Welcome to InfoWild 2023!

1st CIKM International Workshop on Knowledge Extraction and Management for Wildlife Conservation (InfoWild 2023)

To be held in conjunction with 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023)

In collaboration with CIKM 2023, we are pleased to announce the call for papers for InfoWild 2023, a workshop dedicated to explore and enhance AI’s role in big data analysis for wildlife conservation, in brief, Nature Through the Lens of AI . It seeks to address crucial challenges related to data heterogeneity, scale integration, data privacy, mitigating biases, and decision-making under uncertainty. This workshop is centred around leveraging AI’s prowess in deciphering complex spatio-temporal data patterns for wildlife conservation, thereby contributing significantly to the broader canvas of AI for social good.

Call for Papers

We invite original research contributions and work-in-progress papers related to the workshop's theme. Topics of interest include but are not limited to:

  • Data Acquisition and Preprocessing: Leveraging AI for wildlife data collection, quality assessment, privacy issues, and bias mitigation.
  • Data Integration and Aggregation: Semantic processing and data fusion techniques for wildlife conservation.
  • Efficient Data Processing: AI-enabled processing of wildlife conservation data.
  • Analytics and Machine Learning: AI and machine learning applications in wildlife conservation, including predictive modeling and scalable analysis algorithms.
  • Neural Information and Knowledge Processing: Use of neural networks in wildlife conservation tasks.
  • Information Access and Retrieval: Application of search algorithms, retrieval models, and recommender systems in wildlife conservation.
  • Evaluation, Performance Studies, and Benchmarks: Assessment of AI applications in wildlife conservation.
  • Crowdsourcing: Utilizing crowdsourcing for tasks such as data collection, species identification, and behavior observation in wildlife conservation.
  • Understanding Multi-modal Content: Applying natural language processing, computer vision, and knowledge extraction in wildlife conservation.
  • Data Presentation: Visualization and summarization of conservation data.

Submission Guidelines

The following paper categories are welcome:

  • Full papers: Full papers (limited to 10 pages) should present original, unpublished research papers which belong to the scope of the workshop and are not being considered for publication in any other forum.
  • Short papers: Short papers (limited to 4 pages) may focus on a narrowly defined topic, may report on preliminary results (or work-in progress), or may present relevant study results that do not warrant a full paper. The short papers should be original, unpublished, within the scope of the workshop and are not being considered for publication in any other forum.
  • Posters: Poster submissions (2 pages + references) should detail innovative ideas or present preliminary results for discussion.
  • Demo papers (limited to 4 pages): Presenting innovations in action, showcasing practical applications.
  • Dataset and Challenge papers (limited to 4 pages): Unveiling new data treasures and stimulating problem-solving endeavors.
  • Work-in-progress papers (limited to 4 pages): Unfolding ongoing research, paving the way for future breakthroughs.
  • Visionary papers (white papers, limited to 4 pages): Illuminating the path to a transformative future through visionary insights.
  • Review paper (Relevant work that has been previously published, limited to 10 pages): Reflecting the past, shaping the present, and informing future directions in the field.
Workshop papers will not be included in the ACM proceedings. Accepted papers will be published on the workshop's website, however, will not be considered archival for resubmission purposes (i.e., authors are allowed to submit the paper to a conference or journal).

Manuscripts should be submitted in PDF format using the ACM sigconf template, see https://www.acm.org/publications/proceedings-template. Submissions should be in 2-column sigconf format. We look forward to your contributions and particiaptions in our workshop.

Papers should be submitted electronically through the EasyChair submission system: Submission Link

Important Dates

Submission deadline: August 30, 2023 Sept 20, 2023 11:59PM (AoE)
Notification of acceptance: October 10, 2023
Camera-ready papers due: October 15, 2023 11:59PM (AoE)
Workshop date: October 22, 2023 (09:00-17:00 BST)

Detailed Program (22nd Oct, 2023, Teaching and Learning - LG03)

(All times in BST)

Here is the link to attend the workshop virtually:Zoom

9:00-9:10 AM

Opening remarks by InfoWild'23 Workshop Organizers

9:10-10:30 AM

Keynote talk by Dr. Scott Pezanowski

President, BrightWorld Labs

Topic: What do scientists researching wildlife conservation have in common with realtors?

