publications

publications by categories in reversed chronological order. for a more complete list check my google scholar

2023

  1. Efficiently Computing Sparse Fourier Transforms of q -ary Functions
    Yigit Efe Erginbas, Justin Singh Kang, Amirali Aghazadeh, and Kannan Ramchandran
    arXiv:2301.06200 2023

2022

  1. Current progress and open challenges for applying deep learning across the biosciences
    Nicolae Sapoval, Amirali Aghazadeh, Michael G Nute, Dinler A Antunes, Advait Balaji, and 6 more authors
    Nature Communications 2022
  2. On the sparsity of fitness functions and implications for learning
    David H Brookes, Amirali Aghazadeh, and Jennifer Listgarten
    Proceedings of the National Academy of Sciences (PNAS) 2022
  3. BEAR: Sketching BFGS Algorithm for Ultra-High Dimensional Feature Selection in Sublinear Memory
    Amirali Aghazadeh, Vipul Gupta, Alex DeWeese, Ozan Koyluoglu, and Kannan Ramchandran
    In Mathematical and Scientific Machine Learning (MSML) 2022
  4. Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces
    Amirali Aghazadeh, Nived Rajaraman, Tony Tu, and Kannan Ramchandran
    arXiv:2210.02604 2022

2021

  1. Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions
    Amirali Aghazadeh, Hunter Nisonoff, Orhan Ocal, David H Brookes, Yijie Huang, and 3 more authors
    Nature Communications 2021
  2. Group-Structured Adversarial Training
    Farzan Farnia, Amirali Aghazadeh, James Zou, and David Tse
    arXiv:2106.10324 2021
  3. Anomalous nanoparticle surface diffusion in LCTEM is revealed by deep learning-assisted analysis
    Vida Jamali, Cory Hargus, Assaf Ben-Moshe, Amirali Aghazadeh, Hyun Dong Ha, and 2 more authors
    Proceedings of the National Academy of Sciences 2021

2020

  1. CRISPRLand: Interpretable large-scale inference of DNA repair landscape based on a spectral approach
    Amirali Aghazadeh, Orhan Ocal, and Kannan Ramchandran
    Bioinformatics 2020

2019

  1. Large dataset enables prediction of repair after CRISPR–Cas9 editing in primary T cells
    Ryan T Leenay, Amirali Aghazadeh, Joseph Hiatt, David Tse, Theodore L Roth, and 6 more authors
    Nature Biotechnology 2019
  2. Data-driven semi-supervised and supervised learning algorithms for health monitoring of pipes
    Debarshi Sen, Amirali Aghazadeh, Ali Mousavi, Satish Nagarajaiah, Richard Baraniuk, and 1 more author
    Mechanical Systems and Signal Processing 2019
  3. Sparsity-based approaches for damage detection in plates
    Debarshi Sen, Amirali Aghazadeh, Ali Mousavi, Satish Nagarajaiah, and Richard Baraniuk
    Mechanical Systems and Signal Processing 2019

2018

  1. MISSION: Ultra large-scale feature selection using Count Sketches
    Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, and 1 more author
    In International Conference on Machine Learning (ICML) 2018
  2. Insense: Incoherent sensor selection for sparse signals
    Amirali Aghazadeh, Mohammad Golbabaee, Andrew Lan, and Richard Baraniuk
    Signal Processing 2018

2017

  1. Rhash: Robust hashing via l∞-norm distortion
    Amirali Aghazadeh, Andrew Lan, Anshumali Shrivastava, and Richard Baraniuk
    In International Joint Conference on Artificial Intelligence (IJCAI) 2017
  2. Machine Learning in Large-scale Genomics: Sensing, Processing, and Analysis
    Amirali Aghazadeh
    2017

2016

  1. Universal microbial diagnostics using random DNA probes
    Amirali Aghazadeh, Adam Y Lin, Mona A Sheikh, Allen L Chen, Lisa M Atkins, and 4 more authors
    Science Advances 2016

2013

  1. Adaptive step size selection for optimization via the ski rental problem
    Amirali Aghazadeh, Ali Ayremlou, Daniel D Calderón, Tom Goldstein, Raajen Patel, and 2 more authors
    In International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2013