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School of Electronic Engineering and Computer Science

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  1. School of Electronic Engineering and Computer Science
  2. Postgraduate
  3. Why choose us
  4. Academic profiles
  5. Dr Juntao Yu

Dr Juntao Yu

What is it about Natural Language Processing that you enjoy so much?  

Language is at the centre of communication and natural language processing (NLP) is the task of processing and ultimately understanding human language. It is fascinating to see how language can be processed computationally and used to develop useful applications with real-world impact. In this era of AI, NLP is increasingly relevant to our daily lives, with applications ranging from chatbots and machine translation to clinical decision support systems. I find it incredibly enjoyable to witness the progress of NLP and to understand the mechanisms behind its advancements. 

Why do you think this module is critical for students to learn? What will they gain from it?  

AI is driving a new industrial revolution, with applications being used everywhere to improve efficiency and enhance our lives. NLP is at the centre of this revolution and students who study various NLP-related modules (including this one) offered by the university can prepare themselves to embrace the changes brought about by AI. This preparation will equip them for a world where AI is integrated into everyday life. Through this module, they will gain essential knowledge and hands-on experience in various NLP tasks such as sentiment analysis, text classification, and language generation. These skills will undoubtedly enhance their employability and future career prospects. 

How would you describe your teaching style?  

I would describe my teaching style as practical. When I teach this module, I strive to go beyond the textbook by introducing students to the link between different NLP topics and their link to real-world applications. By doing so, students gain a deeper understanding of the practical implications of NLP and are encouraged to think creatively about how these technologies can be applied in diverse settings. 

What components of the module would be transferable to the industry students end up in?  

NLP has a wide range of applications across most industries. Take named entity recognition (NER) as an example. This task, which involves recognising and categorising entities in context, is used by: 

  • Financial companies to navigate news and inform stock trading decisions. 
  • Search engines to improve the relevance of search results. 
  • Banks to augment anti-money laundering investigations. 
  • Hospitals to process electronic health records. 
  • Drug companies to identify adverse drug reactions. 

This is just one example, and students will learn about many other NLP techniques with similarly diverse applications. Therefore, regardless of their chosen industry, students will benefit from the knowledge and skills gained in this module.  

What advice do you have for students considering a degree in Data Science/Machine Learning? 

Choosing a degree in Data Science or AI at QMUL is an excellent decision! Be prepared to work hard, as you will learn a great deal from the program. Whether you plan to pursue a PhD or enter the workforce, this degree will equip you with the necessary skills and knowledge to achieve your goals. To make the most of your studies, I recommend choosing a theme or area that genuinely interests you. This will motivate you to engage deeply with the modules and select a final project that aligns with your passions. By focusing on a topic you enjoy, you'll be more likely to excel in your studies and achieve a fulfilling outcome. 

What has been the highlight of your time at EECS?  

Although I only began my lectureship at EECS less than two years ago, I previously spent five years here as a postdoctoral researcher. I have thoroughly enjoyed my time at EECS and feel fortunate to have returned as a lecturer, where I continue to work with a group of incredibly supportive colleagues. Looking back on my time at EECS, I never imagined that I would one day stand in front of hundreds of students to teach a course. However, with the unwavering support I received from the EECS community, especially my former line manager and now mentor, Professor Massimo, I have been able to achieve this and more. I am deeply grateful for the opportunities and encouragement I have received throughout my time here. 

 

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