Research:

• Autonomous Aircraft Towing Vehicles: towing aircraft all the way from the runways to their gates (and vice versa), thereby reducing pollution, energy consumption, congestion, and human workload

Publications:

• Planning, Scheduling and Monitoring for Airport Surface Operations. R. Morris, C. Pasareanu, K. Luckow, W. Malik, H. Ma, S. Kumar and S. Koenig. AAAI-16 Workshop on Planning for Hybrid Systems 2016.

Research:

• Computational Sustainability: key contributions to AI techniques for applications in sustainability, spanning habitat conservation, land cover mapping, water & energy, urban infrastructure planning, disasters and climate change resilience

Research:

• Paleoclimate: Aims to understand changes in the climate system using a data-driven approach. 
• Metadata standards: Development of metadata standards for paleoclimate data. Participated in various international working groups focused on various aspects of the climate system at different timescales. 
• Scientific software/workflow: Develop various toolboxes geared towards the analysis of paleoclimate data (mostly time series analysis as above and domain-specific proxy system models).

Publications:

• PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data, Paleoceanography and Paleoclimatology, 2019

• The role of uncertainty in estimating lead/lag relationships in marine sedimentary archives: a case study from the tropical Pacific, Paleoceanography, 2019

• A global database of paleotemperature records. Scientific Data, 2020

Software:

• GeochronR and Pyleoclim: Scientific software for time series analysis, in particular paleoclimate time series (in R and Python).

• autoTS: A system for automated time series analysis. 

Research:

• Hydrology and groundwater model metadata: We are developing metadata ontologies for software and models, so models can be automatically set up and composed.
  
• Model integration: We are using a range of AI techniques to help scientists integrate models from different disciplines.

Publications:

• Artificial Intelligence for Modeling Complex Systems: Taming the Complexity of Expert Models to Improve Decision Making
• Evaluation of the OntoSoft Ontology for Describing Legacy Hydrologic Modeling Software

Software:

• MINT model integration framework
  
• The Software Description (SD) and the Software Description for Models (SDM) ontologies for model metadata

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Publications:

• Having a Bad Day? Detecting the Impact of Atypical Life Events Using Wearable Sensors. K Burghardt, N Tavabi, E Ferrara, S Narayanan, K Lerman
• Affect Estimation with Wearable Sensors. S Yan, H Hosseinmardi, HT Kao, S Narayanan, K Lerman, E Ferrara
• Estimating individualized daily self-reported affect with wearable sensors. S Yan, H Hosseinmardi, HT Kao, S Narayanan, K Lerman, E Ferrara
• Discovering latent psychological structures from self-report assessments of hospital workers. HT Kao, H Hosseinmardi, S Yan, M Hasan, S Narayanan, K Lerman, E Ferrara.
• TILES-2018, a longitudinal physiologic and behavioral data set of hospital workers. Karel Mundnich, Brandon M Booth, Michelle l'Hommedieu, Tiantian Feng, Benjamin Girault, Justin L'Hommedieu, Mackenzie Wildman, Sophia Skaaden, Amrutha Nadarajan, Jennifer L Villatte, Tiago H Falk, Kristina Lerman, Emilio Ferrara, Shrikanth Narayanan
• Multimodal Human and Environmental Sensing for Longitudinal Behavioral Studies in Naturalistic Settings: Framework for Sensor Selection, Deployment, and Management. Brandon M Booth, Karel Mundnich, Tiantian Feng, Amrutha Nadarajan, Tiago H Falk, Jennifer L Villatte, Emilio Ferrara, Shrikanth Narayanan
• Lessons learned: Recommendations for implementing a longitudinal study using wearable and environmental sensors in a health care organization. Michelle L'Hommedieu, Justin L'Hommedieu, Cynthia Begay, Alison Schenone, Lida Dimitropoulou, Gayla Margolin, Tiago Falk, Emilio Ferrara, Kristina Lerman, Shrikanth Narayanan

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Research:

• • Domain-specific search engines for helping both casual users and subject matter experts build customized knowledge graph-powered search engines for their domain-specific needs over complex data 

• Human-in-the-loop systems that use open-source technology with an intent to support both civilian and non-civilian operations including fighting child sex trafficking and supporting humanitarian relief operations during disasters

Publications:

• Kejriwal, M., Szekely, P., & Knoblock, C. (2018). Investigative knowledge discovery for combating illicit activities. IEEE Intelligent Systems.

• Kejriwal, M., & Gu, Y. (2020). Network-theoretic modeling of complex activity using UK online sex advertisements. Applied Network Science, 5(1), 1-23.

• Kejriwal, M., & Zhou, P. (2020). On detecting urgency in short crisis messages using minimal supervision and transfer learning. Social Network Analysis and Mining, 10(1), 1-12.

Software:

• DIG, Domain-specific Insight Graphs (nominated for Best Demo: AAAI, 2018)
• THOR, Text-enabled Humanitarian Operations in Real-time (feat. in DARPA’s 60th anniversary)
• Twitter Urgency Detector/SAVIZ, for visualizing and distinguishing urgent social media messages from non-urgent messages during arbitrary disasters (earthquakes, avalanches, floods…), to effectively assist users and first responders 

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Research:

• <add> Polarization: Tracking opinions on the global scale using social media data.

