Lubna is a financial technology professional with experience in DFS research, consulting, product development, business development, and channel partnerships, in-depth research into FinTech propositions. Lubna is the founding director for FinTech Center at Information Technology University where she is responsible for building the Center from ground up, the overall research direction, funding, human resource and project management of the Center. The center is the first partner lab of the Digital Financial Services Research Group at the University of Washington on solutions for DFS adoption and is expected to serve as a blueprint for future labs that will become part of this network. Focus areas of the center include DFS solutions and adoption for low literate and low-income populations in general and women in particular which begin with qualitative explorations and lead to focus segments, needs, solution design and testing. The FinTech Center has projects on women’s financial inclusion especially women entrepreneurs, group savings and fraudulent SMS detection which intersect with the areas of data science, security and human-computer interaction for development (HCI4D).

Lubna is also a consultant with FinSurgents, a Singapore based company working in Pakistan, where she has been the lead author of two studies to date. First study “Seeding Innovation: A Framework for Rooting FinTechs in Pakistan” was an in-depth study of the FinTech ecosystem in Pakistan in comparison with global hubs to suggest a road map for ecosystem development. It also included a framework for Karandaaz Pakistan to invest in FinTech startups. The other study was titled ‘Bridging the Policy Gaps: Enhancing Online Commerce in Pakistan’ which made recommendations regarding consumer protection laws, digital payment systems and human capital development in the online commerce industry. She has also been part of the team informally advising the State Bank of Pakistan on FinTech regulatory initiatives around the globe. She has authored four papers to date for SBP on regulations regarding Digital payments, P2P lending, FinTechs and Regulatory Sandboxes.

Before FinSurgents, Lubna was part of Vopium A/S, a Denmark based technology company. She was the ‘Product Development Lead – Mobile International Remittance platform’ and defined complete business requirements for front end app (End user) and back-end (KYC, payment, settlement, reporting, monitoring, money transfer, fraud prevention modules), led user experience definition and design activity, performed Regulatory research on EU Payments Services Directive, HMRC UK AML/KYC regulations and guidelines resulting in Risk based policy design for KYC, undertook vendor selection, on boarding and management for KYC/AML systems and payment processing (PEP, EU terror list, FATF, ID doc verification systems), supervise development team activities and overall project, reporting progress directly to CEO.

Before joining Vopium, Lubna worked as a marketing consultant for an NGO named Sudhaar which worked towards abolishing child labor and transparency in governance.

Waqar Ahmad has extensive software industry and academic experience. He has taught a number of courses including software development for mobile platforms, software testing, database systems, and software design and architecture. Moreover, he has done research in the areas of software ecosystems and mobile localization. In the software industry, he has worked for over 9 years in different roles including programmer, system analyst and manager and also helped establish a startup. He has done his Masters in Software Engineering from Carnegie Mellon University, USA; he also holds Masters in Software Project Management and Bachelor in Computer Science degrees from FAST-NUCES, Lahore.

Dr. Umar Janjua is an Assistant Professor in the department of Computer Science at the Information Technology University. He graduated from GIKI with BS in CS engineering in 2001, joined startup “Enabling Technologies” for two years, accepted full PhD scholarship at Cambridge University, UK, joined Microsoft Corporation as Software Engineer in 2008 and worked until 2017.

Waqas Sultani completed his Ph.D. in Computer Science under Professor Mubarak Shah at Center for Research in Computer Vision, University of Central Florida. Before this, he earned MS from Seoul National University, South Korea under the supervision of Professor Jin Young Choi at Perception and Intelligence lab. He received his BSc in Electrical Engineering from University of Engineering and Technology, Taxila.  He has worked on several projects related to human action recognition, anomaly detection, crowd tracking, anomaly detection, object segmentation, complex event detection and automatic weakly labeled annotations.  He has worked on projects funded by US Intelligence Advanced Research Projects Activity (IARPA), US Data Transport Solution (DTS), US National Institute of Justice (NIJ), US Xerox Research and Samsung Electronics.

 He has published several research papers in top computer vision conferences and journals. In addition, he holds two US patents. In 2014, he worked for Xerox Research Center, New York. He also worked for around two years in Advanced Engineering Research Organization (NESCOM) and one year in COMSATS Institute of Technology, Islamabad as a Lecturer.

Mohsen Ali is an Assistant Professor at Department of Computer Science of  Information Technology University. He is co-founder of Intelligent Machines Lab at ITU and heads Computer Vision Research Group. He received his doctoral degree from the Department of Computer and Information Science and Engineering, the University of Florida in 2014. Previously he received his MSc and MS in Computer Science degrees from Punjab University College of Information Technology and Lahore University of Management Sciences respectively. He is a Fulbright Scholar.

His research interests lie in the areas of Computer Vision and Machine Learning, specifically Deep Learning and sparse representation. Some of the research problems he is pursuing are satellite/aerial imagery analysis (research page), affective computing (research page) and multi-image co-segmentation.

Teaching

Spring 2020 : Deep Learning
Fall 2019 : Computer Vision
Spring 2019 : Deep Learning
Fall 2018 : Computer Vision
Spring 2018: Deep Learning
Fall 2017 : Computer Vision

Mudassir Shabbir received his PhD from Division of Computer Science, Rutgers University, NJ USA. His main area of research is Algorithmic and Discrete Geometry. He has developed new methods for the characterization and computation of succinct representations of large data sets with applications in nonparametric statistical analysis. He also works in Combinatorics and Extremal Graph Theory.

Previously, Mudassir has worked at LUMS, Lahore, Los Alamos National Labs, NM, Bloomberg L.P. New York, NY and at Rutgers University. He was Rutgers Honors Fellow for 2011-12.

