Carnegie Mellon University

Lane Fellows

Irene Kaplow

Advisor: Andreas Pfenning

Irene received her B.S. in Mathematics from the Massachusetts Institute of Technology in 2010. There, she was involved in developing methods for leveraging protein-protein interaction networks to select hits in RNAi datasets and leveraging conservation information to predict exonic splicing enhancers. She then went to graduate school at Stanford University, where she received her Ph.D. in Computer Science in 2017. At Stanford, she developed methods to analyze novel high-throughput sequencing datasets to better understand the roles of DNA methylation and Cys2-His2 zinc finger transcription factor binding in transcriptional regulation. Irene is interested in developing computational approaches to integrate biological datasets in ways that will provide a more detailed understanding of transcriptional regulation. She is especially interested in elucidating the biological mechanisms behind the differences in gene regulation between different cell types.


Spencer Krieger

Advisor: Jian Ma

Spencer received his PhD in Computer Science in 2022 from the University of Arizona. His dissertation research focused on developing algorithmic approaches for pathway inference in systems biology and for protein secondary structure prediction. He received his B.S. in Biochemistry in 2016, where his research focused on separation and preconcentration of perrhenate by ion exchange chromatography. Overall, he is interested in combining his expertise in algorithm design with his background in biochemistry to solve pertinent biological problems by robust computational approaches.


Nam Nguyen

Advisor: Ziv Bar-Joseph

Nam D. Nguyen received his Ph.D. in Computer Science at Stony Brook University, under the guidance of Professor Daifeng Wang. His doctoral research includes multiview learning for integrating and understanding functional multiomics. He is especially interested in machine learning on graphs and manifolds, and their applications for understanding molecular mechanisms and improving genotype-phenotype predictions in complex biological systems. Prior to that, he received B.Eng. degree in Computer Science at Hanoi University of Science and Technology. Overall, his research interests include computational biology, machine learning and explainable AI.