Speakers

Prof. Dr. Faisal Shafait

Dr. Shafait has 15+ years of research and teaching experience in Artificial Intelligence and Machine Learning with a primary focus on computer vision and document image analysis. He completed his PhD in Computer Engineering from Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU), Germany in 2008 with highest distinction. Currently, he is working as a Professor and is heading the Department of Computing at the School of Electrical Engineering and Computer Science (SEECS), NUST, Pakistan as well as the Deep Learning Lab (DLL) under National Center of Artificial Intelligence (NCAI), NUST, Pakistan. Dr. Shafait has made a significant international reputation in the field of Artificial Intelligence by earning 10,900+ citations with i10 and h indices of 159 and 52 (Google Scholar) respectively. He received the prestigious IAPR/ICDAR Young Investigator Award by the International Association of Pattern Recognition (IAPR) in 2019 and has recently been included in the list of the World’s Top 2% Scientists compiled by Stanford University.

Dr. Christian Weis

Dr. Christian Weis has received the Ph.D. degree in electrical engineering from the TU Kaiserslautern, Germany, in 2014. From 1996 to 1998, he was with Mitsubishi Semiconductor Europe, Germany, where he was engaged in the design and development of microcontrollers. From 1998 to 2009, he was with Siemens Semiconductor, Infineon Technologies AG and Qimonda AG, Munich, Germany, in DRAM design. During this time frame, he was involved in DRAM design for graphics and commodity DRAM products. In 2006, he was a Design Team Leader for the 1Gb DDR3 DRAM, the first DDR3 volume product at Infineon/Qimonda. Since 2009, he has been with the Microelectronic System Design Research Group, TU Kaiserslautern, Germany. He holds more than 20 patents related to DRAMs and DRAM design, and published more than 70 papers. His current research interests include DRAM controller design, Near- & In-Memory processing, 3D-integrated DRAMs, heterogeneous memory architectures, and MPSoCs.

Dr. Syed Mahmood Nasir

Dr. Mahmood has spent decades as a forestry practitioner from grass roots to policy level, as a Board member of WWF- Pakistan, Islamabad Wildlife Management Board and other NGOs, private, semi-government, and government organizations. Dr Mahmood has been a forester and has represented Pakistan in multiple international conferences and has trained multiple generations of foresters while spearheading new innovations in the field One of the latest contributions has been to arrange visits of trainee mid-career forest officers to the National Center for Artificial Intelligence (NCAI) located at the National University of Science and Technology (NUST) with follow up visit of the NUST researchers to the Forest Services Academy, Ghora Gali.

Mr. Sunil Thapa

Mr. Thapa is an experienced researcher in Earth Observation technology and forestry, with more than a decade of expertise specifically in wildfire, forest ecosystems, habitat modelling and biodiversity conservation. He holds MSc degrees from both the University of Twente in the Netherlands and Pokhara University in Nepal. He currently serves as a Remote Sensing and Geo-Information Analyst at International Centre for Integrated Mountain Development (ICIMOD), a renowned inter-governmental research organization for the 8 Hindu Kush countries. Additionally, he is associated with the SERVIR-Himalaya Initiative, which is funded by NASA/USAID. Mr. Thapa's research primarily revolves around forest fire monitoring and risk assessment, as well as the development of climate-resilient forest management systems. He has published in several peer-reviewed international journals and also authored a book chapter on forest fire detection and monitoring.

Dr. SamiUllah Dawar

Dr. SamiUllah Dawar is an Assistant Professor/Head at the Department of Forestry and Range Management, University of Kohsar. He has worked on multispectral, Lidar, InSAR, stereopair aerial photographs and stereoair high-resolution satellite imagery for the generation of canopy height model (CHM) and for volume and above-ground biomass (AGB) estimation. His research includes forestry and remote sensory data.