Linky

September 2024 - Ongoing

Overview

Eliminating 180,000 plastic bottles yearly with a UV-sanitized, accessible drinking fountains for Abu Dhabi’s Corniche.

Role

Lead Product Designer

Timeline

March 2021 - May 2021

Tools

Nomad Sculpt, Fusion 360, Rhino 3D, Adobe Illustrator, KeyShot

Teammates

Mechanical Engineers ②
Business Strategists ③
Product Manager ①
Architect ①

The Problem

Abu Dhabi’s Corniche hosts thousands of daily visitors—walkers, joggers, cyclists, and families. Yet, the absence of safe, inclusive drinking fountains forces reliance on bottled water, contributing to waste and excluding wheelchair users. Traditional fountains often go unused due to hygiene concerns and outdated design.

Results and Impact

Delivered to the UAE Ministry of Urban Planning, we designed a UV-sanitized, foot-pedal fountain for Abu Dhabi’s Corniche. Fully accessible and solar-powered, the design inspired plans to install public fountains along the Corniche—offering a scalable solution to eliminate 180,000 plastic bottles annually.

RESEARCH QUESTION:

Why are Abu Dhabi residents less inclined to use public outdoor drinking fountains?

FINAL DESIGN & REFLECTIONS
Innovative nozzle sanitation system

Full accessible fountain design

The final design is a fully self-sanitizing, hands-free public drinking fountain created specifically for Abu Dhabi’s Corniche—accessible, sustainable, and grounded in local visual language. With its dual-height sinks, foot-pedal activation, and solar-powered UV sanitation, it offers a safer, more inclusive alternative to bottled water in one of the city’s most visited public spaces.

The design was presented to the UAE Ministry of Urban Planning, where it contributed to early-stage efforts to reintroduce drinking fountains in Abu Dhabi. Our proposal helped shape conversations around sustainable urban hydration and influenced plans to bring more accessible water infrastructure to the Corniche.

I'm incredibly proud of what we achieved—not just as a functional product, but as a rethinking of how public design can serve health, sustainability, and equity all at once.

Massive thanks to Eunseo Bong, Samantha Lau, and Zak Saeed for being thoughtful, talented, and tireless collaborators throughout the process.

Overview

Designed an AI networking application that reduces contact management time by 70%, with 3x follow-up efficiency.

Role

Lead Product Designer

Timeline

Ongoing (Prototype completed)

Tools

Figma, Webflow, Python, BeautifulSoup, Selenium, OpenAI API, ZeroWidth LLM, Google Sheets, Notion, Miro, Draw.io, Lucidchart, Postman

Teammates

Software Engineers ②
AI/ML Engineers ②
Business Strategists ③
Product Manager ①

The Problem

Professionals often collect contacts through events, LinkedIn, or referrals, but struggle to keep them organized, remember context, and follow up in a timely way—existing tools store information but don’t support strategic, actionable networking.

Results and Impact

We designed and built an AI-powered tool that helps users collect, organize, and follow up with contacts more efficiently, turning scattered information into clear next steps—creating a 70% reduction in manual effort and a 3x increase in follow-up effectiveness.

   Opportunities Addressed
Linky Features
Users meet people through various channels and need one unified way to capture their info
Multi-channel contact capture
Users often forget context or lack complete info after meeting someone
AI-powered profile enrichment
Users waste time organizing contacts manually
Automatic tagging & categorization
Users struggle to find contacts later due to vague memory or poor structure
Smart search (contextual + tag-based)
Users don’t know who to reach out to or when to follow up
AI-generated follow-up suggestions
Users feel unsure about how to reinitiate conversations meaningfully
Personalized outreach drafting
Users forget when and where they met someone and what was discussed
Contact timeline & notes
Users want networking to be strategic, not random
Goal-based contact prioritization
DESIGN AND TESTING
CORE USER JOURNEY

The user journey starts when a contact is captured—through a scan, tap, or manual entry—and Linky immediately enriches the profile with relevant context. From there, the user can easily search, tag, and organize connections without any manual sorting. As career goals evolve, Linky suggests who to follow up with and how, helping users move from collecting contacts to building meaningful, strategic relationships over time.

