Through the melding of history with technology, a team of scientists and researchers at LUMS is bringing to life our heritage through digitization. This unique combination of archaic knowledge and cutting-edge technology has produced a project that has won THE Awards Asia 2022 for Excellence and Innovation in the Arts. The Sikh Virsa website project is co-led by Dr. Murtaza Taj from the Department of Computer Science and Dr. Nadhra Shahbaz Khan, who is an Associate Professor of art history at the Mushtaq Ahmad Gurmani School of Humanities and Social Sciences, LUMS.

Dr. Taj’s expertise brings in computer vision and Machine Learning to the challenge of recording fine details of artefacts from a bygone era, whereas Dr. Khan’s grip on art history, particularly Sikh art and architecture helps narrow down the search for the most significant pieces of history and their value to contemporary culture. Together, they are helping bring to life artefacts from Pakistan’s Sikh period, in the process creating new opportunities for collaboration beyond the university. The experts would also like to acknowledge the role of their research assistants Ayesha Ali and Amjad Mughal, who offered a complimenting set of technical skills as well as creative writing skills respectively, that fit very well with the kind of work needed to make the project move on smoothly.

Out of the many challenges, working through the peak of the covid pandemic required great perseverance from the team. Recalling this challenge, Dr. Nadhra stated “It brought in a new sense of significance to the project, as we realized how restricted we were in our movements and how important it was to use a digital platform to reach out to people.”. Dr. Taj while recalling the thoroughness of the digitizing exercise said, “We tried to measure every millimeter of the building through laser scanners, panoramic tours and extensive photography [of every single object that needed to be recorded], so that they could be presented in a virtual world.”. He also acknowledged the cross-disciplinary manifestation of working at LUMS. “In this particular case, the coordination between faculty and administration between different schools was amazing!”, he said.

Materials from the iconic Lahore Fort’s Sikh Gallery were given a visual online showcase in Sikh Virsa Pakistan, the first website of its kind in the region, which narrates a journey through Sikh culture and history. The project aims to make culture more accessible and relevant, bringing the arts to new audiences. The project has also led to the creation of a new undergraduate history course (HIST-2121: Digital Preservation and Historical Documentation) that has engaged students in the humanities, social sciences and pure sciences in learning to use computer software to complement traditional research and learning methods. It has also inspired other museums to develop similar projects.

Dr. Murtaza has been collaborating with Dr. Nadhra since 2015 over various forms of the idea to preserve and digitize our heritage. The team would like to acknowledge the Department of Archeology with utmost gratitude and sincerity, for their cooperation and support throughout this exercise.

Another spin-off is in a collaboration where 150 LUMS students will spend a semester with as many students from the University of Baltistan in Pakistan’s Himalayan north in July 2022. The intervention aims to preserve cultural artefacts that have been discovered from prior Greek, Buddhist, and Christian civilizations, exposing students to critical preservation skills needed in the country.

Describing the initiative as “impactful and collaborative”, the judges said: “Through internal, multidisciplinary collaboration between the computer science and history departments, a new project has emerged – a new but not necessarily exclusive way of looking at and reading history.” 

Nadhra Shahbaz Khan is Associate Professor of art history at the Lahore University of Management Sciences. A specialist in the history of art and architecture of the Punjab from the sixteenth to the early twentieth century, her research covers the visual and material culture of this region during the Mughal, Sikh, and colonial periods.

Murtaza Taj is an Assistant Professor at the Lahore University of Management Sciences. His research interest lies in the area of Computer Vision, Graphics and Image Processing. In particular, he is interested in detection and tracking of object in 2D and 3D scenes and in automatic generation of 3D models from raw point cloud data. At LUMS he is a director of Computer Vision and Graphics Lab and the director of Technology for People Initiative.

learn more details in a YouTube video here.

To see more heritage conservation projects by the team, visit this link.

