Mohamed Tarek, PhD

Mohamed Tarek, PhD

Pharmacometrics · Statistics · ML · Topology Optimization
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Publications

Published research papers and conference proceedings.

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Conferences

  1. Early go/no-go decisions in clinical trials using a DeepNLME joint tumor growth dynamics and overall survival model, Population Approach Group in Europe (PAGE). June 5, 2026.  [abstract]  [slides]
  2. Using DeepNLME to identify promising biomarkers with an application to disease progression modelling of Alzheimer's disease, Population Approach Group in Europe (PAGE). June 4, 2026.  [abstract]  [poster]
  3. Multidimensional scaling for longitudinal data embeddings in pharmacometrics, Population Approach Group in Europe (PAGE). June 4, 2026.  [abstract]  [poster]
  4. Post-hoc model joining with normalizing flows for efficient and scalable multi-endpoint PKPD, Population Approach Group in Europe (PAGE). June 3, 2026.  [abstract]  [poster]
  5. Application of DeepNLME framework to characterize distinct platelet dynamics in patients treated with Milademetan, Population Approach Group in Europe (PAGE). June 3, 2026.  [abstract]  [poster]
  6. Metric multi-dimensional scaling for longitudinal data embeddings in pharmacometrics, ICLR Workshop on Geometry-grounded Representation Learning and Generative Modeling. April 25-26, 2026.  [openreview]  [paper]
  7. A Deep Dive into Generative Scientific Machine Learning, 2nd Bonn Conference on Mathematical Life Sciences. March 18, 2026.  [slides]
  8. Finding complex relationships between random effects and covariates using data-driven distributions, American Conference on Pharmacometrics (ACoP). Oct 21, 2025.
  9. Machine Learning For Exploratory Data Analysis And Model Diagnosis In Oncology, American Conference on Pharmacometrics (ACoP). Oct 19, 2025.  [poster]
  10. A DeepNLME framework for modeling ordinal data to describe disease progression in patients with Alzheimer's disease, Population Approach Group in Europe (PAGE). Jun 6, 2025.  [abstract]  [slides]
  11. A DeepNLME-based Tumor Growth Dynamics and Overall Survival Model for Non Small Cell Lung Cancer, American Conference on Pharmacometrics (ACoP). Nov 12, 2024.  [abstract]  [poster]
  12. Make models great again by optimally restricting parameters to make non-identifiable models provably identifiable, Population Approach Group in Europe (PAGE). Jun 28, 2024.  [abstract]  [slides]
  13. Bayesian Pharmacometric Software Benchmarks, American Conference on Pharmacometrics (ACoP). Nov 7, 2023.  [github]  [poster]
  14. DeepPumas for automatic discovery of individualizable functions governing longitudinal patient outcomes, Population Approach Group in Europe (PAGE). Jun 27, 2023.  [abstract]  [poster]
  15. Fast cross-validation for Bayesian inference using proposals on a linear subspace, Population Approach Group in Europe (PAGE). Jun 27, 2023.  [abstract]  [poster]
  16. Marginal No-U-Turn Sampler for Bayesian Analysis in Pharmacometrics, Population Approach Group in Europe (PAGE). Jun 27, 2023.  [abstract]  [poster]
  17. A Complete Bayesian Workflow in Pumas, Population Approach Group in Australia and New Zealand (PAGANZ). Jan 20, 2023.  [abstract]  [slides]
  18. ImplicitDifferentiation.jl: Differentiating Implicit Functions, JuliaCon. Jul 29, 2022.  [youtube]  [software]
  19. AbstractDifferentiation.jl: Backend-Agnostic Differentiable Programming in Julia, Differentiable Programming NeurIPS Workshop. Dec 13, 2021.  [abstract]  [openreview]  [paper]  [software]
  20. Nonlinear mixed effects model based optimal design of experiments using mathematical programming in Pumas, American Conference on Pharmacometrics (ACoP). Nov 9, 2021.  [abstract]  [poster]
  21. Non-Gaussian random effects in nonlinear mixed effects models in Pumas, American Conference on Pharmacometrics (ACoP). Nov 9, 2021.  [abstract]  [poster]
  22. Parallel hierarchical Gibbs-NUTS MCMC algorithm for Nonlinear Mixed Effects models in Pumas, American Conference on Pharmacometrics (ACoP). Nov 9, 2021.  [abstract]  [poster]
  23. Subspace MCMC algorithm for Bayesian parameter estimation of hierarchical PK/PD models in Pumas, Population Approach Group in Europe (PAGE). Sep 7, 2021.  [abstract]  [poster]
  24. Nonconvex.jl, JuMP-dev Workshop. Jul 30, 2021.  [youtube]  [software]
  25. TopOpt.jl: topology optimization done right, JuliaCon. Jul 29, 2021.  [youtube]  [software]
  26. TopOpt.jl: Truss and Continuum Topology Optimization - Interactive Visualization, Automatic Differentiation and More, World Congress of Structural and Multidisciplinary Optimization (WCSMO) 14. Jun 16, 2021.  [abstract]  [software]
  27. Bayesian Neural Ordinary Differential Equations, Languages for Inference (LAFI). Jan 15, 2021.  [abstract]  [youtube]
  28. Analysis of Laplace Approximation for Pharmaceutical Nonlinear Mixed Effects Models, Population Approach Group of Australia and New Zealand (PAGANZ). Jan 7, 2021.
  29. DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models, JuliaCon. Jul 31, 2020.  [youtube]  [software]
  30. AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms, The International Conference on Probabilistic Programming (PROBPROG). Jan 1, 2020.  [poster]  [software]
  31. DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models, The International Conference on Probabilistic Programming (PROBPROG). Jan 1, 2020.  [poster]  [software]
  32. AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms, 2nd Symposium on Advances in Approximate Bayesian Inference (AABI). Jan 1, 2019.  [proceedings]  [paper]  [software]
  33. Bijectors.jl: Flexible transformations for probability distributions, 2nd Symposium on Advances in Approximate Bayesian Inference (AABI). Jan 1, 2019.  [proceedings]  [paper]  [software]
  34. AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms, StanCon. August 20-23, 2019.  [poster]  [software]
  35. TopOpt.jl: An efficient and high-performance package for topology optimization of continuum structures in the Julia programming language, The World Congress of Structural and Multidisciplinary Optimization (WCSMO) 13. Jan 1, 2019.  [software]
  36. Topology Optimization and JuMP, JuMP-dev Workshop. Jul 28, 2018.  [abstract]  [slides]  [youtube]

