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t increasing access to and capacity in stem through mentorship teaching and outreach and was honored to have my efforts recognized with the inaugural caltech computing and mathematical sciences department gradient for change award and the inaugural caltech engineering and applied science division new horizons award research group phd students julia chae timm haucke neha hulkund justin kay eddie vendrow rupa kurinchi vendhan elena sierra incoming fall 2025 antoine salaun incoming fall 2025 masters and visiting students lauren shrack meng yuyan chen visited summer 2024 from mcgill undergraduates kai van brunt xenia zhao asmi kumar ada tsui david fang alumni ari pero alumni avi sundaresan caltech alumni interested in joining the group if you are interested in any position with the group postdoc phd meng urop visitor instead of emailing me please fill out the interest survey below so i can better organize my responses i am unlikely to respond to individual emails interested in a phd i consider students primarily via mit eecs and the mit whoi joint program but i would be open to advising students with the right fit for my lab through mit eaps or mit cee if that is better aligned with your background if you are interested in working with me on impact driven computer vision research for the environment biodiversity conservation and sustainability apply to any of these programs and list me in your application unfortunately i am unlikely to be able to meet with prospective applicants before they have gone through the formal review process interested in a postdoc i will be welcoming postdocs on an ongoing basis depending on funding availability if our research interests align please fill out the interest survey below and include any ideas you have for projects you would be interested in exploring together i am happy to develop fellowship proposal s together i m particularly interested in bringing on a postdoctoral researcher with a background in quantitative large scale biodiversity monitoring to explore the intersection between machine learning outputs and ecological modeling inputs with me and my group fill out the interest survey here selected invited talks plenary panel on scienctific discovery and the environment cvpr 2023 ai and conservation united nations world wildlife day invited speaker 2024 u s department of the interior ai strategy workshop keynote speaker 2024 u s department of fish and wildlife geospatial training workshop keynote speaker 2024 wwf fuller seminar 2023 movement ecology and ai ohio state university room2roam keynote speaker 2024 international symposium on heirarchical bio navigation keynote speaker 2024 monitoring the urban forest with auto arborist rise seminar 2023 image xd symposium keynote 2023 ai helps ukraine seminar 2022 mi eaps seminar 2022 stanford computer vision seminar 2022 cornell urban ai seminar 2022 computer vision for global scale biodiversity monitoring scaling geospatial and taxonomic coverage using contextual clues epfl school of computer communication sciences seminar 2022 eth zurich sustainability seminar 2022 mit eecs seminar 2022 caltech environmental science and engineering seminar 2022 uc berkeley eecs seminar 2022 university of washington computer science engineering seminar 2022 cornell university computer science seminar 2022 ucsb pstats seminar 2022 ucsb computer science computer engineering joint seminar 2022 the ohio state university computer science engineering seminar 2022 university of melbourne computer science seminar 2022 stevens institute of technology data science seminar 2022 ucla electrical and computer engineering seminar 2022 mit operations research center seminar on sustainability and climate change 2022 university of sydney computer science seminar 2022 climate change ai seminar with dave thau global data and technology lead scientist at wwf 2022 ucl center for biodiversity and environment research seminar 2022 ist austria research seminar 2022 max planck institute for intelligent systems and cyber valley scientific symposium 2022 georgia tech computational science and engineering seminar 2021 university of new south wales cognitive robotics seminar 2021 reed college computer science seminar 2021 berkeley ai climate seminar 2021 university of guelph care ai and biodiversity institute joint seminar 2021 seminar at microsoft research cambridge 2020 computational sustainability compsust doctoral consortium 2020 computational imaging challenges in ecological monitoring keynote at the international conference in computational photography 2023 edge ai for wildlife conservation tinyml seminar 2023 ajcai edge ai workshop 2022 joint human ai elephant population monitoring a case study in the greater mara ecosystem keynote the second cv4animals workshop at cvpr 2022 beyond benchmarks going from competition winning methods to real world solutions lifeclef 2021 queer in ai at icml 2021 ai assisted biodiversity monitoring