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01- A
FILM SERIES +
EVENT GRAPHICS
In partnership with Katra Film Series, brand identity for a new film series was developed.
01- A
FILM SERIES +
EVENT GRAPHICS
In partnership with Katra Film Series, brand identity for a new film series was developed.
01- A
FILM SERIES +
EVENT GRAPHICS
In partnership with Katra Film Series, brand identity for a new film series was developed.
FIELD TEST
FIELD LAB
DESIGN SYSTEM: AI + DIGITAL + PRODUCT + DATA
01 - A
GRASSROOTS
ENVIRONMENTAL REPORTING SYSTEM
In partnership with Brown University as a Masters of Design Engineering thesis, I developed an environmental reporting system focusing on methane and water pollution. Utilizing a "Citizen Science" methodology, the project combined digital and physical tools to empower community members to collect and share environmental data.
BROWN
UNIVERSITY
ENGINEERING
In the Engineering Department, I led interdisciplinary projects combining technical innovation with human-centered design. My research focused on scalable solutions for environmental challenges using and exploring emerging technologies and
community-focused design.
RHODE ISLAND
SCHOOL OF DESIGN INDUSTRIAL DESIGN
Partnering with RISD, I approached environmental issues through a design lens, integrating creative experimentation with community engagement. My work explored how artistic methods and human-centered design could drive innovative approaches.
YOUTH-LED SOCIAL & ENVIRONMENTAL JUSTICE ORGANIZATIONS
With the Power Shift Network, I supported grassroots climate justice initiatives by applying design strategies that elevated community voices. Centering equity and accessibility, my work focused on visual storytelling and systems thinking to amplify efforts addressing climate resilience.
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
01 - B
THE INITIAL FOCUS: METHANE POLLUTION
The project began as a response to methane pollution, a major driver of climate change. Drawing on new satellite-based detection tools, it focused on tracking emissions from industrial and agricultural sources. By pairing real-time data with community-led action, the project demonstrated how advanced technology and grassroots efforts can effectively address complex environmental challenges.
SOURCES OF METHANE POLLUTION
PHOTO CREDIT: ADOBE STOCK IMAGES
PHOTO CREDIT: ADOBE STOCK IMAGES
PHOTO CREDIT: ADOBE STOCK IMAGES
01 - C
EXTENDING THE FRAMWORK TO ENIVRONMENTAL CHALLENGES
The framework of the system in tracking methane emissions highlights its adaptability to other environmental concerns. Its flexible design allows it to be applied to pollutants such as water contaminants, air toxins, and soil degradation. By uniting advanced monitoring technology with community-driven action, the framework enables localized solutions while supporting global efforts in environmental health and sustainability.
PHOTO CREDIT: ADOBE STOCK IMAGES
WATER & AIR QUALITY MONITORING
Expanding on a scalable framework, the project incorporated water and air quality monitoring using sensors, AI analysis, and "citizen science". Community members were trained to track pollutants like particulate matter, heavy metals, and nitrates, enabling real-time data collection and advocacy. This approach empowered local action and informed policy using technology and grassroots engagement to drive meaningful environmental change.
BIODIVERSITY
LOSS
The project expanded to address biodiversity loss by integrating AI image recognition, acoustic sensors, and community observations to monitor wildlife and habitat health. Citizen scientists gathered local data, creating a feedback loop between grassroots efforts and scientific analysis. This empowered communities to advocate for conservation, restoration, and sustainable land use.
PUBLIC
HEALTH
The system was adapted to link environmental data with public health, combining sensor readings, citizen reports, and AI analysis. It identified pollution-related risks like respiratory issues and waterborne diseases, enabling communities to track hazards and advocate for targeted health interventions and policy change fostering proactive, data-informed responses to environmental health threats.
PHOTO CREDIT: ADOBE STOCK IMAGES
01 - D
DESIGNING FOR WIDESPREAD USE WITH NEW TOOLS & TECHNOLOGY
The system was built for broad adoption, using modular sensors, flexible AI, and an open data platform to ensure adaptability and low cost. This tech-forward design empowers communities to monitor local conditions, address evolving challenges, and connect to wider environmental networks in safe & legal ways.
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
MODULAR
SENSOR KITS
Designed for adaptability, the modular kits include easy-to-use, low-cost sensors for air, water, and biodiversity monitoring. Customizable to local needs, they empower communities, urban and rural alike, to collect
reliable data and participate in environmental stewardship without requiring technical expertise.