Abstract: We cannot emphasize enough the value of location in wildlife conservation. Location can be explicit when you use GPS and other location tagging to track wildlife. And location can be implicit when the public, media, and policymakers talk about places and other things we can tie to location. The scientific community has produced valuable insights by analyzing the movement of people, wildlife, goods, and more, where the data is precise movement trajectories. However, research should focus more on geographic movement from text descriptions. Descriptions of things moving include rich contextual information that describes what is moving, when, why, and how it moves. There are many challenges to utilizing this source, like location ambiguities and fusion with other data sources. But, combining Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning with visual analytics will help us better utilize this source to monitor and analyze wildlife for conservation. Finally, my most important messages from this talk will be 1) geospatial analysis is vital to all key topics in knowledge extraction and management for wildlife conservation and 2) the geospatial industry unnecessarily complicates geospatial analysis, and many scientists outside the field would benefit from knowing it is simply not that unique.

10:30-11:00 AM


11:00-11:20 AM

Paper Presentation: 20min, QA: 10min

Title: A Flexible and Scalable Approach for Collecting Wildlife Advertisements on the Web

Authors: Juliana Barbosa, Juliana Freire and Sunandan Chakraborty

Abstract: Wildlife traffickers are increasingly carrying out their activities in cyberspace. As they advertise and sell wildlife products in online marketplaces, they leave digital traces of their activity. This creates a new opportunity: by analyzing these traces, we can obtain insights into how trafficking networks work as well as how they can be disrupted. However, collecting such information is difficult. Online marketplaces sell a very large number of products and identifying ads that actually involve wildlife is a complex task that is hard to automate. Furthermore, given that the volume of data is staggering, we need scalable mechanisms to acquire, filter, and store the ads, as well as to make them available for analysis. In this paper, we present a new approach to collect wildlife trafficking data at scale. We propose a data collection pipeline that combines scoped crawlers for data discovery and acquisition with foundational models and machine learning classifiers to identify relevant ads. We describe a dataset we created using this pipeline which is, to the best of our knowledge, the largest of its kind: it contains almost a million ads obtained from 41 marketplaces, covering 235 species and 20 languages.

Camera Ready Version of the paper

11:30 AM-12:30 PM

Talk and Discussion on the topic

Analysis of Elephant Movement in Sub-Saharan Africa: Ecological, Climatic, and Conservation Perspectives

Authors: Matthew Hines, Gregory Glatzer,Shreya Ghosh and Prasenjit Mitra. ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (COMPASS '23)

Abstract: The interaction between elephants and their environment has profound implications for both ecology and conservation strategies. This study presents an analytical approach to decipher the intricate patterns of elephant movement in Sub-Saharan Africa, concentrating on key ecological drivers such as seasonal variations and rainfall patterns. Despite the complexities surrounding these influential factors, our analysis provides a holistic view of elephant migratory behavior in the context of the dynamic African landscape. Our comprehensive approach enables us to predict the potential impact of these ecological determinants on elephant migration, a critical step in establishing informed conservation strategies. This projection is particularly crucial given the impacts of global climate change on seasonal and rainfall patterns, which could substantially influence elephant movements in the future. The findings of our work aim to not only advance the understanding of movement ecology but also foster a sustainable coexistence of humans and elephants in Sub-Saharan Africa. By predicting potential elephant routes, our work can inform strategies to minimize human-elephant conflict, effectively manage land use, and enhance anti-poaching efforts. This research underscores the importance of integrating movement ecology and climatic variables for effective wildlife management and conservation planning.

Link of the paper

12:30-1:30 PM

Lunch Break

1:30-2:30 PM

Keynote talk by Dr. Thomas Muller

Goethe University and Senckenberg Biodiversity and Climate Research Centre, Frankfurt (Germany)

Topic: Animal Movement and Conservation

2:30-2:50 PM

Paper Presentation: 20min, QA: 10min

Title: WildGEN: Long-horizon Trajectory Generation for Wildlife

Authors: Ali Al-Lawati, Elsayed Eshra and Prasenjit Mitra

Abstract: Trajectory generation is an important concern in pedestrian, vehicle, and wildlife movement studies. Generated trajectories help enrich the training corpus in relation to deep learning applications, and may be used to facilitate simulation tasks. This is especially significant in the wildlife domain, where the cost of obtaining addi- tional real data can be prohibitively expensive, time-consuming, and bear ethical considerations. In this paper, we introduce WildGEN: a conceptual framework that addresses this challenge by employing a Variational Auto-encoders (VAEs) based method for the acquisition of movement characteristics exhibited by wild geese over a long horizon using a sparse set of truth samples. A subsequent post- processing step of the generated trajectories is performed based on smoothing filters to reduce excessive wandering. Our evaluation is conducted through visual inspection and the computation of the Hausdorff distance between the generated and real trajectories. In addition, we utilize the Pearson Correlation Coefficient as a way to measure how realistic the trajectories are based on the similarity of clusters evaluated on the generated and real trajectories.