Dr. Arif Mahmood received his MS and PhD in Computer Science from the Lahore University of Management Sciences (LUMS), winning a gold medal along the way and graduating with academic distinction. His PhD thesis was on “Computation Elimination Algorithms for Correlation Based Fast Template Matching.” He has served as a Research Assistant Professor at the School of Computer Science and Software Engineering, and later at the School of Mathematics and Statistics in the University of Western Australia from 2012-2015. Previously, he was an Assistant Professor at the Punjab University College of Information Technology from 2008-2012. He also worked as a Postdoctoral Researcher at the College of Engineering in Qatar University from 2015-2018. In 2011, Dr. Mahmood received a grant from the University of Punjab and established an image processing research facility by purchasing state-of-the-art video and still cameras, workstations and other required apparatus. In 2015, he successfully authored Linkage Project grant from Australian Research Council (ARC): “Machine Learning for Fracture Risk Assessment from Simple Radiography" with industry partners. He has excellent teaching and research experience at several national and international institutes. He was Program Committee member in FIT 2017 and in the 2nd Int. Workshop on “Robust Subspace Learning and Applications in Computer Vision” in conjunction with ICCV 2017, and ICCV 2019. His major research interests include data clustering, classification, action and object recognition using image sets. He has also worked on computation elimination algorithms for fast template matching, video compression, object removal and image mosaicking. At the School of Mathematics and Statistics, he worked on community detection in complex networks. He has been publishing extensively in prestigious journals including IEEE TPAMI, IJCV, MEDIA, IEEE TIP, IEEE TCSVT, IEEE TCC, IEEE TSC, Information Fusion and IEEE TKDE. He has presented his work at over 17 conferences worldwide including very prestigious conference such as CVPR, ECCV, ACCV, BMVC, and WACV. His profile can be accessed at UWA, Publons Profile, Google Profile, Research Gate and LinkedIn Profile.

Dr Faisal Kamiran received his PhD degree from The Eindhoven University of Technology (TU/e), The Netherlands in 2011. Afterwads, he joined King Abdullah University of Science and Technology (KAUST) as a post-doctorate fellow. Faisal joined ITU in 2013 as the first tenure-track professor and currently he is working as an assistant professor and is the Director of Data Science Lab (DSL). Under his aspiring leadership, DSL is working on cutting edge research projects with a particular focus on solving locally relevant problems, e.g., disease outbreak prediction and spatiotemporal analytics of crime data, and so forth. Here, details of the projects can be found.

Faisal is doing research in the well-established area of data science. In his brief research career, he has already published more than 25- refereed papers in various prestigious journals and conferences. His publication list includes four ICDM papers (A* data mining venue), one ECML/PKDD, two KAIS journal papers and several other high-quality papers. According to Google scholar, Dr Faisal Kamran’s H-index is 7, and his research work has more than 300 citations.

Dr. Saeed Ul Hassan is the Director of AI Lab and a faculty member at Information Technology University (ITU), a former Post-Doctorate Fellow at the United Nations University – with more than 15 years of hands-on experience in AI, Machine Learning, and Software Development client work. He earned his Ph.D. in the field of Information Management from the Asian Institute of Technology, Thailand. He has also served as a Research Fellow at the National Institute of Informatics in Japan.

Dr. Saeed’s research interests lie within the areas of Data Science, Machine Learning, Contextual Scientometrics, Altmetrics Bibliometric Tools for Evidence-based Research Policy Formulation, Information Retrieval, and Text Mining. He has published more than 50 papers in reputed international journals and conference proceedings including highly reputed venues like TKDE, WWW, JCDL, Journal of Infometrics, and Scientometrics. Dr. Saeed is also the recipient of the James A. Linen III Memorial Award in recognition of his outstanding academic performance. More recently, he has been awarded Eugene Garfield Honorable Mention Award for Innovation in Citation Analysis by Clarivate Analytics, Thomson Reuters.

Dr. Saeed is a lifetime volunteer of Pakistan Hemophilia Patient’s Welfare Society and technical lead of the National Patient Registry of people with a bleeding disorder in Pakistan.

Dr. Adnan holds a PhD in Computer Engineering from the Sapienza University of Rome, Italy. He has also been a post-doc researcher in the same university twice. He has published more than 21 papers in refereed conferences and journals. According to Google Scholar, his research papers have been cited more than 189 times. Broadly his research interests include wireless sensor and ad hoc networks, Internet of Things (IoT), distributed algorithms, mobile and distributed systems, and cloud computing. Currently, he is working on algorithms for finding efficient virtual LAN topologies, opportunistic networks, heuristics for dial a ride problem, applications of random walk in large-scale wireless sensor networks and exploiting EFI vehicle’s sensors using onboard diagnostics. He is the member of midlab (middleware laboratory) of Department of Computer Science and Engineering, Sapienza University of Rome and works closely with Prof. Roberto Baldoni and Dr. Roberto Beraldi. In addition to research, he is also assisting the research community by serving in a number of technical program committees of national and international conferences and reviewer of many international journals and government project proposals.

Dr. Adnan is an HEC PhD approved supervisor. He has been mentoring a number of MS and PhD computer science students. He has taught a variety of courses at graduate and undergraduate level including Internet of Things (IoT), Advanced Topics in IoT, Parallel and Distributed Algorithms, Special Topics in Networks, Distributed Systems, Computer Networks, Digital Logic Design and Electronics at places like National University of Computer and Emerging Sciences (FAST-NU) Lahore, Sapienza University of Rome and Aitchison College, Lahore.

For details please view the CV below.