Vibhor Gupta and Jingqing Zhang

Vibhor Gupta has a breadth of experience in life sciences through his work in industry and academia over the last two decades. Prior to Pangaea, Vibhor started and built the European business for Quantum Secure, which was an enterprise software solutions provider headquartered in Silicon Valley and was successfully acquired by a global corporation in 2015. Following his work at Quantum Secure, Vibhor served as Senior Vice President of Commercial Strategy and Sales at Seven Bridges Genomics, which was founded at Harvard and provided a cloud based bioinformatics platform. Vibhor’s academic career focused on conducting molecular biology studies and building bioinformatics tools and machine learning models with epigenetic, genomic, transcriptomic and clinical trial data in the context of oncology and infectious diseases. Vibhor has access to an extensive global network in the Life Sciences industry and is regularly invited to speak at international conferences, government funded programs and investment summits.

Jingqing Zhang is the Head of AI at Pangaea Data Limited. He earned his PhD in Computing from Imperial College London in 2022, under the supervision of Prof. Yi-Ke Guo. His research interest is in Language Modelling, Natural Language Processing, Text Mining, Data Mining and Deep Learning, with an emphasis on their applications in healthcare. Jingqing is the founder and main contributor to popular deep learning tools, such as TensorLayer 2.0 and PEGASUS. His projects have received over 10,000 stars on GitHub and millions of downloads on HuggingFace. He was awarded National Scholarship of China (top 1%) in 2015.

Posts by Vibhor Gupta and Jingqing Zhang

Opinion
Health, wellness, doctor, AI

Prompting is Not Clinical Practice: The Limits Of General LLMs in Healthcare

General-purpose LLMs have meaningful value in healthcare - they can support education, documentation and research - as well as lower barriers to knowledge and help improve communication. But acting as a clinical assistant embedded in care delivery requires more - it needs longitudinal EHR grounding, explicit encoding of clinical guidelines, transparent and traceable reasoning and the ability to operate securely at a population scale.