Jenna M. Kline
Field-deployed intelligent sensing systems for coordinated, adaptive monitoring at the far edge.
FIG.01 — PhD, COMPUTER SCIENCE & ENGINEERING
I am a computer systems researcher who designs, builds, and deploys intelligent sensing systems for dynamic, resource-constrained field environments.
I earned my PhD in Computer Science & Engineering at The Ohio State University, advised by Dr. Christopher Stewart and Dr. Tanya Berger-Wolf. I am now a postdoctoral associate in MIT Civil & Environmental Engineering with Dr. Heidi Nepf, developing sensing systems for coastal resilience through the Climate Project at MIT.
Research interests
My research explores intelligent sensing systems for observing dynamic environments, with interests spanning edge AI, autonomy and robotics, multimodal sensing, and data infrastructure. I work with ecologists and environmental scientists to apply these systems across wildlife behavior, biodiversity monitoring, coastal resilience, and other emerging environmental challenges.
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Resource-aware autonomy at the far edge
Systems that close the perception–control loop on a single platform, managing inference, navigation, and resource use in real time under tight compute, energy, and connectivity limits.
Coordinated cross-modal sensing
Distributed architectures that link drones, camera traps, and bioacoustic sensors across space and time, so what one observes guides where and when the network samples next.
Open infrastructure for field AI
Open standards, datasets, and benchmarks that make field-deployed AI systems reproducible and reusable across studies and ecosystems.
Selected papers
What the Sheep Can Teach the Shepherd: A Vision for Self-Organizing Drone Swarms Informed by Collective Animal Behavior
A Maneuver-Indexed Testbed for Context-Aware Adaptive Wildlife Drones
WildWing: An Open-Source, Autonomous and Affordable UAS for Animal Behaviour Video Monitoring
Edge-Native, Behavior-Adaptive Drone System for Wildlife Monitoring
Studying collective animal behaviour with drones and computer vision
MMLA: Multi-Environment, Multi-Species, Low-Altitude Aerial Footage Dataset
Talks & presentations
Lessons from FAIR² Drones: Toward AI-Ready Multimodal, Multispatial Sensor Data for Ecology
AI for Ecology: Accelerating Discoveries, Reducing Uncertainties, and Scaling Solutions
FAIR² Drones: An AI-Ready Standard for Cross-Domain Wildlife Drone Datasets
Autonomous Drones for Animal Studies with Edge AI
Autonomous AI-Driven Environmental Sensing Systems
How do drones fit into multimodal sensing networks?
Autonomous, Adaptive Vision-Based Remote Sensing System for Dynamic Field Animal Ecology Studies
Drones and AI in Field Animal Ecology
From Ohio to Kenya: Autonomous Drones in Field Ecology & Conservation
Autonomous Drones for Collective Wildlife Behavior
Individual Identification of Zebras with Autonomous UAV Swarms
PhD Forum: An Adaptive Autonomous Aerial System for Dynamic Field Animal Ecology
Adaptive, Autonomous Aerial Systems for Dynamic Field Animal Ecology Studies
Intelligent Cyberinfrastructure for Remote Sensing with Autonomous Aerial Robotics
Describing HPC Filesystem Trees with the Grand Unified File-Index
Interdisciplinary Applications of Autonomous Unmanned Aerial Vehicles
Autonomous UAV Missions for Studying Wildlife Behavior: A Case Study for the Individual Identification of Zebras
Individual Identification of Zebras with Autonomous UAV Swarms
PhD Forum: Edge Computing for Software-Defined Cartography
Projects
Field-deployed systems, datasets, open standards, and the tools that support them.
WildWing
Open-source, autonomous, affordable UAS for animal behaviour video monitoring.
Maneuver-Indexed Testbed
Interactive evaluation environment for testing context-aware, behavior-adaptive wildlife drone systems across flight maneuvers and ecological conditions.
SmartWilds
Led multimodal wildlife-monitoring project integrating synchronized drone, camera-trap, and bioacoustic observations.
KABR & MMLA Collections
Field-collected drone-video datasets, synchronized telemetry, annotations, trained models, and open workflows for wildlife detection and behavior monitoring.
