Projects
Here, you’ll find a collection of diverse projects that reflect my experience across different areas.
These include process-improvement and system-modelling projects like Mercy Ships Australia’s inventory optimisation and SAP CRM workflow design, market and pricing analytics for The Leaf Protein Co.
I’ve also explored technical projects in Python, SQL, and C, which strengthened my ability to translate data into insights and practical solutions.
Each project combines technical tools with business problem-solving, showcasing how I approach real-world challenges through both analytical and creative thinking.
Role: Lead System Designer, UI Coordinator, Process Modeller
Project Context:
Mercy Ships Australia operates floating hospitals that deliver surgical care in developing countries. Their warehouse staff relied on Excel and Monday.com for expiry tracking of donated medical supplies which is a method vulnerable to human error, compliance risks, and life-threatening delays.
We designed SkyFlow, a scalable expiry alert prototype built for a low-tech, high-impact humanitarian environment. The system centered around QR code tracking, expiry flagging rules, and role-based interfaces for frontline and supervisory staff.
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​My Contribution:
I was the design and system logic lead across all major development stages:
Research & Ideation
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Participated in initial problem definition and client understanding
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Closely analysed pain points in manual tracking and information flow
System Design
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Led creation of all DFD (Data Flow Diagrams) and BPMN (Process Models), mapping the entire system logic for expiry monitoring and stakeholder actions
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Built UI wireframes with AI-assisted tools to validate system logic and simulate workflows
Team Coordination
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Directed and iterated user personas and system narratives based on logic consistency and client alignment
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Worked closely with one key team member to ensure my design outputs integrated smoothly into the final MVP
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Transitioned from documentation phase while remaining as logic consultant during handover
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Key Challenges & How I Responded
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Challenge 1 – Unclear project scope at the start
The team began with scattered ideas and no clear system direction, making it difficult to define priorities.
→ How I responded: I defined the system’s core around expiry alerts, built a clear logic structure, and guided the team towards a shared direction.
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Challenge 2 – Uneven team contribution
Core system work such as DFD, BPMN, and UI design fell solely on me, while other members focused on lighter tasks.
→ How I responded: I took full ownership of the key design outputs, but also coordinated closely with one teammate to ensure smooth integration.
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Challenge 3 – Frequent client feedback changes
The client’s requirements shifted often, requiring quick turnaround and repeated re-alignment.
→ How I responded: I adopted an agile approach, iterating rapidly based on feedback while balancing delivery speed with design consistency.
Mercy Ships Switzerland, 2021
Mercy Ships Warehouse Management System login UI
Role: Lead Analyst, Project Coordinator
Project Context:
Mister Mega Muscle (MMM) is a boutique gym facing operational inefficiencies, fragmented membership management, and missed opportunities to monetise online influence. Our team designed a digital transformation strategy centred on implementing a CRM system, a booking & scheduling platform, and a digital content platform. The strategy aimed to improve customer engagement, optimise class utilisation, and establish hybrid revenue streams.
My Contribution:
I played a leading role in clarifying direction, delivering core analysis, and ensuring overall project quality across major stages:
Research & Direction Setting
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Took the initiative to clarify requirements with the tutor, aligning the team on a unified project scope.
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Translated client needs into structured deliverables to guide analysis and system design.
Process Analysis & System Design
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Led the Core Affected Business Processes section, modelling lead-to-cash, member retention, and marketing workflows.
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Produced BPMN and DFD diagrams to illustrate system logic and efficiency gains from CRM adoption.
Team Coordination
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Reallocated tasks to balance uneven workload and ensure critical sections were covered.
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Worked with core contributors to integrate outputs into a cohesive final report.
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Key Challenges & How I Responded
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Challenge 1 – Conflicting directions at project start
The team had different interpretations of client needs, risking wasted effort.
→ How I responded: I engaged the tutor with detailed questions to confirm scope and priorities, then guided the team to align on an agreed direction.
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Challenge 2 – Inaccurate deliverables and uneven workload
A teammate submitted AI-generated diagrams that did not meet BPMN/DFD standards, while others focused on easier parts, leaving heavier analysis to fewer members.
→ How I responded: I reworked the critical section with accurate diagrams and analysis, and coordinated workload redistribution based on team members’ strengths to ensure balanced contributions and consistent quality.
Image created by ChatGPT
Role: Data Analyst, Client Liaison
Project Context
The Leaf Protein Company is an Australian start-up producing sustainable, plant-based protein from leafy biomass. Their flagship product, Nüleaf Protein® – Complete, is a multifunctional “green protein” with a high-quality amino acid profile and bioavailability (PDCAAS 0.91), designed as a B2B ingredient for supplements, health foods, and beverages . Our consulting project focused on analysing the Australian green powder supplement market and identifying strategic positioning opportunities for this innovative protein ingredient.
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My Contribution:
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Data preparation & EDA: Cleaned and standardised competitor dataset (87 products) in Excel; applied descriptive statistics, distribution analysis, and visualisations to reveal price bands, pack sizes, and flavour trends.
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Insight generation: Identified that most green powders underplay protein quality and amino acid completeness, framing this as a key differentiator for Nüleaf Protein®.
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Client engagement & validation: Clarified with the startup what insights were most valuable; final EDA was praised by the client as “ready for them to use.”
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Key Challenges & How I Responded
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Challenge 1 – Raw, unstructured competitor dataset
The startup had no internal data, and competitor information was manually gathered by teammates. The dataset was inconsistent in variables such as price, pack size, and flavour.
