UBFalcons Racing is the University of Birmingham Dubai Formula Student team. I founded it in August 2025 and lead it as Team Principal and CEO. The team is entering Formula Student UK in the AI class for the 2026 to 2027 season, working with our Birmingham sister team, UBRacing UK.
What I did
Built the team from inception into a 40-member, competition-ready organisation across six subsystems: Chassis, Vehicle Dynamics, Powertrain, Aerodynamics, Electronics, and Finance and Media.
Recruited and interviewed members and appointed subsystem heads and a Technical Director based on skills and experience.
Led project planning and delivery across the season.
Owned budgeting and sponsorship.
Brought the technical and business teams together so performance goals line up with branding and partnerships.
Technical approach
Split ownership clearly: I run operations, sponsorship, branding, finance and university relations, and the Technical Director runs engineering design and integration.
Built a two-part budget: a car development budget (parts, materials, tools) and a logistics budget (registration, flights, accommodation, freight).
Planned in-kind sponsorship, where suppliers give parts in exchange for logo placement, to cut capital spending.
Produced the sponsor pack: a pitch deck in AED, GBP and USD, a sponsor progress summary and an internal progress report for university staff.
Created the UBFalcons identity: a falcon mark chosen for its UAE link, with logo, colours and livery.
Tools and skills
Project managementteam leadershiprecruitmentsponsorship and negotiationbudgetingbrand designstakeholder managementtechnical reporting
Outcome
A 40-member team, a full sponsorship pack and a campaign budget for the 2026 to 2027 Formula Student UK season.
What I learned
Running an engineering team means turning technical goals into budgets, schedules and people decisions.
Sponsors respond to clear structure and measurable outcomes.
Co-Founder2026 → Present
Krank AI
Founder
Krank AI · independent
Overview
Krank is an AI tool that evaluates engineering lab reports against real university marking rubrics. It gives students detailed technical feedback before they submit, covering units, equations, calculation accuracy and underlying theory, which general AI tools often miss.
What I did
Defined the product, collected sample lab reports to test against, learned the stack from scratch and built the working prototype.
Tested it across different lab report types, modules and marking rubrics to improve accuracy and reliability.
Technical approach
A student uploads a report and can add their own rubric.
Krank identifies the experiment type, key equations, expected units and underlying theory, and builds a technical checklist.
It evaluates each section against the rubric and checks that the analysis, calculations and theory are correct and consistent.
Feedback is tied directly to the student's own report, which prevents generic or hallucinated answers.
The output is an estimated grade, a summary of positive signals and key issues, specific improvement actions showing where marks are lost and the grade uplift if they are fixed, and a follow-up chat for questions such as how to improve the abstract.
Tools and skills
Next.js 14TypeScriptTailwind CSSClaude APIpdf-parseProduct designprompt engineeringAI evaluation and testingrubric-based assessmentfull-stack web development
Outcome
A working prototype.
Planned next modules: a CAD coach and project planning tools for engineers of all levels.
Research2026 → Present
Solar Power and Machine Learning
Researcher
UoB Dubai · ongoing
Overview
My final year research project at UoB Dubai: predictive fault diagnosis of solar PV panels using machine learning on laboratory I-V data. Solar panels lose output to shading, dust build-up and damaged cells, and in the UAE heat and dust make this common. Faults are often only noticed when yield drops over time. The project tests whether machine learning can read the changes a fault makes to a panel's I-V curve, spot it early, identify its type and estimate the power it costs.
What I did
Developed my own project proposal alongside the department's existing PV rig project, which predicts healthy panel output.
Mine asks a different question on the same rig: is the panel faulty, how badly, and what is it costing.
Defined the aim, objectives, methodology and risks, and agreed the direction with my supervisor, Dr Adel Abdelwahab.
Technical approach
Baseline testing: run the rig under normal conditions across different light levels and loads to record healthy behaviour, and train a model that predicts expected output.
Fault testing: introduce safe, repeatable faults at increasing severity, such as partial shading with covers and a thin layer of dust, and record the full I-V response.
Data analysis: extract key values from each test, including maximum power, short-circuit current and open-circuit voltage, as model inputs.
Modelling: anomaly detection from the gap between measured and predicted output, then classification of fault type and regression for severity and power loss.
Start with simple models such as linear regression and decision trees, then try more advanced ones.
Validation: split the data into training and testing sets, check accuracy on unseen cases, and compare model predictions with a standard physics-based PV model.
Tools and skills
Python (pandas, scikit-learn) for data processing and machine learningwith MATLAB alongside it for the physics-based PV model where it fitsAnomaly detectionclassificationregressionexperimental designdata acquisitiontechnical reporting
Outcome
Planned deliverables: a labelled dataset of healthy and faulty panel tests, trained models with code, a comparison of model accuracy, a simple tool that flags likely faults from test data, and a preliminary report, poster and final report.