HOW DOES THE SYSTEM WORK?

The system begins when two users initiate a connection via any of the three modes available on the application. That request is sent to AWS, which relays the task to a central database server. The database interfaces with external APIs like LinkedIn, Twitter, and others to fetch relevant contact and contextual information. This enriched data is compiled and returned through AWS in a simplified, digestible format, which is then displayed on the user’s device for seamless, informed networking.

TESTING TECHNOLOGY

While developing the system, I focused on integrating AI with a custom social media scraping algorithm I developed to surface relevant connections. Using ZeroWidth, I tested how large language models could interpret user goals through prompt engineering, relevance scoring, and AI-generated messaging—creating a smarter, more personalized networking experience.

MID-FIDELITY WIREFRAME

I started with low-fidelity wireframes to lay out the core flows: capturing a contact, viewing enriched profiles, and receiving AI-driven follow-up suggestions. I focused on minimizing user effort—ensuring that adding a contact took no more than three taps and that smart recommendations felt accessible, not intrusive. These early wireframes helped test navigation logic, screen hierarchy, and how users might search or filter contacts before moving into more detailed visual and interaction design.

High-Fidelity wireframe
Home screen

Easily navigate between the applications core functionalities through a vibrant interactive elements.

SCAN ID CAMERA

Providing NFC, contact form andID OCR technology, Linky provides you with a one stop shop for however you want to network.

APPLE PAY INTERGRATION

Conveniently store your customized ID in your apple wallet for easy custom information sharing, supplementing existing apple information sharing mechanisms by provising more custom sharing options.

CHAT WITH LINKY (AI)

Powered by a custom scraping algorithm and ZeroWidth LLM, receive actionable recommendations for achieving your networking goals most efficiently.  

MANAGE CONTACTS

Using our "infinite tag" feature, find any contact you have made in the past through notes, emojis, tags, pictures, date, profession or event.

CUSTOMIZE YOUR ID

Customize both the information shared through your virtual ID as well as what your ID looks like to give you a dynamic experience.

VISUAL ARCHITECTURE
ITERATIONS AND TESTING
USER FEEDBACK

We ran usability tests using high-fidelity Figma prototypes with 186 users from our target audience. Each participant was asked to complete tasks such as capturing a new contact, searching for a past connection, and acting on an AI-generated follow-up suggestion. Key insights:

100%
Independent task completion
42%
Less task completion time
after UI refinement
60%
Search accuracy improvement
through auto-tagging
70%
Less netwoking
management time overall
REFLECTIONS

Building Linky has been one of the most rewarding challenges I’ve taken on. Designing a tool that turns something as messy and human as networking into a clear, strategic process forced me to balance technical feasibility with real-world needs. Working at the intersection of product design, AI, and systems thinking pushed me to grow quickly—and made every iteration feel meaningful.

I’m incredibly grateful to have worked alongside an ambitious and thoughtful team. Thank you to Jasmine Meziou, Javier Araiza, Koka Gugunava, Carmen Rodríguez, Facundo Kim, Patrick Jun, and Daniela Guerra for your insight, late nights, and commitment to making Linky real. Presenting our work at the UC Berkeley Haas School of Business as part of a startup incubator was a full-circle moment—it helped validate what we were building and reminded us of the impact this could have beyond the classroom.

As we continue developing Linky, we’re focused on:

1. Expanding AI recommendations with broader datasets

2. Integrating with CRM and calendar tools

3. Launching a public beta to gather deeper user feedback


Grateful for how far we’ve come, and excited about what’s ahead!

Overview

Designed a replicable model for low-tech migration for 300,000+ Tanzania–Burundi refugees with 92% success using geofencing.