data science frontiers seminar at the african institute for mathematical sciences 2021 leveraging ai to extend specimen networks at idigbio 2021 princeton ai4all 2021 computer vision for biodiversity monitoring and conservation epfl joint mathis lab seminar 2021 ai for mankind 2021 yale center for biodiversity and global change seminar 2020 deep learning camera traps plenary at imaginecology workshop deep learning pour le traitement et l analyse d imageset de sons en écologie at le gdr ecostat 2020 improving computer vision for camera traps leveraging practitioner insight to build solutions for real world challenges ecological society of america annual meeting 2020 compsust open graduate seminar 2020 camera trap technology symposium 2019 ai for camera traps challenges best practices benchmarks and de siloing data world agroforestry centre icraf seminar 2020 wildlabs virtual meetup on camera trapping 2019 computer vision for wildlife conservation workshop at iccv 2019 computer vision for camera traps caltech ai4science workshop 2019 usc center for ai in society symposium on ai for conservation 2019 research seminar at google venice 2019 selected publications this list is a selected subset and may not be up to date for a full list of publications please see my cv or google scholar denotes equal contribution denotes equal advising harnessing artificial intelligence to fill global shortfalls in biodiversity knowledge laura j pollock justin kitzes sara beery kaitlyn m gaynor marta a jarzyna oisin mac aodha bernd meyer david rolnick graham w taylor devis tuia tanya berger wolf nature reviews biodiversity 2025 paper do large language model benchmarks test reliability joshua vendrow edward vendrow sara beery aleksander madry paper webpage generative ai as a tool to accelerate the field of ecology kasim rafiq sara beery meredith s palmer zaid harchaoui briana abrahms nature ecology evolution 2025 paper personalized representation from personalized generation shobhita sundaram julia chae yonglong tian sara beery phillip isola icml 2025 paper webpage the potential for ai to revolutionize conservation a horizon scan sam a reynolds sara beery neil burgess mark burgman stuart hm butchart steven j cooke david coomes finn danielsen enrico di minin américa paz durán francis gassert amy hinsley sadiq jaffer julia pg jones binbin v li oisin mac aodha anil madhavapeddy stephanie al o donnell william m oxbury lloyd peck nathalie pettorelli jon paul rodríguez emily shuckburgh bernardo strassburg hiromi yamashita zhongqi miao william j sutherland trends in ecology evolution 2024 paper inquire a benchmark for natural world image retrieval edward vendrow omiros pantazis alexander shepard gabriel brostow kate e jones oisin mac aodha sara beery grant van horn neurips 2024 datasets and benchmarks track webpage application driven innovation in machine learning david rolnick alan aspuru guzik sara beery bistra dilkina priya l donti marzyeh ghassemi hannah kerner claire monteleoni esther rolf milind tambe adam white icml 2024 position track paper align and distill unifying and improving domain adaptive object detection justin kay timm haucke suzanne stathatos siqi deng erik young pietro perona sara beery grant van horn tmlr 2025 featured paper codebase dataset sustainable trustworthy human technology partnership tanya berger wolf sara beery david rolnick justin kitzes david thau devis tuia daniel rubenstein a landmark environmental law looks ahead science 2023 paper mammalnet a large scale video benchmark for mammal recognition and behavior understanding jun chen ming hu darren j coker michael l berumen blair costelloe sara beery anna rohrbach mohamed elhoseiny cvpr 2023 paper data teaching computer vision for ecology elijah cole suzanne stathatos björn lütjens tarun sharma justin kay jason parham benjamin kellenberger and sara beery paper cv4ecology workshop the caltech fish counting dataset a benchmark for multiple object tracking and counting justin kay peter kulits suzanne stathatos siqi deng erik young sara beery grant van horn and pietro perona eccv 2022 paper data the auto arborist dataset a large scale benchmark for multiview urban forest monitoring under domain shift sara beery guanhang wu trevor edwards filip pavetic bo majewski shreyasee mukherjee stanley chan john morgan vivek rathod jonathan huang cvpr 2022 paper data blog perspectives in machine learning for wildlife conservation devis tuia benjamin kellenberger sara beery blair r costelloe silvia zuffi benjamin risse alexander mathis mackenzie w mathis frank van langevelde tilo burghardt roland kays holger klinck martin wikelski iain d couzin grant van horn margaret c crofoot charles v stewart tanya berger wolf nature communications 2022 paper extending the wilds benchmark for unsupervised adaptation shiori sagawa pang wei koh tony lee irena gao sang michael xie kendrick shen ananya kumar weihua hu michihiro yasunaga henrik marklund sara beery etienne david ian stavness wei guo jure leskovec