Publications:

• Political Polarization Drives Online Conversations About COVID‐19 in the United States. J Jiang, E Chen, K Lerman, E Ferrara
• Linguistic cues to deception: Identifying political trolls on social media. A Addawood, A Badawy, K Lerman, E Ferrara
• Characterizing the 2016 Russian IRA Influence Campaign. A Badawy, A Addawood, K Lerman, E Ferrara
• Who Falls for Online Political Manipulation? A Badawy, K Lerman, E Ferrara
• Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set. E Chen, K Lerman, E Ferrara
• Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign. A Badawy, E Ferrara, K Lerman
• Ad delivery algorithms: The Hidden Arbiters of Political Messaging. Muhammad Ali, Piotr Sapiezynski, Aleksandra Korolova, Alan Mislove, Aaron Rieke. 
• Facebook's Advertising Platform: New Attack Vectors and the Need for Interventions. Irfan Faizullabhoy, Aleksandra Korolova

Software:

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TBD _ science of science (Kristina), sci lit (Wael, Aram)

Research:

• Automated hypothesis-driven science that includes reasoning about scientific questions as graphs, matched with lines of inquiry that map them to data queries and analytic workflows, and with meta-workflows that combine analytic results. Used in cancer multi-omics and neuroscience.
• Provenance and Scientific Workflows: Using the W3C provenance model to capture semantic workflow executions

Publications:

• • Towards Continuous Scientific Data Analysis and Hypothesis Evolution, AAAI 2017.

• Quantifying reproducibility in computational biology: the case of the tuberculosis drugome. 

Software:

• DISK, an automated scientific discovery and data analysis system

Research:

• Scientific integrity analysis and software — We are developing algorithms for evaluating the integrity of scientific publications including figure and plot manipulation and figure repurposing. Further, he successfully developed the world’s first software system for automated scientific integrity including figure provenance and manipulation detection.
• Scientific paper of the future — We are developing best practices for reproducible research, open science, and digital scholarship for scientific publications, including AI publications.

Publications:

• On Reproducible AI: Towards Reproducible Research, Open Science, and Digital Scholarship in AI Publications.
• Towards the Geoscience Paper of the Future: Best Practices for Documenting and Sharing Research from Data to Software to Provenance

Software, Data, and Other Resources:

• Scientific Paper of the Future: training materials
  

Research:

• Virtual Data Integration/Efficient Query Rewriting: SIMS, BIRN/SchizConnect mediators. Efficient query rewriting (translating from domain to source-level queries using logical schema mapping): GQR algorithm (rewrite over 10K mappings in < 1 sec)

• Learning Formal Schema Mappings: from semantic type alignments (Karma)

• Semantic Similarity: Mapping phenotypic variables in biomedical data dictionaries (PhenoExplorer) and neural entity linkage/ normalization (NSEEN).

Publications:

• Wojcik, G.L., et al. Genetic analyses of diverse populations improves discovery for complex traits. Nature 570, 514–518 (2019). https://doi.org/10.1038/s41586-019-1310-4
• Parundekar R., Knoblock C.A., Ambite J.L. (2010) Linking and Building Ontologies of Linked Data. ISWC 2010. Best Research Paper Award. https://doi.org/10.1007/978-3-642-17746-0_38
• Konstantinidis, G. Ambite, J.L. 2011. Scalable query rewriting: a graph-based approach. SIGMOD  2011. https://doi.org/10.1145/1989323.1989335 

Software:

• schizconnect.org: virtual data integration for neuroimaging

• bigdatau.org: BD2K Training Coordinating Center, Educational Resource Discovery Index

• iLASH: Fast identification of shared genetic segments (Identity-by-Descent) in large populations

• prisms-study.org: data integration and analysis infrastructure based on Apache Spark and Apache Kafka, including sensor and traditional sources, added mediator layer. 

Research:

• Sensitivizing students to ethical issues in the context of AI systems: studying how we should teach AI ethics

Publications:

• Ethical Considerations in Artificial Intelligence Courses. E. Burton, J. Goldsmith, S. Koenig, B. Kuipers, N. Mattei and T. Walsh. Artificial Intelligence Magazine 2017.

Research:

• Computer games in the classroom: how to teach AI concepts in the context of video games
• Programming pinball machines: how to teach cyber-physical systems in the context of pinball machines

Publications:

• Teaching Undergraduate Artificial Intelligence Classes: An Experiment with an Attendance Requirement. S. Koenig, T. Uras and L. Cohen. EAAI 2020.
• Implementing Games on Pinball Machines. D. Wong, D. Earl, F. Zyda, R. Zink, S. Koenig, A. Pan, S. Shlosberg, J. Singh and N. Sturtevant. FDG 2010.
• Model AI Assignments 2020. T. Neller, S. Keeley, M. Guerzhoy, W. Hoenig, J. Li, S. Koenig, A. Soni, K. Thomason, L. Zhang, B. Sebatian, C. Resnick, A. Oliver, S. Bhupatiraju, K. Agrawal, J. Allingham, S. Yoon, J. Chen, T. Larsen, M. Neumann, N. Norouzi, R. Hausen and M. Evett. EAAI 2020.
• Model AI Assignments. T. Neller, J. DeNero, D. Klein, S. Koenig, W. Yeoh, X. Zheng, K. Daniel, A. Nash, Z. Dodds, G. Carenini, D. Poole and C. Brooks. EAAI 2010.

Class Projects:

• Computer games in the classroom projects
• Project on multi-agent path finding
• Programming pinball machines