Research & Grants

AI SENSE USA · Baltimore, MD & Kathmandu, Nepal · Last updated April 2026

AI SENSE is an R&D-focused venture at the intersection of nature and technology. We design, build, and deploy intelligent systems that bridge natural environments with digital sensing tools — applying edge AI and nature-inspired algorithms to support sustainable, data-driven decisions in agriculture, biodiversity monitoring, and climate resilience.

We actively collaborate with universities, government research agencies, and conservation organisations. If you are a researcher, faculty member, or grant administrator interested in joint work, this page outlines our current funding, research areas, and how to engage.

Active Funding

NSF SBIR Phase I — AI CoExist

Funder: National Science Foundation (NSF), Small Business Innovation Research Programme
Topic: Wildlife detection and adaptive deterrence for farming communities
Status: Active

AI CoExist integrates AI-enabled cameras with a detect–deter–adapt feedback loop to detect, classify, and track wildlife species in real time, enabling humane coexistence between farmers and local ecosystems. This project represents our flagship funded research initiative.

USDA Collaborative Projects

Funder: United States Department of Agriculture
Topic: Precision agriculture, crop loss quantification, disaster response
Status: Ongoing collaboration

In partnership with USDA and land-grant universities, we are developing AI-driven tools for rapid agricultural damage assessment using satellite, UAV, and IoT sensor data. Research outputs include open datasets and policy briefs.

Research Areas

Our active research spans the following domains:

Wildlife detection and humane deterrence (computer vision, acoustic sensing)
Agricultural disaster response (satellite + UAV + IoT data fusion)
Urban farming AI monitoring (crop health, environmental sensing)
Edge AI and TinyML for resource-constrained outdoor environments
Federated learning for distributed sensor networks
Acoustic sensing and biodiversity monitoring
Climate-smart agriculture and climate resilience modelling
Human–wildlife conflict mapping and spatial ecology

University Collaborators

We maintain active research relationships with the following institutions:

University of Maryland, College Park (UMD)
University of Maryland Baltimore County (UMBC)
University of Maryland Eastern Shore (UMES)

Collaborating Researchers

The following faculty and researchers contribute expertise to our projects:

Dr. Nirupam Roy

Assistant Professor, Department of Computer Science, University of Maryland, College Park.
Expertise: Acoustic sensing systems, mobile computing, human–computer interaction.

Dr. Anuradha Ravi

Research focus: Edge AI, federated learning, and distributed inference for IoT networks.
Contributing to our TinyML optimisation pipeline and privacy-preserving field sensing research.

Dr. Travis Gallo

Urban ecologist and conservation scientist.
Expertise: Human–wildlife coexistence, urban biodiversity, applied spatial ecology.
Advising on ecological validity of AI CoExist deterrence outcomes.

Dr. Nirmalya Roy

Professor and COO, AI SENSE. Director, Mobile, Pervasive, and Sensor Computing Lab, UMBC.
Expertise: Pervasive computing, wireless sensor networks, smart environments, activity recognition.

Grant Collaboration

We welcome proposals for joint research and collaborative grant applications. AI SENSE can serve as a commercial co-applicant or technical partner on federal grants (NSF, USDA, DARPA, NIH, DOE) and international programmes. Our strengths include:

Hardware prototyping and field deployment of sensing systems
Annotated wildlife and agricultural datasets
Edge AI inference pipelines and TinyML expertise
Access to field sites in the US (Maryland) and South Asia (Nepal)
Industry co-funding or cost-share contributions for SBIR / STTR proposals

To discuss a collaboration, email us at [email protected] with a brief description of your research goals and timeline.

Publications & Datasets

The following represent indicative work from our team and collaborators. A full publication list is maintained separately. Please contact us for preprints or dataset access requests.

Basnyat, B., Roy, N., Chugh, S. et al. (2025). "AI-Enabled Adaptive Wildlife Deterrence for Smallholder Farms: A Field Evaluation Framework." Proceedings of the ACM International Conference on Embedded Networked Sensor Systems (SenSys). [Under review]

Roy, N., Gallo, T., Ravi, A. (2024). "Federated Acoustic Monitoring Networks for Urban Biodiversity: Privacy-Preserving Species Classification at the Edge." IEEE Transactions on Mobile Computing. [Preprint available]

Basnyat, B., Dave, P., Haravu Pradeep, K. (2024). "CropGuard: Multi-Scale IoT Sensing for Rapid Agricultural Damage Assessment Following Extreme Weather Events." AgriTech Research. Vol. 12, pp. 44–61.

AI SENSE Wildlife Dataset v1.2 (2025). Annotated camera-trap imagery from Maryland farmland, 14 species, 38,000 frames. DOI: 10.xxxx/aisense-wildlife-2025. [Access on request]

Contact for Research Enquiries

For research collaborations, joint grants, dataset requests, or invited talks:

Email: [email protected]

PI: Dr. Nirmalya Roy, COO — [email protected]

Address: AI SENSE USA, Baltimore, MD 21250

We aim to respond to all research enquiries within 3–5 business days.