→ How I responded: Cleaned and standardised 87 entries in Excel, then ran descriptive statistics and visualisations (histograms, boxplots) to extract meaningful insights on price bands, pack sizes, and flavour gaps.
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Challenge 2 – Aligning technical analysis with client needs
As a startup, the client needed clear, actionable insights rather than raw numbers.
→ How I responded: Translated EDA results into business implications (e.g., protein quality as differentiator, dual-size packaging strategy), and proactively clarified expectations with the client. The final EDA was praised as “ready for them to use.”
Role: CTO
Project Context
With 90% of payment fraud in Australia linked to Card-Not-Present transactions, our team proposed FastBio Pay, a conceptual biometric mobile payment solution. The aim was to explore how multimodal biometrics (face, voice, fingerprint, finger-vein) could reduce fraud risk and strengthen digital identity verification.
My Contribution
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Architected the proposed system design and selected biometric modalities to balance usability and fraud prevention.
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Designed the finger-vein authentication module concept, leveraging NIR imaging, Gabor filtering, and machine learning classifiers.
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Coordinated with cross-functional teammates to align solution design with regulatory, financial, and operational requirements.
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Design & Risk Controls
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Privacy & Security: Proposed end-to-end encryption and cloud storage compliant with Australian privacy standards.
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Anti-Spoofing: Integrated subcutaneous biometric scanning (finger-vein) and anti-replication logic.
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Regulatory & Controls: Ensured alignment with ASIC/ACCC frameworks; introduced fraud detection triggers and audit-readiness monitoring.
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Key Challenges & How I Responded
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Challenge 1 – Balancing security with user experience
→ How I responded: Proposed multimodal biometrics, offering flexibility for users while strengthening fraud prevention.
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Challenge 2 – Regulatory and technical feasibility in a startup context
→ How I responded: Scoped compliance requirements and sandbox testing approach to validate the concept before real-world rollout.
Role: Analyst
Project Context
As part of a team, we assessed Woolworths Group Limited (ASX: WOW), one of Australia’s largest retail companies, to evaluate its market valuation and investment potential amid post-pandemic economic recovery and fluctuating retail dynamics. The project combined strategic, sustainability, and financial analysis to inform an investment recommendation.
My Contribution
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Focused on financial modelling, contributing to the Discounted Free Cash Flow to Equity (DFCF) model in Excel, including assumptions on revenue growth, discount rates, and sensitivity testing.
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Helped synthesise findings into the team’s final investment recommendation by integrating my financial outputs with broader strategic insights.
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Analysis & Findings (Team)
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Market Potential: Identified moderate growth opportunities driven by sustainability initiatives, digital expansion, and loyalty programs.
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Financial Valuation: Team estimated Woolworths’ intrinsic share price at AUD 40.99, marginally higher than the current market price of AUD 39.03.
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Investment Strategy: Recommended a “BUY” strategy based on valuation results and risk assessment.
Key Challenges & How I Responded
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Challenge 1 – Volatile retail sector with post-COVID uncertainty
→ How I responded: Focused on testing assumptions within the DFCF model using scenario and sensitivity analysis.
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Challenge 2 – Connecting financial outputs with strategic analysis
→ How I responded: Collaborated with teammates from the strategy stream to ensure the valuation aligned with sustainability and market positioning insights.
• Problem: Developed a 2D tower defense game simulation in C, focusing on optimizing enemy pathfinding, tower placement, and game-state updates for maps of up to 6 rows and 12 columns.
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• Solution: Utilized C structs and 2D arrays to represent game elements, including land types, entities, and enemy movements. Implemented logic for enemy spawning, path creation, and tower interactions, ensuring efficient gameplay mechanics.
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• Optimization: Enhanced memory management and streamlined enemy movement algorithms, improving processing efficiency for smooth gameplay.
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• Validation: Applied iterative testing and debugging techniques to ensure accurate gameplay mechanics and correct handling of complex scenarios, including enemy waves, tower upgrades, and environmental flooding.
University of New South Wales. (2023). Assignment illustration for COMP1511. UNSW WebCMS3.
• Problem: Developed a Python program to accurately convert between Arabic and Roman numerals, including generalized numeral systems, while ensuring precise input validation and conversion accuracy.
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• Solution: Implemented a comprehensive solution utilizing procedural programming, string manipulation, and arithmetic computations to handle various user inputs. The program accurately converted standard Roman numerals, generalized numeral systems, and determined minimal representations for complex numeral inputs.
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• Optimization: Optimized the algorithm to ensure reliable execution within 30 seconds for each test case, efficiently handling edge cases and large numeral values.
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• Validation: Successfully passed 55 test cases, ensuring accurate responses for various numeral conversions and
enhancing program robustness.
• Problem: Faced the challenge of optimizing complex data retrieval processes from the MyMyUNSW relational database for academic progression and enrollment tracking.
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• Solution: Developed 10 advanced SQL views and PL/pgSQL functions to process complex queries, including course ranking, program completion analysis, and weighted average mark (WAM) calculations, ensuring all queries executed within 60 seconds.
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• Optimization: Enhanced query structures to improve data retrieval efficiency for large datasets, significantly reducing processing time while maintaining accuracy.
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• Validation: Conducted rigorous testing using auto-check scripts to ensure compliance with project specifications, enhancing data consistency and reliability across multiple test cases.
University of New South Wales. (2024). Assignment illustration for COMP9311. UNSW WebCMS3.