Dr. Muhammad Hamad Alizai from the Department of Computer Science and the Syed Babar Ali School of Science and Engineering has been promoted to Associate Professor and granted tenure!

Dr. Alizai has over 12 years of experience in Germany and Pakistan as a researcher, software engineer, and technical lead both in industrial and academic settings. He has authored a book on XXXX, several book chapters, and has published more than 45 scientific papers, several of them in top flight ACM/IEEE journals and conferences. He is experienced in leading innovative research projects in pervasive computing technologies such as Internet of Things, sensor and delay tolerant networks, ICT4D, and mobile computing. Dr. Hamad is a recipient of the Vice Chancellor's Award for Teaching Excellence at LUMS, and a recipient of the George Forster Research Fellowship for senior researchers, under the auspices of the Humboldt Foundation. Dr. Alizai is also winner of the DAAD grant titled "Greenify Older Buildings in Emerging Countries". He has also been awarded the People's Choice Award for Inverted HVAC at ACM BuildSys 2017.

Prof. Nauman Ahamd Zaffar from the Department of Electrical Engineering has been promoted to Professor of Practice!

Prof. Zaffar joined the School of Science and Engineering in 2010 as full-time faculty member in the Department of Electrical Engineering. He is part of LUMS Energy Optimization Committee and has established the region’s most active ecosystems in the areas of power Electronics, smart grids and renewable energy.

Prof. Zaffar received his BS (1990) and MS (1991) in Electrical Engineering from University of Pennsylvania. He then continued his work at the Electro-Optic / Magneto-Optic Labs at the University on development of a high resolution frequency swept microwave diversity imaging system in multiple simultaneous bands from 2GHz-60GHz. He joined University of Engineering and Technology in 1994 where he worked till 2000 as trained the finest talent in electrical engineering. His current areas of interest include dc/dc converters for Solar PV applications, dc/ac inverters for grid-tied distributed energy sources and VFDs for industrial, off-grid and automotive applications.

Prof. Zaffar is also an entrepreneur and is currently leading the National Incubation Centre Lahore at LUMS.

We are delighted to announce the appointment Dr. Hamad Alizai, Associate Professor, Department of Computer Science, SBASSE, as the incoming director of the LUMS Learning Institute (LLI).

Dr. Alizai has over 12 years of experience as a software engineer, technical lead in industry and academia. He is a prolific researcher, with interests in the Internet of Things, networks, mobile computing, and related innovative computing technologies. Dr. Alizai is also the recipient of Vice Chancellor's Award for Teaching Excellence, 2022. His interest in LLI goes back during the Institute’s formative years when he participated in the Instructional Skills Workshop (ISW) and subsequently, as a certified instructor for ISW programs.

During the pandemic, Dr. Alizai was not only an enthusiastic participant but also led several pedagogical workshops for faculty. Dr. Alzai’s growth and impact as a computer science teacher is demonstrated by his ongoing innovation in teaching large classes and designing authentic assessments to enhance the students' learning experiences across 9 different courses in 22 sections.

His commitment and leadership to our teaching community has been evident from the get-go, given his significant contributions to the growth and development of the LLI and its programs. There are wonderful teachers at LUMS. There are fewer who have shown, repeatedly the vision and ability to do things differently in the classroom and across LUMS in ways that influence the learning experiences of students, faculty, and our wider community.

Building on the many contributions of the outgoing director, Dr. Suleman Shahid and LLI staff, and working with the current Interim Director, Dr. Launa Gauthier, Dr. Alzai wants to strengthen LLI’s engagement with each School. He wishes to further understand their needs, build school specific programs, trainings and other supports for faculty and students. Dr. Alizai is also keen on developing relationships with both public and private sector organizations.

We are pleased to welcome him aboard and look forward to his work at LUMS!

Sheza Munir, a Computer Science junior at LUMS, won the Health Tech Pitch Competition at the first Health Data Science conference for her Migraine Prediction Engine. The Clinical and Translational Research Incubator (CITRIC) at Aga Khan University (AKU) organized the conference from March 2nd to 4th, 2023.  The aspiring health informatician shares the journey of her award-winning project.