In the classroom
Research Mentorship
Supervised five undergraduate researchers at Ohio State and two at MIT, including student-led projects published at SEC 2025 and CV4Animals at CVPR 2026. Co-supervised a University of Bologna master's thesis resulting in two ACSOS 2024 publications.
Data Management in the Cloud
Systematic organization of data on cloud architectures, B-tree and hash-based indexing, query optimization and cardinality estimation, replication, data partitioning, and distributed task scheduling.
Modeling & Problem Solving with Spreadsheets and Databases
Hands-on lab instruction in data modeling, spreadsheet analysis, and relational database fundamentals for problem solving.
News
Speaking at ESA 2026
Presenting “Lessons from FAIR² Drones: Toward AI-Ready Multimodal, Multispatial Sensor Data for Ecology” in the symposium “Building an AI-Ready Ecology & Biodiversity Data Infrastructure for Science and Action” (Mon, Jul 27), and joining the “AI for Ecology” panel (Tue, Jul 28) at the Ecological Society of America Annual Meeting in Salt Lake City.
Two papers accepted to ACSOS 2026
“What the Sheep Can Teach the Shepherd” presents a vision for self-organizing drone swarms informed by collective animal behavior; “A Maneuver-Indexed Testbed for Context-Aware Adaptive Wildlife Drones” contributes a peer-reviewed research artifact for evaluating behavior-adaptive flight systems.
Five abstracts accepted to TDWG 2026
Contributions span AI-ready data standards, automated FAIR evaluation, multimodal sensing coordination, edge/cloud infrastructure, and modular behavior-monitoring workflows.
Starting a postdoc at MIT
Joining Dr. Heidi Nepf's group in MIT Civil & Environmental Engineering, working on drones and computer vision for coastal monitoring.
Successfully defended my PhD dissertation
“Autonomous Drone Systems for In Situ Animal Ecology.” Grateful to advisors, committee, and labmates — and excited to join MIT as a postdoc.
2025 Robert May Prize
Awarded for best paper in Methods in Ecology & Evolution by an early-career author.
Organized WILDLABS Edge Computing Group's first in-person meeting
Ahead of the International Conservation Technology Conference (ICTC) in Lima, Peru.
ACM/IEEE SEC 2025 — 1st Place Student Research Competition
For “An Edge-Native Approach to Behavior-Adaptive Navigation in Drone Systems.”
2025–2026 Presidential Fellowship
Ohio State's most prestigious graduate award, recognizing outstanding scholarly accomplishment entering the final phase of dissertation research.
Alumni Grant for Graduate Research & Scholarship (AGGRS)
One of two engineering graduate students awarded the AGGRS for dissertation research. Featured in Imageomics news.
Selected for MIT and Boston University Rising Stars in EECS
A program supporting women pursuing academic careers in EECS, with mentorship and career development.
WildDrone Summer School · Max Planck Institute, Konstanz
Presented “How do drones fit into multimodal sensing networks?” Also joined the AI+Environment Summit at ETH Zurich.
Summer fieldwork at The Wilds, featured by Imageomics
Led a team of students conducting fieldwork and collecting data at The Wilds in Cumberland, OH.
Selected for WiscProf: Future Faculty in Engineering
A four-day program at UW–Madison for senior PhD students and postdocs pursuing academic careers in engineering.
Drone research featured in Ohio State News
Coverage of my autonomous drones for animal ecology and their potential impact on conservation research.
CSE Graduate Student Research Award
Recognizing exceptional research contributions in the Department of Computer Science & Engineering.
Hayes Advanced Research Forum — Engineering Oral, 1st Place
For “Autonomous, Adaptive Vision-Based Remote Sensing System for Dynamic Field Animal Ecology Studies.”
Fieldwork at Ol Pejeta Conservancy, Kenya
Tested autonomous drones for wildlife monitoring with the WildDrone team at Ol Pejeta.
Passed PhD candidacy exam
Approved as the first Imageomics Institute PhD candidate.
Selected for the 2023 CRA-WP Grad Cohort for Women
Attended the Computing Research Association's Grad Cohort Workshop for Women in San Francisco, CA.
Drone pilot for the KABR dataset in Kenya
Fieldwork at Mpala Research Center collecting data for the KABR wildlife behavior dataset.
Let's build the
next smart system.
jennamkline [at] gmail.com