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Alessandro is an Assistant Professor of Oncological Sciences and Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai. His research interests lie primarily in the area of integrative cancer genomics, cancer network biology and precision oncology, with particular focus on Multiple Myeloma, a malignancy of bone marrow plasma cells.

Alessandro achieved his MS degree in Computer Science and PhD in Biology, Human Genetics and Bioinformatics at the University of Catania (Italy), under the supervision of Alfredo Ferro, and completed his Post-Doctoral studies in Carlo Croce’s Lab at The Ohio State University in Columbus, OH, where his research focused primarily on microRNA.

Junia has completed her medical training and doctoral training in Universidade Federal do Ceará, Brazil and McGill University, Canada. Through her extensive training, she has continued to deepen her understanding of how medical genetics can be applied as a fundamental tool to direct translational studies into successful outcomes. With this goal, she completed McGill’s Clinical and Regulatory Affairs Fellowship and started a postdoctoral fellowship in Cancer Immunotherapy at Icahn School of Medicine at Mount Sinai.

As a postdoctoral fellow, she is working with multidisciplinary teams under Dr. Alessandro Laganà’s supervision and in collaboration with Dr. Samir Parekh on a mission to deliver exceptional care while conducting clinical trials with the most recent therapeutic options for Multiple Myeloma.

Alessia’s research focuses on bioinformatics approaches for the study of multiple myeloma, with an emphasis on precision oncology and the integration of high-throughput molecular data. She is particularly interested in identifying novel drivers of high-risk disease, understanding inter- and intra-tumor heterogeneity, and defining key determinants of response to targeted therapies and immunotherapies. Her work involves the development and application of computational tools for the analysis of bulk and single-cell DNA and RNA sequencing data.

She holds an MSc in Medical Physics and earned her PhD in Complex Systems for Physical, Socio-Economic, and Life Sciences from the University of Catania in 2024. During her PhD, she gained hands-on experience in clinical imaging and radiomics, and worked across transcriptomics and genomics to develop integrative strategies for personalized cancer treatment.

Mujahid (Ali)’s work lies at the intersection of AI, biomedical informatics, and clinical genomics—driving innovations that transform unstructured scientific literature and patient data into actionable insights.

He architected OncoCITE, an AI-powered framework for precision oncology, combining RAG pipelines, ReAct agents, and large language models to surface clinically relevant insights from genomic data. He has also investigated the use of machine learning for monitoring CAR-T therapy- related toxicities and is leading the development of a multimodal patient platform integrating EHRs, lab data, and advanced foundation models like Geneformer and Mistral.

Previously a TA and graduate researcher at NYU, he is passionate about building tools that make complex science more accessible—for researchers, clinicians, and patients alike.

With a background in biomedical science, Alison’s projects are focused on multi-omic data integration and analysis. Her work is centered on discovering novel therapeutic approaches for multiple myeloma patients by leveraging patient networks and advancing precision medicine. Alison is also deeply committed to harnessing the power of machine learning and artificial intelligence to drive breakthroughs in cancer biology and accelerate the discovery of innovative treatment approaches.

Outside of work, she enjoys nature walks, playing golf, as well as diving into a good book during her spare time.