Sheza vividly remembers standing in the middle of the stage, with hundreds of ears focusing on her every word. Presenting her work to top-tier researchers in Pakistan on a topic she held so dear to her heart was one of the proudest moments of her life. Being the only female and the only undergraduate at this conference meant that she had achieved something monumental, and the winning certificate was tangible proof of her months of effort.

The country's first Health Data Science conference focused on amalgamating medical research with the latest advancements in computer science. The two-day event included a pitch competition that showcased groundbreaking projects from leading universities in Pakistan. The competition aimed to foster future collaborations and open doors for joint projects with the invited universities.

Sheza was LUMS’ representative for the competition. She and her team of Dr. Basmaa Ali, Dr. Agha Ali Raza, Danyal Maqbool, Saad Hasan Iqbal and Syeda Mah Noor developed a Migraine Prediction Engine leveraging data from longitudinal studies of several migraine patients, encompassing all subtypes of migraines. Her project employs health technology to treat chronic disorders by predicting a disease event pre-occurrence. The method can then be extrapolated over other chronic diseases.

Why Migraines? 
A migraine is marked by a moderate to severe headache, usually localizing in one part of the head and causing nausea, hypersensitivity to light and sound, and dizziness. It is a common disease, affecting 1 in 5 women and 1 in 16 men, and it usually goes untreated for most people. As the statistics suggest, women suffer from migraines more occasionally than men. 2/3rd of migraineurs are women. It becomes an even bigger problem once puberty hits, as menstruation is a big trigger for migraines. This became one of the top motivations for Sheza and her team to work on this topic. Unfortunately, adding to the problem, Pakistan ranks 143/156 countries on the global gender gap index for healthcare outcomes. The crisis does not end here. Migraine and its treatments not only burden the affected and the healthcare system but also significantly impact the GDP due to a major loss in productivity. The team calculated an estimated loss of around 20 billion dollars per annum in productivity. Therefore, predicting a migraine attack in time and thus preventing it would be a major achievement on several frontiers. 

How does the Prediction Engine work? 

The dataset comprises three main streams that were collected from 3 sources:

1)    Smartwatches to track digital biomarkers like heart rate, electrodermal activity, and body temperature.
2)    Diary logging on smartphones for the migraine location, duration, and time.
3)    Weather data for the heat levels, cloud cover, and air pressure.

These three data streams are then manipulated according to every individual to track and predict a migraine event 24-48 hours pre-occurrence and suggest helpers (mitigating factors) that would aid the individual when the migraine occurs. Nine variables are fed to a Wav-2-Vec model, an already developed model used in speech prediction that uses contextual basis to predict missing terms in a sentence by looking at the words before and after the missing word. The model creates a stack of the values and monitors them pre-migraine, mid-migraine, and post-migraine. Over the training period, the model learns the values that lead to a migraine event. Thus, the next time the stack values match the distinctive ones of a migraine, the model alerts the individual that a migraine event is about to occur and suggests precautionary measures. The model has conducted this procedure with an average of 94% accuracy over several tries. 

However, the factor that truly puts Sheza’s particular migraine prediction model over the others is that this engine provides personalized feedback and personalized solution. Every migraineur has specific triggers and certain helpers. All prior studies have been done on groups that do not represent one person’s migraine event.

Sheza believes that interdisciplinary research, inculcating advancement in both healthcare and technology, is truly the way forward. While sharing her journey, she mentioned how every person on her team, from the faculty to the friends she made at AKU during the conference, played a vital role in winning the competition. The prize money of PKR 200,000/- has been invested in the project to aid with data collection.

Sheza hopes to bring her idea to fruition and get the model introduced in the healthcare industry in the upcoming years, thus bringing about a tremendous revolution in the field of health technology.