Curriculum Vitae

Education

• Ph.D. in Computational Biology

  Tri-Institutional PhD Program in Computational Biology & Medicine. Dissertation on cellular context in protein–RNA interactions, advised by Prof. Quaid Morris.

  Weill Cornell Medicine / Memorial Sloan Kettering Cancer Center

  New York, NY

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• M.Sc. in Computer Engineering

  Thesis: DriveWays, identification of overlapping cancer driver modules from multi-omics data.

  Antalya Bilim University

  Antalya, Turkey

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• B.Sc. in Computer Engineering and B.Sc. in Electrical & Electronics Engineering

  Graduated with high honors in both departments; best senior project award.

  Antalya Bilim University

  Antalya, Turkey

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Experiences

• Jul 2021 - Present

  Doctoral Researcher

  Built an RBP-agnostic CLIP model to test whether eCLIP binding reflects an RNA-binding protein’s intrinsic sequence specificity, and reanalyzed 240+ ENCODE experiments with it. Developed an intrinsic-specificity score that flags non-sequence-specific binding without in vitro data. Benchmarked protein language model and AlphaFold-derived representations, built Nextflow pipelines on HPC clusters for CLIP, RNA-seq and Ribo-seq data, and showed that MSI2 promotes translation of a leukemic stem-cell program in AML.

  Morris Lab, Memorial Sloan Kettering Cancer Center & Weill Cornell Medicine

  New York, NY

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• Oct 2018 - Jul 2020

  Research Assistant

  Developed DriveWays, a graph-based algorithm for identifying overlapping cancer driver modules from TCGA multi-omics data, and ran the classification and survival analyses for MEXCOwalk.

  Computational Biology Lab, Antalya Bilim University

  Antalya, Turkey

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• Jun 2019 - Sep 2019

  Visiting Researcher

  Designed and implemented a multitask deep learning model in PyTorch to predict in vivo RBP binding sites from in vitro binding preferences using paired RNAcompete and eCLIP data.

  Morris Lab, University of Toronto

  Toronto, Canada

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• Oct 2016 - Aug 2017

  Senior Project Student

  Integrated gene expression and aCGH data to improve prediction of survival and clinical outcome in neuroblastoma for the CAMDA 2017 challenge.

  Machine Learning Lab, Antalya Bilim University

  Antalya, Turkey

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• Jun 2016 - Sep 2016

  Summer Research Intern

  Built a face recognition system based on GoogLeNet, achieving 94% accuracy on the LFW benchmark.

  Digital Media & Data Reconstruction Lab, Shanghai Jiao Tong University

  Shanghai, China

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Last publications

• ZFP36L2 orchestrates stress-adaptive plasticity in regeneration and cancer

  Authors: Q. Jiang, M. S. Raghavan, A. M. Rodriguez, M. Lallo, I. Baali, et al., Q. Morris, J. M. Chan, K. Ganesh

  Nature • 2026

  The RNA-binding protein ZFP36L2 acts as a stress-responsive orchestrator of dedifferentiation in intestinal regeneration and colorectal cancer metastasis.

• A dynamic RNA-binding protein module coordinates translation of leukemic stemness programs

  Authors: X. Xie*, F. Herrejon Chavez*, I. Baali*, et al., D. T. T. Nguyen, M. G. Kharas

  In review • 2026

  A cooperative RBP module centered on MSI2 controls translation of a leukemic stem-cell program in AML. Co-first author.

• mRNABench: a curated benchmark for mature mRNA property and function prediction

  Authors: R. Shi, T. Dalal, P. Fradkin, D. Koyyalagunta, I. Baali, B. Wang, Q. Morris

  Gen² Workshop on Generative AI in Genomics, ICLR • 2026

  A benchmarking suite of curated datasets and prediction tasks for evaluating mature mRNA representations from nucleotide foundation models.

• Uncovering the HOXA9 translational regulatory complex that promotes AML leukemic stem cells

  Authors: X. Xie*, F. Herrejon Chavez*, I. Baali*, et al., M. G. Kharas

  Blood (ASH Annual Meeting abstract) • 2024

  Identification of RNA-binding proteins that bind MSI2 and co-regulate HOXA9-associated programs in leukemic stem cells.

• DriveWays: a method for identifying possibly overlapping driver pathways in cancer

  Authors: I. Baali, C. Erten, H. Kazan

  Scientific Reports • 2020

  A seed-and-extend heuristic that identifies overlapping cancer driver modules from a protein interaction network and multi-omics data.

• MEXCOwalk: mutual exclusion and coverage based random walk to identify cancer modules

  Authors: R. Ahmed, I. Baali, C. Erten, E. Hoxha, H. Kazan

  Bioinformatics • 2020

  A random-walk method that combines mutual exclusivity and coverage to discover cancer driver modules.

• Machine learning for wearable IoT-based applications: a survey

  Authors: F. Al-Turjman, I. Baali

  Transactions on Emerging Telecommunications Technologies • 2019

  A survey of machine learning methods applied to wearable Internet-of-Things applications.

• Predicting clinical outcomes in neuroblastoma with genomic data integration

  Authors: I. Baali, A. E. Acar, T. Aderinwale, S. HafezQorani, H. Kazan

  Biology Direct • 2018

  Integration of gene expression and aCGH data to improve prediction of survival and clinical outcome in neuroblastoma.

Skills