The project is in progress.
LeadershipAug 2026 → Present
Sports Strategy Society
Secretary
Sports Strategy Society · UoB Dubai, ongoing
Overview
A student society for sports strategy at UoB Dubai.
What I did
Plan and run society events.
Manage admin and communications.
Handle planning, strategy and finances.
Presented the Transfer 101 workshop, which explains football transfers from the club's perspective.
A pro bono consulting engagement through the 180 Degrees Consulting chapter at UoB Dubai. The client is Dream League, an adaptive sports organisation in Dubai that teaches roller skating, alpine skiing and climbing to children with autism, Down syndrome, ADHD, cerebral palsy and other developmental differences. It has run in the UAE since 2022 and is a Certified Autism Center and a SPIA Silver winner for Best Sports Inclusion Initiative in MENA.
What I did
Consultant in a team of four.
Researched and analysed the client's situation and helped develop the strategy and recommendations.
Technical approach
The problem is not awareness but discoverability and trust.
Paid advertising on Google and Meta produced traffic but few paying clients, because choosing an activity for a child with special needs is a personal decision built on trust.
The work focuses on the path that does convert: a parent searches, finds Dream League, checks its credibility, and books a trial.
The analysis covers a website audit, competitor and alternative supply mapping, and four workstreams: Google search and website structure, AI search and third-party presence, a referral and partnership engine, and messaging and trial conversion.
The plan runs in three phases: diagnose, design, deliver, with a 90-day roadmap and KPIs the client can track.
Tools and skills
Consulting frameworkswebsite and SEO auditcompetitor analysiscustomer journey mappingstakeholder interviewsproject planningclient communication
Outcome
In progress.
Engineering2026
Steam Train CFD Optimisation
Analyst
UoB Dubai
Overview
A group CFD project at UoB Dubai that redesigns the LNER A3 steam locomotive, the Flying Scotsman, to reduce drag and improve driver visibility, and compares each redesign against Nigel Gresley's 1930s streamlining of the A4 class. The A4 Mallard set the steam speed record in 1938, which is still unbeaten.
What I did
Part of a five-person group, with each member developing a different redesign from a shared base model.
The redesign concepts are a full streamlined A4-style casing, a rounded smokebox nose cone, smoke deflectors in different sizes and shapes, wheel valances, and a cab-to-tender fairing.
Technical approach
Two metrics are reported for every redesign: drag on the locomotive and tender, and smoke concentration at the cab windows as a measure of driver visibility.
Smoke is tracked as a cold passive tracer using species transport, a modelling technique with little modern research on steam locomotives.
Setup uses steady, incompressible flow with the k-omega SST turbulence model, a half model with a symmetry plane, a moving ground and simple rails.
The wheels, valve gear and pipework are simplified into basic shapes, and all variants are built from the same base CAD so the mesh and settings stay consistent.
Validation uses reference aerodynamic train data and a mesh convergence check.
The deliverables are a technical report and a video presentation.
Engineering2026
Gear Transmission Design
Designer
UoB Dubai
Overview
A design project at UoB Dubai: an automotive-style gearbox with several selectable ratios, designed and documented as a full engineering package.
What I did
Design the gear transmission in Fusion 360, from the individual components to the full general assembly.
Produce the engineering drawings and write a design validation report and an assembly report.
Technical approach
The work covers selecting the ratios across the gear stages, sizing the gears, shafts and bearings, and checking the design against the loads it must carry.
The model is built as a parametric assembly in Fusion 360 and documented with part drawings, an assembly drawing and a general assembly drawing.
Tools and skills
Fusion 360mechanical designgear and shaft designengineering drawingsdesign validationtechnical reporting
Outcome
In progress.
Engineering2026
FEA Structural Analysis
Analyst
UoB Dubai
Overview
A finite element analysis assignment at UoB Dubai, applying structural simulation to real design problems.
EngineeringJun — Aug 2026
AI Development & Thermal Design Engineer
AI Integration Engineer
Dolphin Manufacturing · Ajman
Overview
Dolphin Manufacturing is a UAE heat exchanger and radiator core manufacturer headquartered in Ajman. I worked as the technical bridge between Dolphin R&D and the SimScale developers on an AI-powered RFQ system that automates parameter extraction and heat exchanger core selection.
What I did
Learned a 57-page product catalogue covering more than 100 aluminium and copper-brass core configurations across radiator, charge air cooler and oil cooler families, which became the knowledge base for the whole AI programme.