Journals

  1. Turing.jl: a general-purpose probabilistic programming language, ACM Transactions on Probabilistic Machine Learning (TPML). Feb 14, 2025.  [journal]  [software]
  2. Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). Mar 20, 2024.  [journal]
  3. Approximation schemes for stochastic compliance-based topology optimization with many loading scenarios, Structural and Multidisciplinary Optimization (SMO). Apr 13, 2022.  [journal]
  4. Robust and stochastic compliance-based topology optimization with finitely many loading scenarios, Structural and Multidisciplinary Optimization (SMO). Sept 26, 2021.  [journal]
  5. Adaptive continuation solid isotropic material with penalization for volume constrained compliance minimization, Computer Methods in Applied Mechanics and Engineering (CMAME). May 1, 2020.  [journal]

Preprints

  1. Fitting Large Nonlinear Mixed Effects Models Using Variational Expectation Maximization, arXiv. Apr 28, 2026.  [arxiv]  [preprint]
  2. Nonconvex.jl: A Comprehensive Julia Package for Non-Convex Optimization, ResearchGate. July 13, 2023.  [researchgate]  [preprint]  [software]
  3. Earth Movers in The Big Data Era: A Review of Optimal Transport in Machine Learning, arXiv. May 8, 2023.  [arxiv]  [preprint]
  4. A Practitioner's Guide to Bayesian Inference in Pharmacometrics using Pumas, arXiv. Mar 31, 2023.  [arxiv]  [preprint]
  5. Preconditioners.jl: A Flexible and Extensible Framework for Preconditioning in Iterative Solvers, ResearchGate. Feb 25, 2023.  [researchgate]  [preprint]  [software]
  6. Accelerated Predictive Healthcare Analytics with Pumas, A High Performance Pharmaceutical Modeling and Simulation Platform, bioRxiv. Mar 20, 2022.  [biorxiv]  [preprint]  [software]
  7. Bayesian Neural Ordinary Differential Equations, arXiv. Feb 6, 2022.  [arxiv]  [preprint]
  8. AbstractDifferentiation.jl: Backend-Agnostic Differentiable Programming in Julia, arXiv. Feb 4, 2022.  [arxiv]  [preprint]  [software]
  9. Simplifying deflation for non-convex optimization with applications in Bayesian inference and topology optimization, arXiv. Jan 28, 2022.  [arxiv]  [preprint]
  10. Some popular nonlinear programming algorithms, ResearchGate. Oct 18, 2021.  [researchgate]  [preprint]
  11. Approximation schemes for stochastic compliance-based topology optimization with many loading scenarios, arXiv. Aug 8, 2021.  [arxiv]  [preprint]
  12. Robust and stochastic compliance-based topology optimization with finitely many loading scenarios, arXiv. Mar 8, 2021.  [arxiv]  [preprint]
  13. DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models, arXiv. Feb 7, 2020.  [arxiv]  [preprint]  [software]