AI MODEL
FLEXIBILITY
The system’s scalable AI models adapt to diverse data types, air, water, biodiversity, and health metrics, allowing seamless integration and real-time insights. Tailored to regional needs, they evolve with emerging challenges, enhancing predictive accuracy for varied communities.
OPEN DATA
PLATFORM
The open data platform makes environmental data accessible and transparent to the public, policymakers, and researchers. Its open-source design fosters collaboration, innovation, and informed decision-making, empowering communities and promoting global cooperation.
PHOTO CREDIT: ADOBE STOCK IMAGES
01 - E
COMMUNITY-DRIVEN:
CITIZEN SCIENCE AS
AN UNIVERSAL METHOD
Central to the project is "citizen science", engaging communities in data collection and analysis to democratize environmental monitoring. This approach empowers diverse participants to contribute to research, raise awareness, and influence policy, fostering global collaboration and local ownership in addressing issues like pollution and biodiversity loss.
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
01 - F
COMMUNITY-DRIVEN:
ADVOCACY ALIGNMENT ACROSS ISSUES
The project bridges diverse grassroots groups by highlighting the interconnectedness of environmental and health challenges. It supports coalition-building that leverages local knowledge and collective action, enabling communities to address multiple issues simultaneously and influence policy through unified, cross-issue advocacy.
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
MULTIPLE ISSUES TO ADDRESS
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
01 - G
MARKET RESEARCH:
METHODOLOGY
FOR POLLUTION MONITORING DEVICES
The system’s development relied on market research using qualitative and quantitative methods, including expert interviews, user surveys, and trend analysis. Data analysis and pilot feedback collection enabled rapid iteration, resulting in a cost-effective, adaptable pollution monitoring solution.
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
HAND-HELD METHANE DEVICES
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
01 - H
ETHNOGRAPHIC RESEARCH:
ADVOCACY & ACTIVISM
Ethnographic research provided deep insights into local environmental advocacy by engaging communities, NGOs, and activists through observation, interviews, and focus groups. Using storytelling and mapping, it captured lived experiences to center affected voices, guiding the creation of community-driven solutions and strengthening collaboration between grassroots groups and technology.
ALTERNATIVE ECO-ACTIVISM GROUPS
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
01 - I
DATA COLLECTION:
BLENDING QUANTITATIVE & QUALITATIVE APPROACHES
The project combined quantitative data from sensors with qualitative insights from community interviews and observations. Spatial and thematic analyses integrated scientific measurements with local narratives, creating a comprehensive, actionable understanding of environmental challenges grounded in both data and lived experience.
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
SOCIALLY-DRIVEN QUALITATIVE APPROACHES
The project prioritized community experiences, especially from marginalized groups, to frame environmental issues beyond data, considering social, economic, and cultural contexts. Through interviews, focus groups, and participatory workshops, it captured diverse perspectives that informed scientifically sound and socially relevant interventions.
AI INTEGRATION + DATA ANALYTICS
APPROACH
AI and data analytics enhanced the project’s ability to process environmental data from sensors, satellite imagery, and community reports. ML / AI identified patterns, predicted pollution hotspots, and recommended interventions, enabling real-time insights and empowering communities with actionable information through intuitive visualizations.
DESIGN + PROTOTYPING METHODOLOGIES
The project employed digital prototyping tools to rapidly develop and refine. Continuous stakeholder feedback guided iterative improvements, ensuring the solutions were intuitive, effective, and user-friendly. This digital-first approach enabled seamless collaboration across design, engineering, and community teams throughout development.
PHOTO CREDIT: ADOBE STOCK IMAGES
SOLUTION
PROBLEM
DISCOVER
IDEATE
DEFINE
DELIVER
UX DESIGN
UX RESEARCH
UI DESIGN
Design
Engineering
Marketing
Design
Strategy
Funding
DISCOVER
This phase focuses on UX research to explore the problem space deeply. Methods like user interviews, observations, and data analysis are used to gather insights about user behaviors, needs, and pain points. The goal is to understand the context without assumptions and collect information to inform design.
DEFINE
During this phase, the research findings are synthesized to create a clear problem statement. UX design plays a key role by mapping user journeys, identifying pain points, and defining design opportunities. This focused understanding aligns the team and sets a clear direction for solution development.
DEVELOP
In these phases, ideas are generated and translated into UI designs and interactive prototypes. Through iterative testing and user feedback, the designs are refined to improve usability and effectiveness. This user-centered approach ensures the final product is both functional and engaging, ready for implementation.
