Artificial Intelligence: Technological and Human Foundations

Farhan Ali is an Assistant Professor in the Learning Sciences and Assessment Academic Group. A neuroscientist by training, he was previously an Associate Research Scientist at Yale University School of Medicine, performing translational neuroscience research related to brain disorders and learning using neuroimaging. Farhan received his PhD (Neuroscience) from Harvard University doing basic research on brain circuits underlying learning and a BSocSci (Psychology, 1st Class Honours) from National University of Singapore with undergraduate research in brain and cognition. Farhan has taught and supervised students at NTU and Yale University in the areas of neuroscience, psychology, and education. His students have co-published papers and gone on to pursue education and STEM-related careers. At NIE, his teaching portfolio includes AI/machine learning, quantitative methods, technologies for learning and science of learning. Research goals: How we feel and what pushes us can determine what, and how much, we learn. Thus, our group is interested in using modern methods from educational data mining/data science, machine learning, and big data to better understand the complexities of emotions and motivation such as interest, curiosity, engagement. We tackle these issues particularly in technology-rich environments such as digital learning and social media. The overall goal is to discover and apply new knowledge to enhance learning experiences/outcomes, human functioning, and well-being. Undergraduates, graduate students and research fellows are welcome to join our group. Funding for PhD studies is available. More information at: https://www.findaphd.com/phds/project/emotion-and-motivation-in-everyday-informal-learning-a-big-data-machine-learning-approach/?p174912

**** ANNOUNCEMENT(s): I am always on the lookout for PhD/EdD students. If you are interested in doing impactful work at the intersection of emotions, learning through problem-solving, and AI for education, feel free to reach out for any queries and discussions on overlapping research interests! A short writeup of current projects can be found here: https://lnkd.in/gmmztMBC. Next application cycle in second half of 2025! **** Dr. Tanmay Sinha is an assistant professor at the National Institute of Education, Nanyang Technological University in Singapore. He obtained a master’s degree in artificial intelligence from Carnegie Mellon University (USA) and completed his doctoral work in the learning sciences at ETH Zurich (Switzerland). Tanmay served as executive director for the first ETH-EPFL joint doctoral program in the learning sciences in Switzerland during its formative years (2021-2023), where he co-developed the academic program strategy, formulated and taught courses on learning sciences foundations and artificial intelligence for education. Tanmay's research has appeared in flagship avenues such as Journal of the Learning Sciences, Journal of Educational Psychology, Review of Educational Research, Learning and Instruction, and Cognitive Science. His research has received further accolades at three international conferences, including Empirical Methods for Natural Language Processing (shared task winner in modeling large scale social interaction in MOOCs), Intelligent Virtual Agents (best student paper), European Conference on Technology Enhanced Learning (best paper nominee). Tanmay has served as a peer-reviewer for journals such as Nature Scientific Reports, Journal of the Learning Sciences, Journal of Educational Psychology, Learning and Instruction, Instructional Science, Journal of Learning Analytics, International Journal of Computer Supported Collaborative Learning, Computers and Education, to name a few. His research has also garnered attention from prestigious media outlets like The New York Times, Times Higher Education, and the World Economic Forum.