Adji Bousso Dieng
I am an Assistant Professor of Computer Science at Princeton University where I lead Vertaix on research at the intersection of artificial intelligence and the natural sciences. I am affiliated with the High Meadows Environmental Institute (HMEI). I am also a Research Scientist at Google AI and the founder and President of the nonprofit The Africa I Know. I have been named an AI2050 Early Career Fellow by Schmidt Futures and the Annie T. Randall Innovator of 2022 for my research and advocacy by the American Statistical Association. I received my PhD from Columbia University where I was advised by David Blei and John Paisley. My doctoral work received many recognitions, including a Google PhD Fellowship in Machine Learning, a rising star in Machine Learning nomination by the University of Maryland, and a Savage Award from the International Society for Bayesian Analysis, for my doctoral thesis.
I am a postdoctoral researcher in Computer Science at Princeton University where I work with Adji Bousso Dieng on developing methods at the intersection of Artificial Intelligence and Materials Science to address problems related to medical imaging. I previously completed my PhD in Automatic, Signal and Image Processing from Inria, Côte d'Azur University in France, jointly advized by Rachid Deriche and Samuel Deslauriers-Gauthier. I investigated Diffusion Magnetic Resonance Imaging and 3D-Polarized Light Imaging of the Brain white matter. I hold a MSc in Computational Biology and Biomedicine from Côte d'Azur University under the supervision of Rachid Deriche, and two engineering degrees from Ecole Centrale de Lyon, France and Ecole Supérieure Polytechnique de Dakar, Cheikh Anta Diop University, Senegal. Outside work, I enjoy meditation, soccer and going to the gym.
Andre Niyongabo Rubungo
I am a PhD student in Computer Science at Princeton University, where I am advised by Adji Bousso Dieng. I am interested in Artificial Intelligence, with a focus on Multitask and Multimodal Learning. I aim to leverage Natural Language Processing and Machine Learning to solve challenging problems in the Sciences. I completed my Masters and Bachelor’s degree in Computer Science and Technology at University of Electronic Science and Technology of China (UESTC) in China. My research in natural language processing during my Masters spans several topics. I have worked on machine translation, language modeling, text classification, summarization, sentiment analysis, common sense reasoning, named-entity recognition, and dataset creation and curation for low-resourced African languages. In my free time, I enjoy playing soccer, going to the gym, running, and hiking.
I’m a first-year PhD student in the Department of Computer Science at Princeton. My main research interests are in understanding and improving machine learning algorithms in the context of fairness, robustness, and reliability. I did my undergrad at MIT, where I worked on machine learning research with Devavrat Shah and Aleksander Madry.
I am a PhD student in Computer Science at Princeton University, where I am advised by Adji Bousso Dieng. I graduated from Columbia University with M.S. in Data Science and B.A. with Statistics and Applied Math majors. I was advised by David Blei during masters, and by Itsik Pe'er and Andrew Gelman during undergrad. I am interested in artificial intelligence, with a focus on probabilistic methods and deep generative models. I aim to combine probabilistic modeling with deep learning to better utilize human knowledge in complex models, and currently work on methodology and scientific applications. Outside of work, I enjoy music, art, and taking walks.
Daniel Lwanzo Paluku
I am an incoming graduate student in the Computer Science department at Princeton University interested in the application of Machine Learning in Materials Science. I previously completed my Bachelor's in Mechanical and Energy Engineering at Kazan State Power Engineering University in Russia where I worked on porous materials under the supervision of Professor Olga V. Soloveva. Upon graduation, I joined the Master's program in Clean Energy Processes from the department of Chemical and Biological Engineering at the University of Erlangen-Nuremberg where I have gained knowledge in thin-film processing as well as self-organization processes and nanotechnologies of dispersed systems.
I am a first year M.S.E. student in the Computer Science department at Princeton University, advised by Professor Adji Bousso Dieng. I graduated from École Polytechnique in Paris, France with a B.S. in Mathematics and Computer Science. I am interested in Artificial Intelligence, particularly in Energy-Based Models. Previously, I completed my Bachelor Thesis at Instadeep (Paris, France), where I worked on a Contrastive Learning Model in the context of Few-Shot Learning and Meta-Learning for Image Classification. Outside of work, I enjoy spending time in the mountains, either hiking or skiing.