PHOTO CREDIT: ADOBE STOCK
PHOTO CREDIT: BROWN UNIVERSITY
PHOTO CREDIT: BROWN UNIVERSITY
01 - J
THE SOLUTION:
DESIGN SYSTEM
A community-driven environmental monitoring system with modular sensors, a user-friendly app, and an open data platform. It offers real-time tracking, predictive analytics, and fosters collaboration between communities, advocates, and scientists to empower environmental action.
PORTABILITY
These lightweight, compact devices are easy to carry and deploy across diverse locations, from urban to remote areas, enabling community members to monitor pollution without complex setups. Their portability supports flexible, temporary monitoring of changing environmental conditions.
COST-EFFECTIVENESS
Designed to be affordable without compromising function, these devices make environmental monitoring accessible to communities and grassroots groups. Their low cost enables widespread adoption and large-scale data collection without financial barriers.
REAL-TIME DATA
The devices provide immediate pollution insights via mobile apps and dashboards, enabling communities and policymakers to respond quickly and make informed, data-driven decisions shaping smarter planning and public strategies.
COMING SOON...
01 - K
FIELD LAB
The Field Lab introduced color-coded paper strips for quick, low-cost water quality testing. Designed for ease of use, the strips detect pollutants like nitrates and phosphates, changing color when dipped in water. Users compare results to a chart for instant analysis. This simple tool empowers communities to identify contamination and respond swiftly, supporting widespread, on-site environmental monitoring.
COMING SOON...
ACCESSIBILITY
Designed for ease of use, the color-changing paper strips make water testing accessible to all, regardless of technical background. With no need for costly equipment or training, communities can independently monitor and report water quality, encouraging broader participation in environmental stewardship.
AFFORDABILITY
Paper testing strips offer a low-cost solution for water monitoring, making them ideal for widespread, community use, especially in underserved areas. Their affordability supports large-scale participation without financial barriers or strain on the grassroot organizations and communities.
ON-SITE RESULTS
The paper strips deliver immediate, easy-to-interpret results, allowing users to assess pollution levels directly on-site. This real-time feedback empowers individuals and communities to quickly evaluate environmental conditions, monitor changes over time, and take prompt, informed action when needed.
COMING SOON...
01 - L
WEBSITE
The website is a hub for the Environmental Reporting System, offering real-time data, AI chatbot support, and interactive tools. Users can upload sensor data, view water quality results, and track pollution trends. Visualizations and forums foster insight, collaboration, and community engagement.
COMING SOON...
DESKTOP WEBSITE
COMING SOON...
COMING SOON...
COMING SOON...
01 - M
CHATBOT AI
The AI-powered chatbot simplifies environmental reporting by guiding data entry, explaining sensor and water test results, and offering personalized pollution insights. It also provides educational resources and connects users to local advocacy groups, making complex data accessible and actionable for communities.
MOBILE CHATBOT
01 - N
COMMUNITY WORKSHOPS & PUBLIC TRAINING SESSIONS
Workshops and training sessions engage communities in using sensor kits, interpreting water tests, and navigating the reporting platform. Combining technical education with practical guidance, they empower participants of all skill levels to collect reliable data and support conservation. Often in partnership with local advocates, policymakers, and scientists, these sessions build skills, share knowledge, and foster networks for lasting environmental impact.
COMMUNITY WORKSHOPS
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
PHOTO CREDIT: ADOBE STOCK IMAGES
01 - O
FUTURE STAKEHOLDERS
The system’s success depends on engaging diverse stakeholders: local governments using data for policy, advocacy groups strengthening activism, educators incorporating monitoring into curricula, and sustainable corporations enhancing transparency. Tech developers also drive innovation in modularity and AI. Collaboration among these groups ensures ongoing growth, adoption, and shared commitment to environmental conservation.
PHOTO CREDIT: ARTIFICIAL INTELLIGENCE
GOVERNMENT +
POLICY MAKERS
Local, regional, and national agencies focused on environmental protection, urban planning, and public health can use the system’s real-time data to inform regulations, monitor compliance, and develop policies that reduce pollution and enhance community health.
COMMERCIAL & AGRICULTURAL
Businesses and farms can use the system to monitor environmental impacts, manage resources efficiently, and meet sustainability goals. This supports responsible practices, reduces pollution, and improves compliance with regulations while promoting eco-friendly operations.
ACADEMIC + TECH INNOVATORS
Universities, researchers, and tech developers support system refinement and expansion. They use the platform for data collection, studies, and improving technology, while industries leverage it for environmental monitoring and compliance.
PHOTO CREDIT: ADOBE STOCK IMAGES
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