2026

  1. Early go/no-go decisions in clinical trials using a DeepNLME joint tumor growth dynamics and overall survival model, Population Approach Group in Europe (PAGE). June 5, 2026.  [abstract]  [slides]
  2. Using DeepNLME to identify promising biomarkers with an application to disease progression modelling of Alzheimer's disease, Population Approach Group in Europe (PAGE). June 4, 2026.  [abstract]  [poster]
  3. Multidimensional scaling for longitudinal data embeddings in pharmacometrics, Population Approach Group in Europe (PAGE). June 4, 2026.  [abstract]  [poster]
  4. Post-hoc model joining with normalizing flows for efficient and scalable multi-endpoint PKPD, Population Approach Group in Europe (PAGE). June 3, 2026.  [abstract]  [poster]
  5. Application of DeepNLME framework to characterize distinct platelet dynamics in patients treated with Milademetan, Population Approach Group in Europe (PAGE). June 3, 2026.  [abstract]  [poster]
  6. Fitting Large Nonlinear Mixed Effects Models Using Variational Expectation Maximization, arXiv. Apr 28, 2026.  [arxiv]  [preprint]
  7. Metric multi-dimensional scaling for longitudinal data embeddings in pharmacometrics, ICLR Workshop on Geometry-grounded Representation Learning and Generative Modeling. April 25-26, 2026.  [openreview]  [paper]
  8. A Deep Dive into Generative Scientific Machine Learning, 2nd Bonn Conference on Mathematical Life Sciences. March 18, 2026.  [slides]

2025

  1. Finding complex relationships between random effects and covariates using data-driven distributions, American Conference on Pharmacometrics (ACoP). Oct 21, 2025.
  2. Machine Learning For Exploratory Data Analysis And Model Diagnosis In Oncology, American Conference on Pharmacometrics (ACoP). Oct 19, 2025.  [poster]
  3. A DeepNLME framework for modeling ordinal data to describe disease progression in patients with Alzheimer's disease, Population Approach Group in Europe (PAGE). Jun 6, 2025.  [abstract]  [slides]
  4. Turing.jl: a general-purpose probabilistic programming language, ACM Transactions on Probabilistic Machine Learning (TPML). Feb 14, 2025.  [journal]  [software]

2024

  1. A DeepNLME-based Tumor Growth Dynamics and Overall Survival Model for Non Small Cell Lung Cancer, American Conference on Pharmacometrics (ACoP). Nov 12, 2024.  [abstract]  [poster]
  2. Make models great again by optimally restricting parameters to make non-identifiable models provably identifiable, Population Approach Group in Europe (PAGE). Jun 28, 2024.  [abstract]  [slides]
  3. Scalable Optimal Transport Methods in Machine Learning: A Contemporary Survey, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). Mar 20, 2024.  [journal]

2023

  1. Bayesian Pharmacometric Software Benchmarks, American Conference on Pharmacometrics (ACoP). Nov 7, 2023.  [github]  [poster]
  2. Nonconvex.jl: A Comprehensive Julia Package for Non-Convex Optimization, ResearchGate. July 13, 2023.  [researchgate]  [preprint]  [software]
  3. DeepPumas for automatic discovery of individualizable functions governing longitudinal patient outcomes, Population Approach Group in Europe (PAGE). Jun 27, 2023.  [abstract]  [poster]
  4. Fast cross-validation for Bayesian inference using proposals on a linear subspace, Population Approach Group in Europe (PAGE). Jun 27, 2023.  [abstract]  [poster]
  5. Marginal No-U-Turn Sampler for Bayesian Analysis in Pharmacometrics, Population Approach Group in Europe (PAGE). Jun 27, 2023.  [abstract]  [poster]
  6. Earth Movers in The Big Data Era: A Review of Optimal Transport in Machine Learning, arXiv. May 8, 2023.  [arxiv]  [preprint]
  7. A Practitioner's Guide to Bayesian Inference in Pharmacometrics using Pumas, arXiv. Mar 31, 2023.  [arxiv]  [preprint]
  8. Preconditioners.jl: A Flexible and Extensible Framework for Preconditioning in Iterative Solvers, ResearchGate. Feb 25, 2023.  [researchgate]  [preprint]  [software]
  9. A Complete Bayesian Workflow in Pumas, Population Approach Group in Australia and New Zealand (PAGANZ). Jan 20, 2023.  [abstract]  [slides]

