4/28/2021

Invited to speak on a panel at Out in Technology and Math, a UCSD event for LGBTQ + STEM students

4/17/2021

Gave an invited tech talk titled AI for Wildlife Conservation for AI for Mankind.

3/10/21

The iWildCam 2021 Competition is now live! This year we go beyond single-frame detection and species categorization to counting individuals of each species across image bursts.

2/20/21

Gave an invited seminar titled CV for Global-scale Biodiversity Monitoring: Scaling Spatial and Taxonomic Covergae Using Contextual Clues at EPFL.

1/11/21

Honored to have been awarded an Amazon/Caltech AI4Science Fellowship. This fellowship recognizes graduate students and postdoctoral scholars that have had a remarkable impact in machine learning and artificial intelligence, and in their application to fields beyond computer science

12/15/20

Was named a Rising Star in Data Science by the Center for Data and Computing (CDAC) at the University of Chicago in January 2021.

12/10/20

Honored to have been awarded a PIMCO Fellowship in Data Science. This fellowship recognizes and supports graduate students and postdoctoral scholars that have had a remarkable impact in data science, broadly defined, and its application to the social sciences.

11/30/20

Gave an invited seminar titled Towards Global-scale Biodiversity Monitoring: Scaling Spatial and Taxonomic Covergae Using Contextual Clues at Microsoft Research Cambridge.

11/16/20

Gave a plenary talk on Deep Learning + Camera Traps at the Imaginecology Workshop.

10/17/20

Gave a talk on global-scale biodiversity monitoring and a tutorial on working with data from static monitoring sensors at the CompSust Doctoral Consortium.

8/4/20

Gave an invited talk at the virtual Ecological Society of America 2020 Meeting, Improving computer vision for camera traps: Leveraging practitioner knowledge to build better models, as part of a session on Deep Learning for Image Analysis in Ecology.

6/28/20

Yannic Kilcher posted a fantastic video walkthrough of our paper: Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection (Paper Explained).

6/26/20

Published a Google AI Blog post about the Context R-CNN architecture, titled Leveraging Temporal Context for Object Detection.

6/25/20

Gave an invited WILDLABS Tech Tutorial titled How do I get started using machine learning for my camera traps?, recording available here.

6/19/20

Presented the results of the 2020 iWildCam Competition and participated in a panel discussion with the winners at the seventh Fine-Grained Visual Categorization (FGVC) Workshop at CVPR 2020 at CVPR 2020.

6/18/20

Presented Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection at CVPR 2020.

6/14/20

Presented Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection at the Women in Computer Vision Workshop at CVPR 2020.

5/26/2020

The iWildCam 2020 Competition, focused on species identification in camera traps, ended with 126 participating teams from around the globe! See the final leaderboard here.

5/26/2020

Gave an invited lecture for Caltech EE/CNS/CS 148 (Selected Topics in Computational Vision), titled Computer Vision for Conservation. See the slides here.

4/3/2020

Gave an invited talk for the CompSust Open Graduate Seminar, titled Improving Computer Vision for Camera Traps: Leveraging Practitioner Insight to Build Solutions for Real-World Challenges. See the recording here.

3/9/20

Launched iWildCam 2020, our 3rd annual camera trap kaggle competition associated with the seventh Fine-Grained Visual Categorization (FGVC) Workshop at CVPR 2020.

3/2/20

Presented our work Synthetic Examples Improve Generalization for Rare Classes at WACV2020.

3/1/20

Organized the Deep Learning Methods and Applications for Animal Re-Identification Workshop at WACV2020 along with Stefan Schneider and Jason Parham, and gave a talk titled Animal Re-Identification from Camera Trap Images: Can We Deal with Low-Quality Data?

2/25/20

Gave an invited departmental seminar titled Computer Vision for Biodiversity Monitoring and Conservation with Elijah Cole at the Yale Center for Biodiversity and Global Change. We also spent a few days visiting the Jetz Lab.

3/2/20

Our paper Context R-CNN: Long Term Temporal Context for Per-Camera Object Detection was accepted at CVPR 2020!

2/21/20

Gave a talk, Improving Computer Vision for Camera Traps Using Expert Intuition At the 2020 Visipedia Retreat at Cornell Tech, which I also helped to organize.

2/8/20-2/13/20

Visited the Mara Elephant Project in Maasai Mara, Kenya to jumpstart future collaborations between MEP, WildMe, and the Vulcan Machine Learning Center for Impact.

2/5/20

Gave an invited seminar titled AI for Camera Traps: Challenges, Best Practices, Benchmarks, and De-Siloing Data at World Agroforestry (ICRAF) in Nairobi, Kenya.

2/3/20

Visited WWF Kenya to discuss the integration of technology into their Southern Kenya, Northern Tanzania (SOKNOT) Transboundary Conservation Programme.

1/30/20

Visited the Ol Pejeta Technology Lab in Laikipia, Kenya to discuss options for expanding their work in conservation technology.

1/15/20-1/29/20

Designed and installed an ecological study using 100 camera traps at Mpala Research Center in Laikipia, Kenya, in partnership with the Great Grevy’s Rally.

12/16/19

Passed my candidacy exam! My committee is Yisong Yue (chair), Pietro Perona, Serge Belongie, and Katie Bouman.

11/7/19-11/8/19

Spoke at and helped organize the Camera Trap Technology Symposium at Google. I gave a talk in the Machine Learning session and led a group Q&A. The talk can be viewed here.

10/29/19

Invited to represent the CV/ML community in the WildLabs Virtual Meetup on Camera Trapping. I spoke alongside Roland Kays, Research Professor at North Carolina State University and the Head of the Biodiversity Lab at the NC Museum of Natural Sciences, and Sam Seccombe, Technical Project Manager and Field Specialist in the Conservation Tech Unit at ZSL.

10/27/19

Gave a talk, sat on a panel, and served in the program committee at the Computer Vision for Wildlife Conservation Workshop at ICCV 2019, in Seoul, South Korea. My talk was titled Camera traps: generalization, sample efficiency, best practices, benchmarks, and de-siloing data.

10/22/19

Presented an extended abstract, Efficient Pipeline for Automating Species ID in new Camera Trap Projects, in the Symposium on advancing biodiversity research through artificial intelligence at Biodiversity Next 2019 in Leiden, The Netherlands. I was also a collaborating author on a second abstract, Training Machines to Identify Species using GBIF-mediated Datasets, and was invited to speak on a panel on AI for Biodiversity.

08/30/19

Completed my Google Research Internship in Seattle, Washington and was invited to stay at Google as a Student Researcher throughout the academic year.

08/05/19

Gave an oral presentation, Efficient Pipeline for Camera Trap Image Review at the Data Mining and AI for Conservation Workshop at KDD 2019 in Anchorage, Alaska. Our paper was selected to be featured at the main KDD conference Earth Day celebration.

06/17/19

Saw 336 global teams participate in the second year of my kaggle camera trap challenge, iWildCam 2019, as a part of the Sixth Fine-Grained Visual Categorization Workshop (FGVC) at CVPR 2019 in Long Beach, California.

05/13/19

Started my summer research internship on the Visual Dynamics team at Google, working with Jonathan Huang and Wildlife Insights.