cv

Murtaza's curriculum vitae, please download my latest one page resume from the button on the right.

Education

  • 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

Academic Interests

  • Deep Learning/ Machine Learning.
    • Graph Neural Networks.
    • Self and Semi Supervised learning frameworks.
    • Contrastive learning.
    • Representation 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.

Experience

  • 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)
    • 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. Published our system and findings at HotMobile2021 [https://dl.acm.org/doi/abs/10.1145/3446382.3449073].
  • 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. We published our findings at ACM SIGCOMM CCR [https://ccronline.sigcomm.org/2020/ccr-october-2020/mobile-web-browsing-under-memory-pressure/]. As a part of our broad aim of democratizing the access to emerging technology, we also developed a messaging network stack over the existing cellular networks to send few bits of information encoded under a missed call duration to provide an interface to people to communicate without any charges. We built survey and remote learning application on top of this framework to exploit the underlying asymmetry in financial resources to move the communication overhead to the person who can pay. We published our work at ACM CHI MissIt, Using Missed Calls for Free, Extremely Low Bit-Rate Communication in Developing Regions CHI '20 Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems [https://dl.acm.org/doi/10.1145/3313831.3376259]
  • 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.

Skills

  • Programming: C, C++, Python, Javascript, GoLang, Java, SQL, R.
  • Frameworks: Pytorch, Tensorflow, JAX, Pytorch Geometric, NLTK, Spark, Hadoop, Docker.
  • Bioinformatics Pipelines: Bioconductor, Juicer, Coolertools, BWA, Bedtools, pyMol.

Invited talks and Poster Presentations

  • 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

Currently Advising

  • Winston Li - We are developing a continuous learning framework that imposes strict structure in the latent space to improve meta-label learning when extrapolating to unseen tasks.
  • Byron Butaney - We are building a benchmarking framework that tests whether the Large Language Model (LLM) style scRNA-seq models can correctly assemble cells based on i) cell-cycle phases (structure) ii) spatial positing and iii) temporal cell-differentiation trajectories.
  • Wangdrak Dorji - We are developing a novel protein representation that embeds dynamical properties of proteins through Anistropic Network Model (ANM). We show that by including dynamical properties we can improve protein-protein interactions accuracy performance in comparison to representations that rely solely on structure or sequence.

Past Mentorship Experience

  • Madeline Hughes - Pre-Doctoral Research Assistant at Microsoft Research
  • Thulasi Varatharajan - Masters student at North Eastern
  • Abdul Manan - Graduate Student at Brown University
  • Abrar Tariq - Software Reliability Engineer (SRE) at Bytedance

Teaching Experience

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

Volunteer Service

  • Reviwer for MLCB - 2024
  • Reviwer for ICLR MLGenX - 2024
  • Brown Ph.D Admissions committee - 2023, 2024
  • Ritambhara Singh's sub-reviewer for ICML, RECOMB, ICLR - 2020 - Present
  • Served as a peer mentor for International Students at Brown - 2021
  • Mobin Javed's sub-reviewer for ACM Internet Measurements Conference
  • Served as a Medical First Responder for EMS at LUMS (2017 - 2019)

Honors and Awards

  • 2024
    • Brown sixth-year Dissertation Fellowship
  • 2019
    • Dean's Honor List - LUMS
  • 2017
    • Dean's Honor List - LUMS
  • 2016
    • Dean's Honor List - LUMS

Languages

  • Urdu (Native) and English (Fluent)

Other Interests

  • Hobbies: Tennis, Running, Biking, Swimming and Cooking.