Data Science and AI for City Management


Technological advancements are rapidly changing the landscape of city management. With the growth of urbanisation and internet (IoT) cities are generating vast amounts of data, from traffic patterns to energy usage to public health information. By leveraging data science and AI, informed decisions can be made to optimize city services, improve public safety, and enhance the quality of life for citizens.

atomcamp has already developed partnership with CITY at LUMS for trainings in the area of AI for City Management. At this webinar, Dr. Momin Upal, Associate Professor at LUMS and Prinicipal Investigator at CITY at LUMS will highlight how AI and Data Science can play a significant role in city management organised jointly by atomcamp and CITY at LUMS. Dr. Momin and his team has also been developing products and solutions for application of AI in city management in Pakistan.


Dr Momin Uppal

Momin Uppal is a tenured associate professor of electrical engineering at Lahore University of Management Sciences. He received his PhD and MS in Electrical Engineering from Texas A&M University in 2010 and 2006, respectively. Earlier, he received his BS in Electronic Engineering with highest distinction from GIK Institute of Engineering Sciences, Pakistan in 2002. At LUMS, he serves as the director of the Advanced Communications (AdCom) Lab and the Smart Data Systems and Applications (SDSA) Lab. He has published over 50 papers in leading IEEE Journals and Conferences, and has two US patents to his name. During his time at LUMS, he has secured research funding from national and international agencies including Ignite (formerly National ICT R&D Fund), Higher Education Commission of Pakistan, National Instruments, and United Kingdom's Grand Challenges Research Fund (GCRF). His research interests lie in prototyping of novel communication strategies using software defined radios (SDRs), non-orthogonal multiple access, machine learning for wireless communications, back-scatter communications, and environmental sensing using radio signals.