Biography

Dr. Anandarup Mukherjee is a Senior Research Associate at the Institute for Manufacturing (IfM), University of Cambridge, specializing in industrial digitalization, IoT, and intelligent systems. With over 13 years of research experience, his expertise spans digital twin architectures, predictive analytics, and low-cost automation solutions for manufacturing and healthcare. He has played a key role in high-impact international research projects, including Digital Manufacturing on a Shoestring and Digital Hospitals, focusing on democratizing digital transformation for global manufacturing SMEs and healthcare ecosystems.

His research integrates digital twins, industrial IoT, machine learning, and low-cost sensing to develop scalable, interoperable, and economically viable digital solutions. A core focus of his work is untangling complex industrial information flows, mapping processes, digital solutions, information architectures, logistics, and supply chains to create structured and efficient digital adoption strategies. He takes a multi-layered approach to transformation, addressing both systems-level improvements (processes, workflows, automation) and information-level advancements (data intelligence, interoperability, and real-time analytics).

Dr. Mukherjee holds a Ph.D. in Computer Science and Engineering from IIT Kharagpur, where his thesis, “Offloading in UAV Networks,” explored optimizing data processing and communication efficiency in constrained aerial IoT environments. He also holds a Master’s and Bachelor’s degree in Electronics and Communication Engineering, providing a strong foundation in hardware-software co-design, communication networks, and embedded systems.

Actively shaping the future of digital connectivity, he serves as Vice Chair of IEEE P1954, leading standardization efforts for Self-Organizing Spectrum-Agile Unmanned Aerial Vehicle (UAV) Communications since February 2022. Since August 2020, he has also contributed as an Area Expert in IoT Communications and Interoperability for the IEEE ComSoc Special Interest Group (SIG) on IoT for e-Health.

Dr. Mukherjee is a Senior Member of IEEE and a Fellow of the Royal Statistical Society (RSS). He holds editorial positions as Editor for IET Digital Twins and Applications and Associate Editor for Springer Nature’s Peer-to-Peer Networking and Applications (PPNA). His contributions to research have been recognized in Elsevier’s Top 2% Scientists list, and he has authored over 70 peer-reviewed publications and two textbooks, with an h-index of 22 and an i-10 index of 34.

His accolades include the IEEE e-Health TC Best Paper Award (2022), the Gandhian Young Technological Innovation Award (2018), and multiple top-cited papers in IEEE Transactions on Parallel and Distributed Systems.

His work bridges the gap between cutting-edge research and real-world applications, making digital transformation more accessible, scalable, and impactful across industries. By integrating AI-driven insights, service-oriented architectures, and edge computing, his research enhances the resilience, efficiency, and intelligence of industrial and healthcare ecosystems, ensuring seamless interoperability, predictive decision-making, and structured digital adoption across complex networks.

Dr. Mukherjee has extensive teaching experience at both undergraduate and postgraduate levels. At the University of Cambridge, he has designed and delivered guest lectures on Industrial IoT, low-cost digital solutions, and digital manufacturing. He has supervised postgraduate research on energy analytics and industrial automation. Previously, at IIT Kharagpur, he co-developed two Massively Open Online Courses (MOOC) on IoT and Industrial IoT, and he has taught courses on wireless networks, software engineering, and IoT architectures. He continues to mentor students in applied research, focusing on real-world industrial and healthcare challenges

Professional Affiliations

• Fellow of Royal Statistical Society (UK),
• Senior Member of IEEE (USA),
• Member of IET (UK),
• Affiliate Member, IFAC (USA)