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Education
Education
2019 - 2023 Ph.D. of Mechcanical Engineering
Purdue University Advisor: Prof. Arezoo M. Ardekani
2016 - 2019 M.S. of Fluid Mechanics
University of Science and Technology of China Advisor: Prof. Hang Ding & Prof. Nansheng Liu
2012 - 2016 B.S. of Aerospace Engineering
Nanjing University of Aeronautics and Astronautics Advisor: Prof. Changyue Xu
About
About
Dr. Han is an interdisciplinary researcher working at the intersection of computational biophysics, biotransport, compuational fluid dynamics, machine learning, and thermal imaging. She specializes in computatial modeling of drug delivery, thermal biophotonics, and viscoelastic fluids. Her overarching research interests lie in computational biophysics, biological transport, biomechanics, multiphase/multi-species flow, biological fluid flow, and the interaction of cells, proteins, and extracellular matrix (ECM), as well as developing novel and advanced imaging technology for biomedical applications. She has extensive experience solving interdisciplinary problems using high-fidelity numerical simulations, leading multiple interdisciplinary research projects with applications to drug delivery and health monitoring, collaborating with researchers who have different research backgrounds and skills.
After completing Ph.D. in Dr. Arezoo Ardekani's group, Dr. Han worked as a postdoctoral researcher in the Jia Lab for Systems Biophotonics in Wallace H. Coulter Department of Biomedical Engineering at the Georgia Institute of Technology. During her first year's postdoctoral research, she developed an innovative phasor-enabled hyperspectral thermal imaging system, named Phasor Thermography. Her research focused on integrating advanced hyperspectral imaging techniques, thermal radiation modeling, thermal phasor analysis, and phasor-enabled thermal unmixing to enhance non-invasive health monitoring and elucidate mechanisms of bioheat transport. Currently, she is working as a postdoctoral researcher in Dr. Susan Thomas' Lab, leveraging her expertise in computational modeling of lymphatic uptake, biomedical imaging, and machine learning to quantitatively simulate and investigate complex biological processes, biotransport, biomechanics, and biosystems, with applications to controlled drug release, drug delivery of biotherapeutics including nanoparticles, monoclonal antibodies, and other formulations, benefiting cancer theraphy, immunotherapy, lymphatic uptake, and lymphatic disturbed diseases treatment.
Dr. Han is also interested in data-driven computational modeling and physics-informed neural networks. She is interested in integrating machine learning with CFD and predictive computational modeling to improve computational efficiency regarding estimating parameters for biological processes and optimizing solutions. Leveraging artificial intelligence, computational modeling, and imaging physics, she aims to advance research in precision health, controlled drug delivery, non-invasive screening and biomedical diagnosis, and broad applications including medicine, sustainability, and biological and industrial processes.
Research
Research
Quantitative Biotransport and Computational Drug Delivery: Lymphatic transport and uptake
Hybrid tissue model embedded with explicit vessel network
Diffusive and convective transprot into the lymphatic system
Binding of drug molecules to the extracellular matrix slows down the drug absorption
Solute transport model across the lymphatic vessel memebrane
Paracellular transport taking into account of drug solute size and concentration gradient across the lymphatic vessel membrane
Modeling the primary valve opening under high interstitial fluid pressure difference
Sketch of subcutaneous injection
Drug distribution and lymphatic uptake
Comprehensive continuum model for solute transport and absorption in porous medium
Heterougeneous drug distribution and lymphatic uptake in multi-layered skin tissue
Computational Fluid Dynamics: Interface dynamics inside syringes for drug delivery device design
Qunatitatively investigate the role of fluid viscosity, air gap size, syringe acceleration, syringe tilt angle, liquid-wall contact angle, surface tension and fill volume on the interface dynamics
Optimization of drug delivery system
Computational Fluid Dynamics: Multiphase flow of non-newtonian fluids
Scaling law for viscoelastic droplet spreading
Velocity field and Normal stress distribution druign droplet impacting
A water drop bounces up after impacting on hydrophobic solid surfaces.
A PEO solution drop doesn't rebound after impacting on same surfaces.
Numerical simulation of multiphase flow of non-Newtonian fluids with a moving contact line
Validation against experimental data on the dynamics of polymer solution droplets impacting on super-hydrophobic substrates
Computational Imaging: Hyperspectral thermal imaging for biomedical applications
Hyperspectral phasor thermography for vital sign detection
Phasor-enabled analysis and thermal unmixing algorithms for advanced thermal vision, capturing precise material, vivid texture, and accurate temperature.
Machine learning algorithms for material segmentation and physical feature extraction.
Innovative phasor thermography is demonstrated in vital sign detection, including pulse and respiration rates, as well as subsurface imaging, i.e., subcutaneous vein pattern identification.
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