Role

Product Designer, System Architect, Field Research Lead

Timeline

August 2022 - Ongoing

Tools

KoboToolbox, Garmin eTrex GPS, OpenStreetMap (OSM), QGIS, PostGIS, Twilio SMS API, RapidPro

Teammates

Community volunteers ③
Refugee informants ②
Humanitarian workers ②
Telecom SMS engineers ①

The Problem

Burundian refugees moving between Tanzania and Burundi often travel without maps, internet, or verified information—relying on word-of-mouth while navigating dangerous, unmarked routes. This reflects a broader global migration challenge: the absence of reliable, low-tech systems to communicate real-time safety along human migration paths.

Results and Impact

We built a geofencing-based SMS alert system for Burundian refugees moving between Tanzania and Burundi—achieving 92% delivery success on feature phones. It serves as a potential replicable model for low-tech, migration-focused communication systems globally.

CONTENT NOTE
Due to this project involving cross-border technology deployment between Tanzania and Burundi, detailed disclosures are currently limited. Mapping Nyumbani is undergoing formal regulatory review by relevant government bodies. As a result, this documentation does not include sensitive implementation details such as the names of contributing partners, telecom providers, or full architecture workflows. Specific field locations and humanitarian collaborator identities have also been withheld in accordance with compliance standards. That being said, let's dive in!
What I Did vs What We Did
Throughout this project, I led all aspects of system design, architectural planning, prototyping, visual mapping, and field implementation strategy. I also facilitated community co-design and restructured our engagement model for deeper cultural integration. The system architecture, zone logic, privacy model, and visual storytelling were developed by me with input and validation from a small interdisciplinary team: refugee participants, local humanitarian workers, telecom engineers, and volunteers embedded in the camps and remote volunteer researchers.


To maintain clarity in what follows:

"I did" = product design, system logic, mapping facilitation, testing leadership.

"
We did" = co-design of messages, zone refinement, translation, field validation, input from volunteers and engineers.
Defining the problem
JOURNEY MAP
Defining the problem
Problem statement
Refugees migrating between Burundi and Tanzania face life-threatening uncertainty, navigating volatile routes with no real-time safety guidance. Dependent on word-of-mouth in fast-changing environments, and cut off from digital tools due to limited connectivity and widespread feature phone use, they lack access to reliable information. Mapping Nyumbani seeks to solve this core problem: how might we deliver accurate, real-time route safety alerts using only the low-tech devices refugees already carry?
Understanding the System
70% of the East African refugees we interviewed own basic feature phones, not smartphones. These phones work over 2G SMS—no internet required. Refugees use them to get urgent information from family or aid groups, often without airtime. Mapping Nyumbani taps into this ubiquitous, low-cost infrastructure to deliver life-saving updates via SMS.
Scoping a Solution
SYSTEM FLOW DIAGRAM
I led the scoping process, translating insights from field research into a technically feasible system. This included selecting the architecture (feature phones, SMS-based geofencing), identifying integration options (Twilio, PostGIS), and validating compatibility with existing mobile networks. I designed the zone logic and built early system flow prototypes in Figma.
BUILDING COLLABORATIVELY
Contextualizing OUR framework
We invited refugees to co-design features and messaging, but early feedback was superficial. I realized participants lacked full visibility into the system’s purpose and assumptions. In response, we began sharing our own methodology—including mapping logic, design rationale, and constraints. This transformed the process: refugees began identifying not just surface-level changes but cultural gaps and deeper misalignments. They proposed workflow changes, rephrased alerts for clarity, and even influenced the structure of message logic. This mutual transparency led to stronger uptake and grounded the system in real community logic.
TESTING
Successful tests on no-internet feature phones entering remote geo-fenced areas
Successful tests on smart phones entering geo-fenced areas with internet access.
We tested 100+ SMS alerts across 15km routes of various internet and cell service consistencies using 10 feature and smart phones and various network providers and phone brands. 92% of messages were received within actionable time. Alerts will contribute to directly informing refugee movement behavior, helping them avoid danger zones and reach aid more confidently.
Reflections & next steps
Mapping Nyumbani gave me the opportunity to step beyond traditional design execution into strategic leadership and community-led innovation. Leading this project pushed me to consider how system thinking, ethics, and technology intersect in humanitarian contexts. A major turning point was realizing that early-stage co-design lacked meaningful insight—not because of disinterest, but because we had not opened up our own logic and process. Shifting to a more transparent model where we shared our rationale and invited critique created the conditions for real co-ownership. This experience continues to shape my approach to collaborative, community-informed design.

