cv | Ghulam Murtaza

2019 - 2025

PhD

Brown University, GPA 4.0/4.0, Expected Graduation Spring 2025
2019 - 2021

Master's

Brown University, GPA 4.0/4.0
2015 - 2019

Bachelor's

Lahore University of Management Sciences, GPA 3.83/4.0

Deep Learning/ Machine Learning.
- Graph Neural Networks.
- Self and Semi Supervised learning frameworks.
- Contrastive learning.
Genomics.
- Bulk genomics (Hi-C, RNA-seq, ChIP-seq and ATAC-seq/DNAse-seq).
- Single-cell genomics (scRNA-seq and scHi-C).
- Spatial genomics.

2021 - Current
Research Assistant

Brown University
- Dissertation research with Ritambhara Singh. Developing novel graph based representations that align structural and sequential genomics in shared representation spaces.
2022 - 2023
Guest Researcher

National Institute of Standards and Technology (NIST)
- Collaborating with the GIAB team to analyze pancreatic tumor scATAC-seq, scRNA-seq, and Hi-C datasets to identify epigenetic and transcriptomic markers of tumor progression.
- Built a benchmarking platform that comprehensively evalutes the performance trade-offs between existing Hi-C resolution improvement frameworks.
2019 - 2021
Research Assistant

Brown University
- Developed a causal model for web page loading process that provided detailed performance insights into interactions between the device hardware, network conditions, webpage content and optimizations.
2018 - 2019
Research Assistant

Lahore University of Management Sciences
- I was working under Dr Ihsan Ayyub Qazi to quantify the impact of memory bottlenecks in context of low-end devices in developing regions.
2017 and 2016
Research Intern

Lahore University of Management Sciences
- Assisted members of Bioinformatics lab under supervision of Dr Aziz Mithani on various research projects to improve the memory footprint or runtime.

Programming: Python, R, C, C++, SQL, Javascript, Go, Java
Frameworks: Pandas, NumPy, Matplotlib, PyTorch, Tensorflow, scikit-learn, XGBoost, Keras, Bowtie, Scanpy, Seurat
Developer Tools: Git, Docker, Singularity, Slurm, Snakemake, Nextflow, Hadoop, pySpark, AWS, GCP, Azure

Talk at ISMB 2024 - scGrapHiC Deep learning-based graph deconvolution for Hi-C using single cell gene expression
Poster at RECOMB 2024 - scGrapHiC Deep learning-based graph deconvolution for Hi-C using single cell gene expression
Poster at WABI 2023 - GEGGE A Graph Encoder for Generalized Genomics Embeddings
Talk at BioKDD 2023 - GrapHiC An integrative graph based approach for imputing missing Hi-C reads
Poster at ISMB 2023 - GrapHiC An integrative graph based approach for imputing missing Hi-C reads
Poster at GRC 2023 - GrapHiC An integrative graph based approach for imputing missing Hi-C reads
Poster at MLCB 2022 - GrapHiC An integrative graph based approach for imputing missing Hi-C reads
Flash Talk at CONEXT 2020 - WebOptProfiler Providing performance clarity for Mobile Webpage Optimizations

Keya Kilachand - Modeling cell cycles in single-cell Hi-C data with Hamiltonian Neural Networks
Xiaoke Song - Extracting features from single-cell Hi-C for accurate multi-modal integration and alignment
Winston Li - Evaluating Contrastive learning based approaches for scRNA-seq
Byron Butaney - Evaluating efficacy of large single-cell RNA-seq models in capturing higher order biological semantics

2018
- CS202 Data Structures - Lahore University of Management Sciences
2017
- CS100 Computational Problem Solving - Lahore University of Management Sciences