Tobias : Unsupervised Prediction of Citation Influences. In: Proceedings of the 24th International Conference on Machine Learning. Corvallis, Oregon, USA, June 2007 .pdf – Watch the Talk – project
Since August 2016: Assistant Professor (tenure-track) in the Computer Science Department at University of New Hampshire. Head of the TREMA lab.
March 2015 - August 2016: Post-doctoral Research Scientist at Data and Web Science Group (DWS), Mannheim University (DWS, Simone Paolo Ponzetto)
August 2012 - March 2015: Research Scientist at Center for Intelligent Information Retrieval (CIIR), University of Massachusetts (CIIR, Bruce Croft)
October 2010 - August 2012: Post-doctoral researcher at University of Massachusetts (IESL, Andrew McCallum).
January 2008 - January 2011: PhD Student at Max-Planck-Institute for Informatics (Databases and Information Systems, Prof Gerhard Weikum), Saarbruecken
January 2007 - December 2008: PhD Student at Max-Planck-Institute for Informatics (Machine Learning, Prof. Tobias Scheffer), Saarbruecken
October 2006 - December 2006: PhD Scholarship at Knowledge Management Group (Prof. Tobias Scheffer), Humboldt University, Berlin
December 2002 - September 2006: Research Associate at Concert Division and I-Info Division, Fraunhofer Institute for Publication and Information Systems (IPSI), Darmstadt
Strepsirrhini, a modular composable toolkit in scala for retrieval, reranking, and expansion with and without entity annotations, Laura Dietz, 2014.
Riffle, open hardware and software for a water-quality sensor with data analysis software. Benjamin Gamari, Don Blair, Laura Dietz, 2014.
Stream-Eval, an evaluation framework for time-aware evaluation of cumulative citation recommendation systems. Laura Dietz, Jeffrey Dalton, Krizstian Balog, 2013.
KB-Bridge, a framework for entity linking. Jeffrey Dalton, Laura Dietz, 2013.
Hphoton and photon-tools - overview - walkthrough Open source hardware and software for single-molecule fluorescence analysis. Benjamin Gamari, Laura Dietz, Lori Goldner, 2013. (Received OSSI Award 2013 from UMass ICB3)
Bayes-Stack, a framework for inference on probabilistic graphical models. Laura Dietz, Benjamin Gamari, 2012.
Tikz-Bayesnet, open source latex add-on / TIKZ package for graphical model diagrams. Laura Dietz, 2010. (Forked and continued by Jaakko Luttinen, 2012).