Camera Ready Version of the paper

3:00-3:30 PM


3:30-4:15 PM

Keynote talk by Dr. Bistra Dilkina

Dr. Allen and Charlotte Ginsburg Early Career Chair in Computer Science and Associate Professor of Computer Science, University of Southern California.

Topic: AI for Wildlife Conservation

4:15-5:00 PM

Keynote talk by Christopher Yeh

Computing and Mathematical Sciences, California Institute of Technology, USA

Topic: Shared Challenges across Machine Learning for Sustainability

Abstract: Machine learning techniques have demonstrated significant advancements across a wide range of sustainability issues, ranging from poverty mapping to energy systems and wildlife conservation. While the domains are distinct, the underlying machine learning problems have a number of shared challenges modeling challenges. In this talk, I will describe how the problems of datasets curation, uncertainty quantification, decision-focused learning, and active learning are both shared and intertwined. By understanding and addressing these shared challenges, we can maximize the potential of machine learning in tackling pressing global sustainability issues.

5:00-5:30 PM

Panel Discussion and Concluding Remarks

Discussion Topic: "What is the next step?"

Concluding Remarks by Dr. Prasenjit Mitra

Future directions in the field of AI-driven wildlife conservation: (1) Can we discern and interpret spatio-temporal patterns in largescale human activity data related to the frequency and intensity of human-wildlife interactions and conflicts? (2) How can we quantify and predict the impact of various sound and light pollution types on wildlife behavior and visitor experiences in protected areas? (3) To what extent do human-induced habitat modifications, such as land-use changes and settlements, impact the signature mobility or activity patterns of wildlife? Can we develop an AI model to quantify these effects? (4) How can we leverage AI-driven spatio-temporal data analysis to enhance protection strategies for endangered species? (5) Can we utilize spatio-temporal data analysis to predict wildlife-human conflicts and devise risk mitigation strategies? (6) What are the potential obstacles and limitations when employing AI for spatio-temporal data analysis in wildlife conservation? (7) How can we apply AI-driven spatio-temporal analysis to understand the effects of climate change on wildlife migration patterns? (8) Can AI-driven spatio-temporal data analysis aid in disease surveillance within wildlife populations? (9) How do we ensure ethical use of AI and uphold animal privacy rights in wildlife conservation?

Workshop Organizers

Organizer 1

Prasenjit Mitra

Professor, The Pennsylvania State University, USA and Visiting Professor, Leibniz University, Hannover, Germany

Organizer 2

Bistra Dilkina

Associate Professor, Computer Science, Co-Director, Center for Artificial Intelligence in Society (CAIS), University of Southern California, USA

Organizer 4

Thomas Müller

Professor for Movement Ecology and Biodiversity Conservation, Goethe University and Senckenberg Biodiversity and Climate Research Centre, Frankfurt, Germany

Organizer 4

Shreya Ghosh

Postdoctoral Scholar
The Pennsylvania State University, USA


  • Sanjay Chawla, Research Director of QCRI’s Data Analytics department
  • Dan Morris, Research Scientist, Google AI for Nature and Society
  • Bing Pan, Professor of Commercial Recreation and Tourism, The Pennsylvania State University
  • Lily Xu, Ph.D. Student, Harvard University, USA
  • Saptarshi Sengupta, Ph.D. Student, College of IST, Pennsylvania State University, USA
  • Fei Fang, Assistant Professor of Computer Science at Carnegie Mellon University, Pennsylvania
  • Emmanuel Dufourq, AIMS-Canada Junior Research Chair
  • Johnson Kinyua, Associate Teaching Professor, College of IST, Pennsylvania State University, USA
  • Brendan Derrick Taff, Associate Professor, Recreation, Park, and Tourism Management, The Pennsylvania State University, USA
  • Edwin Sabuhoro, Assistant Professor,Recreation, Park, and Tourism Management, The Pennsylvania State University, USA
  • Gileard Minja, Mwenge Catholic University Tanzania
  • Derek Lee, The Pennsylvania State University, USA
  • Andrew Perrault, Assistant Professor, The Ohio State University, USA
  • Titus Enock Adhola, Lecturer, University of Nairobi, Kenya
  • Randall Boone, Assistant Professor, Colorado State University, USA
  • Lorène Jeantet, Postdoctoral Researcher, University of Stellenbosch, African Institute for Mathematical Sciences - AIMS South Africa