In this lecture first we will discuss the current trends and challenges in Artificial Intelligence (AI) and Machine Learning (ML). In addition to the fundamentals of ML, we will demonstrate the importance of using Deep Learning (DL), Graph neural network (GNN) and explainable AI. While DL has been used very successfully for image analysis, GNN is being used extensively for unstructured datasets including biological datasets available in the form of graphs containing the interaction between genes, drugs, diseases etc.
ML is used in healthcare with the goal for betterment in therapeutic as well as early diagnosis of diseases. Moreover, generally the same therapies are used for patients having similar diseases. However, based on the biological conditions of a patient, use of specific therapy is the key in precision medicine. In the second part of the lecture we will discuss how DL and GNN techniques can be used for developing improved healthcare systems including some startups started from our research labs . The explainable AI will also be discussed to address the practical challenges in the medical expert system.
Finally, we will also discuss how Data Science and ML together are changing the research and development road map.
Dr. Ujjwal Maulik is a Professor in the Dept. of Comp. Sc. and Engg., Jadavpur University since 2004. He is currently a visiting faculty at Stanford University. Dr. Maulik has worked in many universities and research laboratories around the world as visiting Professor/ Scientist, is a recipient of the Alexander von Humboldt Fellowship during 2010, 2011 and 2012, and Fulbright Fellowship in 2024-2025. He is a Fellow of theThe Institute of Electrical and Electronics Engineers (IEEE), USA, International Association for Pattern Recognition (IAPR), USA, and Asia-Pacific Artificial Intelligence Association (AAIA), Hong Kong. He is also the Distinguished Member of the ACM. He is a Distinguished Speaker of IEEE as well as ACM. His research interests include Machine Learning, Pattern Analysis, Data Science, Bioinformatics, Multi-objective Optimization, Social Networking, IoT and Autonomous Cars.