Wrote the core selection logic framework, a 9-step process covering parameter extraction, thermal sizing, fin and material defaults and edge cases.
Evaluated 20 real RFQs of increasing complexity, including multi-circuit generator radiators and FPSO lube oil coolers, and turned them into structured documentation used to train the AI models.
Validated the AI's extraction against the source engineering documents and raised formal change requests with the developers.
Ran a gap analysis of the core selection API and proposed new sub-steps.
Built the Dolphin Core Advisor web app as a prototype.
Presented progress weekly to a 20-person review group across Sales, R&D, IT and executive leadership.
Technical approach
Compared extracted values with source documents and classified each error by type.
Checked the handling of operating conditions, core geometry, heat dissipation, fouling factor, TEMA defaults, allowable against predicted pressure drop, and design margin against safety factor.
Grouped recurring faults, such as null heat dissipation outputs, value classification into input, estimated and calculated, dual-circuit separation, and replacement or re-core identification, and wrote each as a standalone change request.
Tools and skills
AI system validationrequirements writingchange request managementheat exchanger thermal designAPI analysisrapid web app prototypingtechnical documentationexecutive communication
Outcome
A documented core selection process and a set of change requests, projected to automate a pipeline of more than 200 RFQs a year and remove manual calculation, CAD iteration, simulation, BOM generation and reporting.
What I learned
How to test an AI system against engineering ground truth, how to write defects so developers can act on them, and how thermal design rules become software logic.
BusinessFeb 2026 — May 2026
Sales & Outreach Intern
Sales and Outreach Intern
Jawaher Education
Overview
A sales and outreach role at Jawaher Education, an Arabic education company.
What I did
Ran outreach to prospective clients through LinkedIn, email and community channels.
Researched prospects, tracked leads and coordinated follow-ups.
Developed marketing and outreach materials for campaigns and group promotions, including university emails promoting a free online beginner workshop, "Speak Arabic, Build Confidence".
Tools and skills
Lead generationCRMemail copywritingcampaign materialsevent promotioncommunication
EngineeringOct — Dec 2024
Deputy Lead — Powertrain & Drivetrain
Deputy Lead, Powertrain and Drivetrain
UBRacing Dubai · Formula Student
Overview
Deputy lead of the Powertrain and Drivetrain subsystem at UBRacing Dubai, the Dubai campus Formula Student team.
What I did
Researched and compared powertrain and drivetrain options to support early design decisions.
Wrote technical reports for the wider team.
Tools and skills
Powertrain and drivetrain selectiontechnical researchstructured problem solvingtechnical reporting
Systems EngJan — May 2026
Future Ocean Habitat
Project Coordinator
UoB Dubai
Overview
A large-scale systems engineering project at UoB Dubai. The team turned a complex challenge brief into quantified requirements, system architectures and validated design pathways for a future ocean habitat.
What I did
Project Coordinator for a six-person multidisciplinary team.
Produced and coordinated an extensive engineering report of about 200 pages.
Managed technical interfaces, documentation control and project operations, keeping the work consistent, traceable and aligned with the assessment criteria.
Technical approach
Applied formal requirements management, functional decomposition and evidence-based design justification.
Built sustainability and life-cycle thinking into technical decisions, including material selection, energy flows and environmental impact at system level.
The work packages cover team roles, a RACI matrix, a Gantt plan, a master system block diagram, failure space and HAZOP analysis of the top ten hazards, an environmental safeguard statement, a UN SDG causal map, and a verification matrix that cross-checks every work package.
Tools and skills
Systems engineeringrequirements managementlife-cycle assessmentrisk and hazard analysisproject coordinationtechnical report writing
DesignOct — Dec 2025
UAV Engine Design
Project Lead
UoB Dubai
Overview
A multidisciplinary engineering project at UoB Dubai to design a UAV engine, taken from concept to final submission.
What I did
Led the project and held full responsibility for CAD and documentation.
Carried out the analytical calculations that justified the design choices.
Wrote the design validation report and prepared the CAM.
Delivered a complete design package: report, drawings, assembly and manufacturing plan.
A design, build and test project at UoB Dubai: a wooden truss structure.
What I did
Coordinated a small team and took responsibility for planning and the key design decisions, balancing theoretical analysis with practical manufacturing constraints.
Operations and Business Analysis Intern, Kaizen Paints, JAFZA
Kaizen Paints · JAFZA
Overview
A summer internship at Kaizen Paints in the corporate operations function.
What I did
Supported operations and HR with fringe benefits analysis and cost breakdowns in Excel.
Researched the company's facilities, machinery and competitors, covering production methods, equipment capability, operational efficiency and market position.
Presented the findings to supervisors and colleagues as clear, actionable insights.
