Joseph Cave Email & Phone Number

Houston, Texas, United States

• Developed PBPK models using MATLAB and SimBiology with mass-balanced ODEs to predict drug ADME and optimize nanoparticle (NP) therapeutic delivery systems, calibrating parameters with in vitro and in vivo pharmacology.
• Created mechanistic PK/PD models to simulate disease progression under immunotherapy, chemotherapy, and micro-RNA treatments, identifying 3 synergistic drug combinations and optimal dosing schedules for NSCLC.
• Conducted local and global sensitivity analyses, pinpointing key PBPK model parameters affecting drug biodistribution.
• Generated virtual populations via Latin Hypercube Sampling and Monte Carlo simulations to improve population-scale PK predictions.
• Translated preclinical PK data to human parameters using allometric scaling, evaluating clinical endpoints (e.g., PFS, OS), and optimizing dose regimens to enhance therapeutic efficacy.
• Utilized nonlinear mixed-effects modeling (popPK) with NONMEM to analyze inter-patient variability in drug concentrations from clinical data, informing clinical decision-making.

Coventry, England, United Kingdom

• Spearheaded the development of Graph Convolutional Networks (GCN) using Keras and TensorFlow for classifying lymphatic tissue micro-environments from 3D cell surface data, achieving ~85% accuracy.
• Managed diverse data types, including Whole Slide Images (WSIs) and genotype data, to classify cell phenotypes and infer gene expression levels, showcasing expertise in data handling and interdisciplinary analysis.
• Implemented dimensionality reduction techniques, specifically variational autoencoders (VAEs), to handle high-resolution WSI data, significantly enhancing computational efficiency and model performance.
• Enhanced dataset size by 50% through synthetic data generation with VAEs (via learning latent space representations) and generative adversarial networks (GANs), facilitating more robust model predictions.
• Optimized GCN by leveraging transfer learning for performance improvements and benchmarked against existing computational models (‘GraphSAGE,’ ‘attri2vec’).
• Collaborated across 4 different labs, fostering a multidisciplinary approach to development.

Coventry, England, United Kingdom

- Systematically researched the sustainability of FMCW RADAR and optical automotive perception sensors.- Analyzed and elected PCB materials to prolong lifespan and wear-out for next-generation FMCW RADAR sensors.- Investigated and refined current manufacturing methods utilized to mitigate the causes of sensor ageing and malfunctioning.- Established a.

Coventry, England, United Kingdom

• Investigated mathematical models to assess the impact of confining halide perovskites in Single-Walled Carbon Nanotubes (SWCNTs) on electrical properties and bandgap, demonstrating advanced computational and analytical.
• Conducted XRD on 30+ samples to assess crystalline structures and measure bandgap modifications for model validation.
• Applied advanced microscopy techniques (SEM/TEM) to characterize SWCNT-perovskite composites and EDS for elemental composition analysis of halide perovskites within CNTs, showcasing meticulous technical expertise.
• Employed MATLAB and Python for advanced image processing, including Gaussian blurring and Fast Fourier Transforms.
• Utilized Materials Studio and LAMMPS for nanocrystal simulation, modeling atomic interactions to predict electronic properties influenced by SWCNT characteristics, demonstrating proficiency in grasping new concepts and.

Krakowski, Małopolskie, Poland

• Redesigned a Supervisory Control and Data Acquisition (SCADA) GUI system for AFP detectors within the ATLAS accelerator using Linux, the Joint Controls Project (JCOP) framework, and Siemens WinCC OA tools.
• Significantly reduced data latency and enhanced the ATLAS Forward Proton detector's spatial and temperature sensor feedback accuracy through programming specialized functions using C.
• Installed and configured the SCADA interface for operators in the ATLAS control room, ensuring seamless integration with existing systems while meticulously documenting the development processes to facilitate.
• Demonstrated capacity to work collaboratively and communicate effectively in a demanding international research environment, culminating in an award-winning project.
• Integral part of daily operations and is actively used by technicians and operators in the particle accelerator's control room, demonstrating sustained impact on high-energy physics research.

Redruth, England, United Kingdom

• Awarded a Nuffield Foundation Fellowship for research at Bluefruit Software, focusing on medical image processing efficiency.
• Developed a memory-efficient compressed file system for Philips ultrasound systems using C on Linux, improving storage and retrieval processes for high-resolution images.
• Implemented Huffman coding and utilized cyclomatic complexity equations to optimize data compression without compromising image quality and system efficiency.
• Employed C/C++, Python, ‘Zlib’/’Gzip’ for compression, and ‘OpenSSL’ for data security.
• Integrated POSIX Threads for enhanced multi-threading capabilities and conducted comprehensive benchmarking with ‘iozone’ and ‘fio’.
• Utilized Docker to simulate varied operating conditions and executed extensive stability, load, and scalability tests to ensure reliability and performance under real-world conditions.

Doctor Of Philosophy - Phd, Physiology, Biophysics, And Systems Biology (Pbsb)

Master Of Science - Ms, Computer Science

Bachelor'S Degree, Physics