Connecting Runners, One Stride at a Time
Revolutionising running experiences by combining users' personal running goals with social connections, to enhance motivation, build lasting friendships and encourage an active lifestyles. This project is in collaboration with four diverse and talented creatives. My contributions throughout the end-to-end Human Centered Design project focused on reimagining runners experience. Together, we developed an innovative solution that integrates user insights with thoughtful design, resulting in features that create a sense of community and personal growth for runner.
As the UX Designer, I transformed user insights into intuitive interactions, enhancing motivation, engagement, and community in the running experience. Through research, prototyping, and testing, I designed solutions that seamlessly balance personal goals with social connection.
While many runners seek companionship to boost motivation and enjoyment, finding the right running partner can be a challenge. Logistical barriers, such as scheduling conflicts and pace differences, often prevent meaningful connections. Additionally, compatibility extends beyond running ability—interpersonal factors like conversation styles and shared interests also play a crucial role. We aim to break logistical and compatibility barriers, making social running more seamless and fulfilling.
A social behaviour theory, Self-Determination Theory, suggests that intrinsic (e.g., personal progress) and extrinsic motivation (e.g., social connection) influence engagement by fulfilling psychological needs for autonomy, competence, and relatedness.
Image of key challenges for Asha, highlighting time constraints, environmental impact, limited culinary variety, and insufficient food management as core issues to address in the project.
This project applied the double diamond approach, everage human-centered practices to create a solution for social runners to find companions.
Image of the design thinking approach for Asha, outlining the process from empathising through research, defining insights, ideating solutions, prototyping, testing, and finally evolving through algorithmic solutions.
Enable users to discover nearby group runs, tailored to their preferences with customizable filters.
Highlighted that runs are displayed within a 5-mile radius, refined filter designs based on insights from A/B testing.
Conversation levels are defined clearly and socialization opportunities available during and before/after runs.
Designed to be welcoming, intuitive, and mission-driven, guiding users toward sustainable food choices effortlessly.
Seamlessly connects users with personalised recipes, pantry tracking, and meal planning for a more sustainable approach to food management.
The recipe generator empowers users to create personalised meals based on their cravings, dietary needs and on-hand pantry ingredients.
The page provides an interactive cooking experience, integrating sustainability insights and ingredient flexibility.
Enable users to upload FASTQ files (DNA sequencing text based files) to initiate fusion detection directly from the home screen.
Users can filter and sort through files and create folders to organize the data for more streamlines upload-to-results pipeline with realtime updates and clear progress.
Allow users to customize key analysis parameters prior to running the pipeline.
Parameters are clearly labeled with helpful default values to support novice users, while advanced users can fine-tune settings to fit specific research needs.
Provide users with real-time visibility into each stage of the fusion detection pipeline through a clearly segmented progress tracker.
Each module, from read alignment to fusion calling, is labeled and dynamically updated as steps complete.
Display fusion detection results in a concise, user-friendly table immediately after analysis completion.
Designed to support quick interpretation and downstream decision-making, with the ability to scroll, review, and export data for further analysis.
Enable users to configure essential app settings such as file storage location, cache management, and update preferences.
Users can change default settings of parameters in the settings to personalize the fusion detections settings based on their needs.
Allow users to personalize their profiles to share content on profile based on privacy preferences.
Agency to expand their network by connecting with compatible runners through friend requests.
Empower users to design runs by setting location, pace, and distance while fostering community through nearby runner participation.
Enhanced customisation options for greater control, including socialisation preferences and granular interest matching. Added seamless run-sharing across social media.
Keep a track of all runs—upcoming, hosted, and saved for later—organised in one place, along with related notifications like join requests, their statuses, and friend requests.
Updates were informed by user insights to align seamlessly with the overall experience and ensure consistency throughout the app.
Enable users to set running and social preferences like pace, experience, and interests.
Added a product overview with engaging wording and playful icons.
Introduced onboarding questions for personalisation and an app walkthrough for seamless navigation.
Overall, we conducted 4 competitive analyses, 25 survey responses, and 4 interviews to explore user needs in running apps. Key insights highlight motivation, social connections, and safety concerns, with a competitive analysis of Strava, Nike Run Club, Peloton, and Meetup.
Infographic showing how expert interviews, feedback sessions, and usability tests led to four design goals: improved navigation, clearer workflow, better result interpretation, and a cohesive design system.
We defined two personas, Primary and Secondary
A comparison of the current (first image) and revised (second image) Nanopore App flows, showing a shift from linear navigation to a more organized, expert-informed layout with improved sorting, navigation, and tab structure.
The ideation session explored key running companion app features, including companion recommendations, safety, meetup spots, search filters, and community engagement, using paper sketches to map user needs and interactions.
A stakeholder map for BioDepot Workflow Builder (Bwb) showing concentric layers of end users, direct and indirect stakeholders.
The information architecture organises the app into five main sections - Onboarding, Explore Runs, Create Run, My Runs, and Profile—each with clear sub-functions, allowing users to seamlessly set preferences, find and host runs, track their own runs, and manage their profiles.
A journey map outlining user steps, pain points, and design opportunities in the Nanopore app workflow. Starting from launching the app to editing workflows.
Image of usability testing and prototypes for Nanopore, showcasing home, parameters, progress and results screens, focusing on usability of legacy and revised versions.
Creating this design system ensured consistency and efficiency by defining typography, colours, icons, and components. This streamlined framework enables faster iteration, better accessibility, and a cohesive user experience, making the interface intuitive and polished.
Image of a design system, including logotypes, colours, typography, icons, UI components, and customised elements, ensuring consistency and scalability of Nanopore.
To evaluate the effectiveness of our running app prototype, we conducted usability tests with four participants across key features: onboarding, profile setup, exploring runs, and creating runs. Our findings highlighted areas for improvement in clarity, customization, and user expectations, which guided iterative design refinements to enhance the overall experience.
Images of usability testing findings for a recipe app, highlighting user feedback on meal selection, onboarding, pantry organization, and home screen improvements.
The image shows Python code for constructing a CNN model using TensorFlow and Keras, featuring convolutional, max pooling, flatten, and dense layers, compiled with the Adam optimiser and categorical crossentropy loss.
Working on SynQ provided valuable insights into designing for social running experiences. Here are my key takeaways:
