I am Viplove Arora, a postdoctoral researcher working on machine learning in Bioinformatics in The Theoretical and Scientific Data Science Group at SISSA. I am a part of the Machine Learning and Systems Biology research unit led by Guido Sanguinetti. Previously, I was a Postdoctoral Research Assistant in the School of Industrial Engineering at Purdue University. I earned my PhD under the guidance of Mario Ventresca, where we devised a generative probabilistic model for graphs that learns a mixture of distinct link creation processes. I completed my bachelor’s in Production and Industrial Engineering from IIT Delhi in 2014, where I worked with Makarand Kulkarni for my bachelor’s thesis.

My expertise lies in Graph Machine Learning, and I’m actively seeking opportunities preferably in the San Francisco bay area. At SISSA, I have applied GNNs to raw biological data (RNA-protein binding, multi-omics) creating graphs for novel Graph ML tasks like transfer learning and link weight prediction. More recently, I led a project to understand the effective capacity and generalization of neural networks through the lens of pruning, with implications for both traditional and large language models (LLMs). I am also co-supervising a PhD thesis on Continual Learning in neural networks using biologically plausible optimization algorithms.

Contact Information

Email: varora@sissa.it
Office: SISSA Main Building, 656
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