2022

  1. ImplicitDifferentiation.jl: Differentiating Implicit Functions, JuliaCon. Jul 29, 2022.  [youtube]  [software]
  2. Approximation schemes for stochastic compliance-based topology optimization with many loading scenarios, Structural and Multidisciplinary Optimization (SMO). Apr 13, 2022.  [journal]
  3. Accelerated Predictive Healthcare Analytics with Pumas, A High Performance Pharmaceutical Modeling and Simulation Platform, bioRxiv. Mar 20, 2022.  [biorxiv]  [preprint]  [software]
  4. Bayesian Neural Ordinary Differential Equations, arXiv. Feb 6, 2022.  [arxiv]  [preprint]
  5. AbstractDifferentiation.jl: Backend-Agnostic Differentiable Programming in Julia, arXiv. Feb 4, 2022.  [arxiv]  [preprint]  [software]
  6. Simplifying deflation for non-convex optimization with applications in Bayesian inference and topology optimization, arXiv. Jan 28, 2022.  [arxiv]  [preprint]

2021

  1. AbstractDifferentiation.jl: Backend-Agnostic Differentiable Programming in Julia, Differentiable Programming NeurIPS Workshop. Dec 13, 2021.  [abstract]  [openreview]  [paper]  [software]
  2. Nonlinear mixed effects model based optimal design of experiments using mathematical programming in Pumas, American Conference on Pharmacometrics (ACoP). Nov 9, 2021.  [abstract]  [poster]
  3. Non-Gaussian random effects in nonlinear mixed effects models in Pumas, American Conference on Pharmacometrics (ACoP). Nov 9, 2021.  [abstract]  [poster]
  4. Parallel hierarchical Gibbs-NUTS MCMC algorithm for Nonlinear Mixed Effects models in Pumas, American Conference on Pharmacometrics (ACoP). Nov 9, 2021.  [abstract]  [poster]
  5. Some popular nonlinear programming algorithms, ResearchGate. Oct 18, 2021.  [researchgate]  [preprint]
  6. Robust and stochastic compliance-based topology optimization with finitely many loading scenarios, Structural and Multidisciplinary Optimization (SMO). Sept 26, 2021.  [journal]
  7. Subspace MCMC algorithm for Bayesian parameter estimation of hierarchical PK/PD models in Pumas, Population Approach Group in Europe (PAGE). Sep 7, 2021.  [abstract]  [poster]
  8. Approximation schemes for stochastic compliance-based topology optimization with many loading scenarios, arXiv. Aug 8, 2021.  [arxiv]  [preprint]
  9. Nonconvex.jl, JuMP-dev Workshop. Jul 30, 2021.  [youtube]  [software]
  10. TopOpt.jl: topology optimization done right, JuliaCon. Jul 29, 2021.  [youtube]  [software]
  11. TopOpt.jl: Truss and Continuum Topology Optimization - Interactive Visualization, Automatic Differentiation and More, World Congress of Structural and Multidisciplinary Optimization (WCSMO) 14. Jun 16, 2021.  [abstract]  [software]
  12. Robust and stochastic compliance-based topology optimization with finitely many loading scenarios, arXiv. Mar 8, 2021.  [arxiv]  [preprint]
  13. Bayesian Neural Ordinary Differential Equations, Languages for Inference (LAFI). Jan 15, 2021.  [abstract]  [youtube]
  14. Analysis of Laplace Approximation for Pharmaceutical Nonlinear Mixed Effects Models, Population Approach Group of Australia and New Zealand (PAGANZ). Jan 7, 2021.

2020

  1. DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models, JuliaCon. Jul 31, 2020.  [youtube]  [software]
  2. Adaptive continuation solid isotropic material with penalization for volume constrained compliance minimization, Computer Methods in Applied Mechanics and Engineering (CMAME). May 1, 2020.  [journal]
  3. DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models, arXiv. Feb 7, 2020.  [arxiv]  [preprint]  [software]
  4. AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms, The International Conference on Probabilistic Programming (PROBPROG). Jan 1, 2020.  [poster]  [software]
  5. DynamicPPL: Stan-like Speed for Dynamic Probabilistic Models, The International Conference on Probabilistic Programming (PROBPROG). Jan 1, 2020.  [poster]  [software]

2019

  1. AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms, StanCon. August 20-23, 2019.  [poster]  [software]
  2. AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms, 2nd Symposium on Advances in Approximate Bayesian Inference (AABI). Jan 1, 2019.  [proceedings]  [paper]  [software]
  3. Bijectors.jl: Flexible transformations for probability distributions, 2nd Symposium on Advances in Approximate Bayesian Inference (AABI). Jan 1, 2019.  [proceedings]  [paper]  [software]
  4. TopOpt.jl: An efficient and high-performance package for topology optimization of continuum structures in the Julia programming language, The World Congress of Structural and Multidisciplinary Optimization (WCSMO) 13. Jan 1, 2019.  [software]

2018

  1. Topology Optimization and JuMP, JuMP-dev Workshop. Jul 28, 2018.  [abstract]  [slides]  [youtube]