scispace - formally typeset
S

Savas Tasoglu

Researcher at Koç University

Publications -  132
Citations -  5349

Savas Tasoglu is an academic researcher from Koç University. The author has contributed to research in topics: Medicine & Computer science. The author has an hindex of 36, co-authored 100 publications receiving 4001 citations. Previous affiliations of Savas Tasoglu include University of Connecticut & Boğaziçi University.

Papers
More filters
Journal ArticleDOI

Bioprinting for stem cell research

TL;DR: Recent achievements with bioprinting technologies in stem cell research are reviewed, and future challenges and potential applications including tissue engineering and regenerative medicine, wound healing, and genomics are identified.
Journal ArticleDOI

Bioprinting for cancer research

TL;DR: 3D cancer models that mimic the tumor microenvironment are discussed, providing a platform for deeper understanding of cancer pathology, anticancer drug screening, and cancer treatment development.
Journal ArticleDOI

Untethered micro-robotic coding of three-dimensional material composition

TL;DR: This work describes a method to code complex materials in three-dimensions with tunable structural, morphological, and chemical features using an untethered magnetic micro-robot remotely controlled by magnetic fields, and demonstrates the coding of soft hydrogels, rigid copper bars, polystyrene beads, and silicon chiplets into three-dimensional heterogeneous structures.
Journal ArticleDOI

3D-printed microfluidic devices.

TL;DR: A broad range of approaches for the application of 3D printing technology to fabrication of micro-scale lab-on-a-chip devices are discussed, making microfluidics more accessible to users.
Journal ArticleDOI

Flow induces epithelial-mesenchymal transition, cellular heterogeneity and biomarker modulation in 3D ovarian cancer nodules

TL;DR: It is demonstrated that fluidic streams induce a motile and aggressive tumor phenotype, and the microfluidic platform developed here potentially provides a flow-informed framework complementary to conventional mechanism-based therapeutic strategies, with broad applicability to other lethal malignancies.