Asif Rahman

My interests are at the interface of machine learning and digital health. Currently, I am a scientist at Apple. Previously I worked on applications of machine learning in healthcare at Philips Research with a special interest in bio-signal processing, patient similarity, and incorporating prior knowledge into AI models. I obtained my PhD in neural engineering and was an algorithms scientist at Stitch Fix where I worked on deep learning computer vision systems.

Research topics

  1. Bio-signal processing →
  2. Disease phenotyping →
  3. Patient similarity →
  4. Interpretable machine learning →

1. Bio-signal processing

I specialize in deep learning algorithms for physiological signals collected from wearable devices, including electrocardiograms (ECG), photoplethysmography (PPG), phonocardiograms (PCG, heart sounds), and arterial blood pressure (ABP). Many of these solutions have been productionized and come in first place at the PhysioNet Challenges.See publications below.

2. Disease Phenotyping

I built realtime clinical risk algorithms that are deployed on patient monitors and central stations.

3. Patient similarity

Patient similarity aims to find cohorts based on vital signs, labs, medical history, and treatments for case-based reasoning.

4. Interpretable machine learning

A key requirement of clinical models is that they have to be explainable so that the nurse or clinician can understand the risk factors. The models should also be editable so we can identify when then algorithm makes an error and fix it before deployment.


2022 Neural gradient boosting in federated learning for hemodynamic instability prediction: towards a distributed and scalable deep learning-based solution
2022 Offline Off-Policy Reinforcement Learning to Optimize Fluid Management in Critical Care
2021 Early prediction of hemodynamic interventions in the intensive care unit using machine learning
2021 Interpretable Additive Recurrent Neural Networks For Multivariate Clinical Time Series
2021 Utilizing machine learning to improve clinical trial design for acute respiratory distress syndrome
2020 Phenotyping with Prior Knowledge using Patient Similarity
2020 A Wide and Deep Transformer Neural Network for 12-Lead ECG Classification
2020 Direct current stimulation boosts hebbian plasticity in vitro
2019 A Multi-Task Imputation and Classification Neural Architecture for Early Prediction of Sepsis from Multivariate Clinical Time Series
2018 Densely connected convolutional networks for detection of atrial fibrillation from short single-lead ECG recordings
2018 Analyzing single-lead short ECG recordings using dense convolutional neural networks and feature-based post-processing to detect atrial fibrillation
2018 An ensemble boosting model for predicting transfer to the pediatric intensive care unit
2017 Patient Similarity Using Population Statistics and Multiple Kernel Learning
2016 Ensemble of feature-based and deep learning-based classifiers for detection of abnormal heart sounds
2016 Animal models of transcranial direct current stimulation: methods and mechanisms
2015 Reliability of repeated TMS measures in older adults and in patients with subacute and chronic stroke
2017 Direct current stimulation alters neuronal input/output function
2017 Direct current stimulation boosts synaptic gain and cooperativity in vitro
2015 Modeling sequence and quasi-uniform assumption in computational neurostimulation
2015 Multilevel computational models for predicting the cellular effects of noninvasive brain stimulation
2015 Methods for specific electrode resistance measurement during transcranial direct current stimulation
2014 Clinician accessible tools for GUI computational models of transcranial electrical stimulation: BONSAI and SPHERES
2014 Polarizing cerebellar neurons with transcranial direct current stimulation
2013 Origins of specificity during tDCS: anatomical, activity-selective, and input-bias mechanisms
2013 Cellular effects of acute direct current stimulation: somatic and synaptic terminal effects
2013 The “quasi-uniform” assumption in animal and computational models of non-invasive electrical stimulation
2013 Methods for extra-low voltage transcranial direct current stimulation: current and time dependent impedance decreases
2013 Effects of weak transcranial Alternating Current Stimulation on brain activity–a review of known mechanisms from animal studies
2012 Computational models of transcranial direct current stimulation
2012 Axon terminal polarization induced by weak uniform DC electric fields: a modeling study
2012 Temperature control at DBS electrodes using a heat sink: experimentally validated FEM model of DBS lead architecture
2012 High-resolution modeling assisted design of customized and individualized transcranial direct current stimulation protocols
2010 Low-intensity electrical stimulation affects network dynamics by modulating population rate and spike timing
2010 Electrode montages for tDCS and weak transcranial electrical stimulation: role of “return” electrode’s position and size

See all publications on Google Scholar


2022 Patient subtyping from disease progression trajectories
2021 General and personal patient risk prediction
2019 Method for transforming patient data into images for infection prediction
2018 Learning and applying contextual similarities between entities
2018 Person identification systems and methods
2018 Discretized embeddings of physiological waveforms
2018 Detecting atrial fibrillation using short single-lead ecg recordings
2017 Using a neural network
2017 Classifier ensemble for detection of abnormal heart sounds
2012 Voltage limited neurostimulation


Feb 2023 Time series similarity with random convolutional features and locality-sensitive hashing
Jun 2022 Audio biosignal processing of phonocardiograms
Apr 2022 Heart Rate Variability and Atrial Fibrillation
Mar 2022 Python project setup
Feb 2022 ECG beat detection algorithm
Feb 2022 Types of health data
Jan 2022 Cosine similarity 1D convolutions
Jan 2022 Group-by and count in Numpy
Jan 2022 Separable temporal convolutions
Dec 2021 Challenges in Machine Learning for Health
Oct 2021 Quantile binning with missing data
Sept 2021 Ensemble decision trees in Numba
Sept 2021 Feature engineering for time series data using Numba
Aug 2021 Select a random window of maximum duration in NumPy
Feb 2021 Causal inference learners
Jul 2020 Offline Off-Policy Reinforcement Learning with Contextual Bandits
Jul 2020 Univariate Risk Curves
Jun 2020 Transform Grouped Pandas DataFrame to Numpy Array
Jun 2020 AWS Lambda Web Scraper
Jun 2020 Deploy static website with rsync
May 2020 Svelte Webpack Boilerplate
Dec 2018 Arrhythmia classification with stationary first order Markov process
Dec 2018 Nowcasting: Maintaining real time estimates of infrequently observed time series
Feb 2016 State space models and the Kalman filter
May 2015 Pandoc static site generator
Dec 2014 Data science at the command line
Aug 2014 Punchcard visualization using D3.js
Mar 2014 Data Mining PubMed