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    This LSE student is solving life with statistics and AI

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    Haitao Tao from China is a BSc Mathematics, Statistics and Business student at London School of Economics and Political Science (LSE). Source: Haitao Tao

    Remember Dory from “Finding Nemo”? The lovable blue fish who is forgetful, easily distracted, and often off in her own world?

    While her quirks are endearing, they also mirror what many individuals with attention-deficit/hyperactivity disorder (ADHD) experience in real life.

    ADHD affects about 3.1% of adults worldwide, and in the US alone, one in nine children between the ages of three and 17 has been diagnosed with it.

    Some people with ADHD, like Bryan Chee from Singapore, report trouble with time management. Recognising their struggles, one statistics student from China developed a time management app to help.

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    When he was not busy with his studies, Tao travelled to the Netherlands and Spain. Source: Haitao Tao

    From numbers to AI

    When Haitao Tao began studying Mathematics, Statistics, and Business at the London School of Economics (LSE), his path appeared clear. Like many peers at this prestigious institution, finance, consulting, or trading seemed natural destinations.

    But sometimes the passion carries us far beyond the intended shore.

    “I was halfway through my degree when GPT-4o launched in May 2024,” Tao recalls, “Suddenly, AI wasn’t just academic theory or a toy anymore, it was reshaping the world in real-time. I found myself spending nights exploring this new frontier, wondering: what should I do to get involved in the upcoming new era?”

    LSE’s curriculum offered exactly what Tao needed to understand AI.

    His Machine Learning and Deep Learning courses provided mathematical foundations from neural networks to transformer architectures. “The professors didn’t just teach theory,” he explains. “We implemented algorithms from scratch using PyTorch, which gave me deep insights into how these systems actually function.”

    But understanding AI models was only part of the equation. Tao realised that to create useful applications, he needed to master the full stack. So he taught himself TypeScript online and web development, spending countless hours building interfaces and learning how to deploy models in real-world applications.

    “I started with small projects, trying to solve everyday problems,” he says. “Each project taught me something new, not just about coding, but about myself. I discovered I’m most alive when finding solutions, instead of dealing with financial statements.”

    This realisation would soon manifest in his first major creation, born from a simple yet universal frustration: the chaos of managing time as a busy student.

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    Even while busy with AI and statistics classes, Tao found time to build EasyDDL. The app uses visuals to help you understand and manage your time better. Source: Haitao Tao

    Learning through iteration

    Tao has always found it hard to manage and visualise time. Traditional to-do lists didn’t help. “You can only write your tasks; they don’t give you a clear visual of how time is actually used,” he says.

    It was this one problem that inspired his first major project: EasyDDL, an intuitive app designed to visualise time management.

    “As my very first project, it naturally had many shortcomings such as limited features, design challenges, and bugs I didn’t initially anticipate,” admits Tao.

    But he wasn’t deterred; in fact, Tao recognised a deeper lesson: true growth comes from iteration. Each challenge encountered wasn’t a setback, but an opportunity to learn and refine.

    “The process taught me more than the app itself,” Tao reflects. “Every problem solved was another step toward becoming a better builder.”

    Eventually, EasyDDL launched on the Apple App Store, a proud moment that validated his persistence through countless late nights and continuous improvement.

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    At LSE, Tao’s studies were mixed with AI and statistics, including machine learning, market research, finance, operations research, and more. Source: Haitao Tao

    No more fights over which restaurant to dine at

    Building on his experience with EasyDDL, which focused on software development, Tao tackled a more complex challenge for his final assignment in the Deep Learning course: a multilingual restaurant review analyser.

    For the programmers who get it, Tao fine-tuned a XLM-RoBERTa model on a specialised dataset of restaurant reviews.

    “The interesting part was seeing how a properly fine-tuned model could outperform much larger general-purpose models like Qwen2.5 7B on this specific task,” Tao shares.

    “It reinforced that understanding your problem domain deeply matters more than throwing bigger models at it.”

    In simple terms, he made deciding where to have your next meal with friends even easier with some generous tweaks in the data.

    Even better yet, what started as coursework evolved into something bigger. Namely, a submission for a hackathon and a First Class in the project.

    So, for those who are either struggling to decide where to eat or are interested in how to create an app to solve that problem, Tao has released the model on the open-source platform Hugging Face, making it accessible to others working on similar challenges.

    From working on school projects to tackling industry crisis

    As Tao developed AI projects, a global crisis unfolded in maritime shipping: new carbon regulations imposed by the European Union (EU) and International Maritime Organisation threatened shipping companies with crippling fines of millions annually.

    “Imagine facing penalties of one to two million dollars per vessel every year,” Tao explains. “Smaller shipping companies don’t have vast teams of consultants to manage this. For many, these regulations could spell financial failure.”

    In response, Tao teamed up with an expert in shaping maritime regulations to launch Vlos.ai.

    It is an AI-powered platform that helps shipping companies navigate decarbonisation compliance.

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    Vlos.ai keeps shipowners up to date with complex regulations, predicts emissions and financial risks, and provides cost-saving compliance strategies. Source: Haitao Tao

    From building a time management app to creating a restaurant recommender and even applying AI to help shipping companies, Tao’s journey as a statistics student has taken him far.

    Each project not only sharpened his technical skills but also deepened his understanding of how statistics, design, and innovation can solve real-world problems.

    These experiences didn’t just shape his professional path; they helped him grow personally, too.

    “I now fully realise I’ve always dreamed of being a builder and creator,” he says. “The iterative process of learning, building, refining, is what truly drives me.”

    Despite his success, Tao doesn’t see his journey as complete. In fact, every challenge he faces is just another step forward. For him, it’s all about staying curious and being open to what comes next.

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    Thanks to his strong foundation in AI and statistics, Tao’s all set for whatever the future brings. Source: Haitao Tao