Currently, the project is undergoing cross-border regulatory review by Tanzanian and Burundian authorities. This phase has introduced a new layer of learning—how to ethically and legally manage inter-country data flows, telecom collaboration, and humanitarian system integration.

Once approved, we intend to revisit our framing for replication to include learnings from this process, specifically around regulatory compliance, sovereignty, and local control of technology-driven interventions.


Project Impact:
126,000+ Burundian refugees can benefit
50 alerts tested
92% delivered
30+ danger or support zones mapped
Pilot sparked policy conversations and NGO interest

Next Steps:
Secure telecom/government approval
Develop real-time location mapping and editing
Scale pilot geographically
Publish replication toolkit

Limitations & Ethics:
No personal data stored
Alerts depend on coverage
Risks mitigated via human verification
Clear opt-in

Read more about this project here:
Overview

Boosted AI Engagement by 75%, introduced 300+ users to Google’s Chimera Painter at the Mozilla Festival.

Role

AI Education Facilitator– User Research & Engagement Lead

Timeline

March 2021 — April 2021

Tools

Figma, Chimera Painter, Photoshop, Google Slides, Miro

Teammates

ML Engineer (Google AI)
Festival Participants (300+)
Creative Technologists

CONTEXT & OPPORTUNITY
Machine learning tools like Google AI’s Chimera Painter offer powerful creative potential—but their interfaces and workflows often alienate beginner artists and non-technical users. At Mozilla Festival 2021, we saw an opportunity to bridge this gap and make AI-assisted art more inviting, intuitive, and accessible to a wider creative audience.
Animated GIF
What I Did
I conducted targeted user research with beginner artists and game designers to uncover where the AI tool created confusion or creative block. Based on these insights, I developed 20+ custom sketches and modular sketching guides designed to align with how users naturally think and create. I facilitated live onboarding sessions at Mozilla Festival, gathered real-time feedback, and delivered usability insights back to the development team to support further refinement of the tool.
Outcome
75%
increase in engagement
+300
first-time users onboarded
20+
custom sketches created
>10
usability insights delivered
 to Google AI team
NOTE
Due to confidentiality agreements, I’m unable to share further project details publicly. However, you can find more insights at the below.
Image Gallery
Using an image imported to Chimera Painter or generated with the tools provided, an artist can iteratively construct or modify a creature outline and use the ML model to generate realistic looking surface textures. In the examples below, I demonstrate how this is done.
Learnings & Reflection
Working on Chimera Painter in such a compressed timeline—and with such a globally diverse audience—deepened my belief that accessibility in design isn't just about usability; it's about translation. I learned how to rapidly distill complex technologies like AI into visual languages that resonate with beginners, creatives, and non-technical minds.

It pushed me to design not just for clarity, but for curiosity—to invite users into experimentation rather than just guide them through functionality. Collaborating with Google AI and engaging 300+ users from around the world also reminded me how powerful design can be when it connects people across skill levels, languages, and tools—not by simplifying complexity, but by scaffolding exploration.

Most of all, I learned that designing for unfamiliar tools requires deep empathy, procedural creativity, and a readiness to adapt fast. This experience sharpened my ability to design systems that teach as they guide, and to center the user even when the system itself is unfamiliar, invisible, or unpredictable.