Social networks have offered us a lot of data. Hence, how to understand the data and find insights from the data opens up research directions. In our team, we focus on addressing the Top K, and we define a series of new research problems for our members. We utilize advanced machine learning methods and develop new algorithms to handle them. Recently, we have worked on an activity recommendation problem. 

How to handle big datasets with hundreds of GB, even a few TB, is a tough research problem.  We define and provide a series of algorithms to handle big data problems. We aim to reduce computing time and increase accuracy for large-scale datasets. In our lab, we published a series of papers relevant to big data processing.  Several algorithms have been developed based on Hadoop and Spark frameworks. Recently, we have focused on how to select a small number of samples. 

For this research field, we focus on how to implement ML and AL to map disasters. We have studied susceptibility landslide disasters for 15 years. We developed a series of ML-based landslide prediction models, which have been published in many papers. Currently, we are investigating the reliability of models.

Edge computing is hot topic.  Handling the massive amount of data generated by Smart Mobile Devices (SMDs) is a challenging computational problem. Edge Computing is an emerging computation paradigm that is employed to conquer this problem. It can bring computation power closer to the end devices to reduce their computation latency and energy consumption. Therefore, this paradigm increases the computational ability of SMDs by collaboration with edge servers. This is achieved by computation offloading from the mobile devices to the edge nodes or servers. However, not all applications benefit from computation offloading, which is only suitable for certain types of tasks. Task properties, SMD capability, wireless channel state, and other factors must be counted when making computation offloading decisions. Hence, optimization methods are important tools in scheduling computation offloading tasks in Edge Computing networks. 

Doctor Kuanishbay Sadatdiynov developed many algorithms to handle these problems.