Transforming education data into smart
learning and decision making tools.
We are team of researchers bringing together AI experience from academia and AI application experience from industries leaders such as Samsung, Amazon and Microsoft. In past, we explored text, images, DNA sequences, medical records and now we want to the way educational data can be collected and explored for better learning. We are bringing following expertise to the table.
Most of the educational data is in handwritten or hand written scanned documents format. At Samsung's printing division (2008~12) we extensively worked on fonts and handwritten documents. We also optimized the application to suite the small device memory and computational resources.
Images and videos play a central role in STEM and non STEM education system. Without processing them efficiently it's hard to reach best decisions. We worked on mathematics of images and video and applied them to GPUs to get best performance during our work at MRI division of Samsung.
For humans, prediction and recommendation are key to decision making. Recently, Deep Neural Networks (DNN) have revolutionized it. We successfully developed and applied advanced AI algorithms to various data sets. We published the findings in top scientific journals and conferences.
The data we are dealing with (text books, question papers, answer sheets, notes, suggestions, ..etc.) is in human understandable form. Long Short Term Memory (LSTMs), a form of Deep Learning algorithms significantly improved the NLP capabilities of machines. In past, we worked on a Q&A system that used machine learning algorithms.
Hundreds of thousands of universities and colleges across the world produce tons of data from every class, exam, lab test and reports. Most of the time data is unused because its unstructured and hand written paper form. We are using state of art methods to collect, organize and analyze it. More importantly, developing user friendly tools to bring the learning to end users.
It's impossible to collect all the relevant data without employing advanced tools due its size and nature. We have been developing advance scrapers with NLP capabilities to collect relevant information from thousands of universities and courses.
Data cleaning and organizing huge data in an efficient way is important for energy efficient learning. With help of experts and advanced mathematical techniques such as compressive sensing we are developing methods to organize data.
We are using data collected over years to train sophisticated multi layer Artificial Neural Networks (ANNs) and their variants for prediction, recommendation and classification. These models are constantly improved with new data availability.
Allowing users to interact with a complex system and representing results with many dimensions in a easy to understand is an extremely challenging task. We employ best in the field research and best tools to achieve the desired results.
With limited resources web applications are best and fastest way to let users evaluate the work. It allow us to easily to assess the success of the product and make plans for improvement. We have been developing web apps using best platforms available.
Mobile certainly leading the user index compared to desktop. With the availability of resources in future we will be looking forward to convert top UI/UX research into mobile apps that are stable and scalable. Currently, we use responsive web apps.
Zahid is founder and CEO of InI Labs Inc., holds phd in applications of AI applications in bioinformatics. Worked in academia (ISI Kolkata, UWaterloo) and industry (Samsung Electronics Korea) on various advanced projects. Working on tecnology core and strategy at InI labs.
Farquad is Director of Data Division at InI Labs Inc., holds phd in applications of AI applications to finance and banking sector. Worked in various universities (HCU, Hong Kong University, Madina University) across the world. Responsible for all data related tasks at InI Labs.
Fadia is an AI Expert and Advisor at InI Labs Inc. , holds phd in Astrophysics from Université Paris Sud (Paris XI). Have been working on few of the most challenging problems in physics with the application of advanced mathematical algorithms applied to run multicore machines. Responsible for AI strategy and technical direction at InI.
Nazia holds a BA and B.Ed (education) degree in social sciences from Osmania University. Have worked with schools and colleges for a decade. She is responsible for identifying data sets, collecting them from authenticated sources curating them. Also responsible for exploring new applications for AI in education.
A Diplomat Economist with MBA degree from South Korea Mihaela enjoys her career in Marketing by bringing new ideas to life. She is associated with top tech companies (Samsung Electronics, IBM) and advising InI Labs on business strategy, direction, evaluation and marketing aspects.
Nirbhay is Civil Engineering graduate from University of Waterloo. He is the co-founder of an entrepreneurship program called 'Be A Nomad', was CEO of Engineers for Hope, and spoke twice at TED. Harry is planing and marketing expert at InI labs and advisor in business strategy.
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