We aim to connect students and research leaders in ML/AI by helping the students discover projects suited to their interests and research labs showcase their work and available opportunities Learn more about the platform
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The Oxford Biomedical Image Analysis (BioMedIA) cluster is an academic group of faculty, postdoctoral researchers, software engineers, support staff and research students that develop medical imaging and image analysis algorithms and tools that aim to improve image-based diagnostics, therapies and monitoring technologies in hospitals and primary care, and for both western world and global health care settings. The breadth of our interests span all major clinical imaging modalities (particularly magnetic resonance imaging, ultrasound imaging, endoscopy imaging, histopathology), multi-modal imaging (imaging and audio, imaging and gaze tracking, imaging and electrocardiogram) and microscopy. We conduct inter-disciplinary translational research with clinical partners in Oxford and elsewhere in the UK and overseas in clinical domains of application ranging from fetal development, to oncology, respiratory medicine, gastroenterology, neurology and cardiovascular medicine.
See lab's pageThe Laboratory of Computational Neuro-Oncology at the École Polytechnique Fédérale de Lausanne (EPFL) focuses on biomedical data science for children and young adults with brain tumors. Our research group is affiliated with the Swiss Institute for Experimental Cancer Research at EPFL, the Department of Neurology at the University of California, San Francisco (UCSF), and the Centre for Molecular Medicine Norway (NCMM). We study clinical cancer genomes and develop statistical and AI approaches for rapid diagnostics that are globally accessible and transformative for patients with aggressive brain tumors. Our current research focus is centred on the following topics: (1) origin and somatic evolution of pediatric brain tumors (eg, Nature 2020a, Nature 2020b, npj Genomic Medicine 2023), (2) rapid molecular diagnostics in pediatric neuro-oncology (eg, The Lancet Oncology 2018, Journal of Clinical Oncology 2019), and (3) clinical cancer genomics in early-phase trials for patients with brain tumors (eg, Clinical Cancer Research 2022, Cancer Discovery 2023)
See lab's pageComputer Vision Lab is a research group at Warsaw University of Technology that gathers faculty and students working together on topics at the intersection of computer vision, machine learning and perception.
See lab's pageWe specialize in designing efficient computational methods and mathematical models for analyzing data from high-throughput biotechnologies, such as mass spectrometry, NMR, HiC, and NGS. We are particularly interested in applications in molecular medicine and issues related to the evolution and stability of the human genome.
See lab's pagePrimarily based at the NYU Abu Dhabi campus, the Clinical Artificial Intelligence Lab is a hub at New York University for state-of-the-art machine learning research that tackles real-world clinical problems. The group is led by the Principal Investigator Dr. Farah Shamout. Our long-term goal is to improve health outcomes by designing and developing smart diagnostic and prognostic systems. Our research interests cut across multiple disciplines, namely health, engineering, & computing.
See lab's pageI am interested in methods that can deliver a robust decision-making capability in complex scenarios. Such methods can be applied in control to obtain broadly intelligent agents. At the core of this effort is solving credit assignment over prolonged horizons. I like to put, perhaps unorthodoxly, many problems under this umbrella. The tasks requiring extreme reasoning, like math solving, on the one side and classical continuous control in robotics, on the other side.
See lab's pageRobot learning is a broad domain, that encompasses various aspects of computer vision, reinforcement learning and robotics. Recently the field has become even broader as more and more high level planning algorithms in robotics involve LLMs.
See lab's pageWe are a group of astronomers, machine learning enthusiasts, engineers, and enthusiasts, eminently human, coming from all over the world to make it happen. Our goal is to use foundation models to democratize Astronomy for everyone and expand our horizons on what’s possible for the field moving forward. One of the big questions we want to answer is: can large language models come up with unique scientific insights and hypotheses?
See lab's pageThe Generative AI group focuses on building deep generative models (a combination of probabilistic modeling and deep learning) that could be used for defining generative processes, synthesizing new data, and quantifying uncertainty. The research carried out within the Generative AI group is reinforced by multiple applications in Life Sciences (biology, biochemistry), Molecular Sciences (chemistry, physics), and problems ranging from signal processing (e.g., data compression) to self-driving cars, and smart devices, and smart apps (e.g., chatbots, art generation).
See lab's pageGMUM (Group of Machine Learning Research) is a group of researchers working on various aspects of machine learning, and in particular deep learning - in both fundamental and applied settings. The group is led by prof. Jacek Tabor. We are based in the Jagiellonian University in the beautiful city of Kraków, Poland.
Some of the research directions our group pursues include:
In 2023, we organized the second edition of Machine Learning Summer School (MLSS^S) with a focus on Applications in Science. We invite participants to collaborate with us on various ongoing research projects - learn more here.
See lab's pageIDEAS NCBR Sp. z o.o. is a research and development centre operating in the field of artificial intelligence and digital economy, whose mission is to support the development of these technologies in Poland by creating a platform that connects the academic and business environments. IDEAS NCBR Sp. z o.o. is a part of the National Center for Research and Development (NCBR Group). Our goal is to build in Poland the largest, friendly to conduct innovative research platform, to educate a new generation of scientists focused on development of algorithms and their subsequent practical application, commercialization in the industry, finance, medicine and other branches of the economy. At IDEAS NCBR, we are constantly on the lookout for new talent. If you are a student or graduate of Mathematics, Computer Science, Information and Communication Technology or a related discipline and would like to pursue a career in research, then share your plans with us.
See lab's pageML in PL Association is a non-profit organization set up by students from Poland that wanted to have a world-class machine learning conference in their country, so they decided to organize it themselves. The association consists of a group of volunteers, mostly undergrad, graduate, and PhD students, that are devoted to fostering the machine learning community in Poland and Europe and promoting a deep understanding of machine learning.
See lab's pageIn our research laboratory at Poznan University of Technology, we process data for a wide range of perception applications using a variety of vision sensors and hardware platforms, employing computer vision and machine learning algorithms and techniques.
See lab's pageWe are the SprintML lab with a research focus on Secure, Private, Robust, INterpretable, and Trustworthy Machine Learning. The lab is jointly led by Professors Adam Dziedzic & Franziska Boenisch. We are located at the CISPA Helmholtz Center for Information Security in Saarbrücken, Germany. Get to know our team and find out about our latest research.
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