Postdoctoral fellow at NYU, former PhD student at Tel Aviv University, 17th Young Scientists' Forum Organizing Committee chair
Dr. Abraham Lin is no stranger to interdisciplinary research, having a background in Nuclear Engineering (B.S.E) from the University of Michigan – Ann Arbor, Biomedical Engineering (PhD) from Drexel University, and now working as a joint postdoctoral researcher in the Center for Oncological Research (CORE) and the Plasma Lab for Sustainability and Medicine – Antwerp (PLASMANT) at the University of Antwerp, Belgium. Previously, he worked for NASA, where he studied using plasma, an ionized gas, for space propulsion before transitioning to study how the same technology can be used for cancer immunotherapy. Now, he is part of a team (Orbits) that is investigating how computer vision and artificial intelligence can be applied for advanced image analysis to unlock the full potential of next-generation, ‘patient-in-the-lab’ cancer models, known as patient-derived organoids. He hopes that by integrating these different technologies together, he can help researchers predict how cancer patients will respond to different therapies in the clinic. This could ultimately help researchers develop more effective drugs and help clinicians move towards more personalized cancer medicine.
Brenda Stride
Deputy Head of Internal Scientific Training/ Postdoctoral Programme Manager, EMBL
Mitrajit Ghosh
Specialist, Nencki Institute of Experimental Biology, Polish Academy of Science, Warsaw
Mitrajit Ghosh, is a Specialist Scientist at the Laboratory of Molecular Neurobiology, Nencki Institute of Experimental Biology, Polish Academy of Science, Warsaw, Poland. He is a PASIFIC fellow, who is working on deciphering heterogeneity in brain cancer and better defining the tumor microenvironment. He loves to solve puzzles, communicating science to common people to make science relatable and exciting. He believes the ardent thirst to find the unknown is what we call "motivation" that leads to discovery and "eureka moments''.
I am a postdoctoral researcher in bioinformatics at the German Cancer Research Center (DKFZ) in Heidelberg, where I work in the Applied Bioinformatics group lead by Professor Benedikt Brors. I am also a member of the AI Health Innovation Cluster postdoctoral program. Prior to this, I obtained my Ph.D. at the Cancer Research Center CIC-IBMCC in Salamanca, Spain. My research interests include single-cell sequencing and genomics in cancer, neurodegenerative diseases, and aging, developing novel statistical and bioinformatic methods, and applying artificial intelligence to molecular data. I strongly believe that interdisciplinary research is essential to overcoming new scientific challenges.
Affiliations:
CIC bioGUNE, Basque Research and Technology Alliance (BRTA), 48160 Derio, Spain.
Biomedical Research Networking Center in Cancer (CIBERONC), 48160, Derio, Spain.
IKERBASQUE, Basque Foundation for Science, 48009 Bilbao, Spain.
Biochemistry and Molecular Biology Department, University of the Basque Country (UPV/EHU), P.O. Box 644, E-48080 Bilbao, Spain.
Inês Pinto is a research fellow in the Center of Neuroscience and Cell Biology (University of Coimbra). She obtained her BSc in Biomedical Sciences from the University of Beira Interior and MSc in Molecular Biomedicine at the University of Aveiro since 2022. Some of her current areas of interest include cancer nanomedicine, targeted gene delivery, biomaterials, immunotherapy, and oncobiology
Our lab uses genetically modified mouse models and a combination of cell biology, molecular biology, and biochemistry techniques to study the role of altered mitochondrial dysfunction and metabolism in human diseases. A primary analytical tool of the group is metabolomics, which enables the parallel quantification of hundreds of small molecule metabolites. The team also uses computational approaches to integrate datasets from multi-dimensional analyses, including metabolomics, proteomics, and transcriptomics, with the aim to model aging-related disorders and to generate mechanistic hypotheses that will be cross validated experimentally.