kate saenko tatsunori hashimoto sergey levine chelsea finn percy liang iclr 2022 oral paper code data scaling biodiversity monitoring for the data age sara beery acm xrds 2021 paper wilds a benchmark of in the wild distribution shifts pang wei koh shiori sagawa sang michael xie marvin zhang akshay balsubramani weihua hu michihiro yasunaga richard lanas phillips irena gao tony lee etienne david ian stavness wei guo berton earnshaw imran haque sara beery jure leskovec anshul kundaje emma pierson sergey levine chelsea finn percy liang iclr 2021 oral paper code data benchmarking representation learning for natural world image collections grant van horn elijah cole sara beery kimberly wilber serge belongie and oisin mac aodha cvpr 2021 oral paper code data video species distribution modeling for machine learning practitioners a review sara beery elijah cole joseph parker pietro perona kevin winner acm compass 2021 paper elephantbook a semi automated human in the loop system for elephant re identification peter kulits jake wall anka bedetti michelle henley sara beery acm compass 2021 paper a deep active learning system for species identification and counting in camera trap images mohammad sadegh norouzzadeh dan morris sara beery neel joshi nebojsa jojic jeff clune methods in ecology and evolution 2021 paper automated salmonid counting in sonar data peter kulits angelina pan sara m beery erik young pietro perona grant van horn climate change ai at neurips 2020 paper video context r cnn long term temporal context for per camera object detection sara beery guanhang wu vivek rathod ronny votel jonathan huang cvpr 2020 paper code video synthetic examples improve generalization for rare classes sara beery yang liu dan morris jim piavis ashish kapoor markus meister neel joshi pietro perona wacv 2020 paper efficient pipeline for camera trap image review sara beery dan morris siyu yang data mining and ai for conservation at kdd 2018 selected to be featured at kdd earth day paper code recognition in terra incognita sara beery grant van horn pietro perona eccv 2018 paper data finding areas of motion in camera trap images agnieszka miguel sara beery erica flores loren klemesrud ieee icip 2016 paper teaching instructor mit 6 s954 computer vision and planetary health spring 2025 course webpage https cv4planet github io co instructor mit 6 s898 deep learning fall 2023 fall 2024 course webpage https phillipi github io 6 s898 co instructor mit 6 8300 1 advances in computer vision spring 2024 course webpage https advances in vision github io workshop on computer vision methods for ecology course webpage http cv4ecology csail mit edu a three week intensive program teaching computer vision methods for ecology seeking to empower ecologists to accurately and efficiently analyze large image audio or video datasets using computer vision co instructor caltech ee cs cns 148b advanced topics in computer vision spring 2021 i helped adapt this advanced projects based computer vision course to focus on conservation and sustainability applications to set up project groups for success i curated a set of ecological challenges with publicly available image and video datasets and matched projects to ngos and research groups that would directly benefit to provide domain expertise and context i mentored 5 teams of computer vision students in structuring and defining these real world challenges as computer vision and machine learning problems and assisted them in holistically probing and evaluating their solutions and effectively communicating them to both computer vision and machine learning experts and the ecological community guest lectures and tutorials lecture at caltech ge bi be cns ese147 quantitative ecology 2022 lecture at caltech bi 1 principles of biology 2022 tutorial at 2d3dai 2021 lecture at georgia tech vip 4601 vvs humanitech 2020 lecture at georgia tech vip 4601 vwe gatech4wildlife 2020 tutorial at compsust doctoral consortium 2020 tutorial at wildlabs tech tutors 2020 lecture at caltech ee cns cs 148 advanced topics in computer vision 2020 cv bio download my cv here last updated april 2024 bio for invited talks dr sara beery is the homer a burnell career development professor in the mit faculty of artificial intelligence and decision making she received her phd in computing and mathematical sciences at caltech where she was advised by pietro perona her research focuses on building computer vision methods that enable global scale environmental and biodiversity monitoring across data modalities tackling real world challenges including geospatial and temporal domain shift learning from imperfect data fine grained categories and long tailed distributions her work has been recognized with a schmidt sciences ai2050 early career fellowship an nsf career grant the amori doctoral prize an amazon ai for science fellowship a pimco data science fellowship and an nsf grfp she partners with industry nongovernmental organizations and government agencies to deplo...