The distance between a fabrication protocol and a functioning biological experiment is rarely covered in a single step. It requires systematic translation: converting the process controls, measurement standards, and tolerance specifications native to materials engineering into a form that biological systems can be tested against reliably. Justin Jadali, a graduate student in Mechanical Engineering and Materials Science at Yale University in New Haven, Connecticut, operates precisely at this translation boundary.
Justin Shayan Jadali arrived at this position through an accelerated academic path: a perfect ACT score, high school graduation at 16, three Associate of Science degrees in Physics, Mathematics, and Natural Sciences from Irvine Valley College by 18, a B.S. in Mechanical Engineering from UCLA at 20, and an M.S. in Mechanical Engineering and Materials Science at Yale at 21, completed alongside a certificate in Physical and Engineering Biology. He also brings operational experience from building and managing teams in a startup environment, a background that informs the accountability discipline his fabrication and research workflows demand.
What Materials Engineering Brings to Biological Research
Materials science and biological research share a common challenge, producing consistent outputs from complex systems, but they have developed different cultures for addressing it. In materials engineering, process control is foundational. Alloy composition, casting temperature, cooling rate, and post-processing treatments are specified and monitored because small deviations in these inputs produce large and sometimes catastrophic differences in mechanical performance. Biological research has not uniformly adopted this standard, where variability is sometimes treated as an inherent feature of living systems rather than a fabrication problem addressable upstream.
Justin Jadali brings the materials engineering culture of input control directly into the biological research context. The fabrication of alginate hydrogel microparticles, the scaffold system central to his M.S. work, is treated as a manufacturing process with defined input parameters, measurable outputs, and acceptance criteria that must be met before any particle batch advances to cell culture. Polymer concentration, crosslinker concentration, ionic strength, mixing protocol, and gelation time are each specified and held constant across batches.
Defining Acceptance Criteria for Scaffold Batches
The practical consequence of applying manufacturing discipline to scaffold fabrication is that each batch must pass mechanical and structural characterization before it is used. Elastic modulus, swelling ratio, and particle size distribution are measured for every preparation. These measurements serve the same function as incoming material inspection in an industrial setting: they confirm that the input to the biological experiment is what it is assumed to be. A batch that falls outside the accepted range for any parameter is not advanced, regardless of the effort invested in preparing it.
This approach draws directly on quality control practices from materials processing. In structural materials engineering, a casting with porosity outside specified limits is rejected regardless of whether it looks acceptable. The fabrication standards that Justin Jadali’s materials processing approach applies to alginate microparticles reflect the same logic: the cost of running a biological experiment with a non-conforming scaffold is a confounded result, which is more expensive than the cost of the rejected batch itself.
Justin Jadali’s Application of Crosslinker Chemistry to Scaffold Engineering
The crosslinking step in alginate hydrogel fabrication is the clearest example of how materials processing knowledge translates into biological research design. Crosslinking, the formation of chemical bridges between polymer chains that convert a polymer solution into a solid or semi-solid gel network, is a standard operation in polymer processing. The choice of crosslinker, its concentration, and the conditions under which crosslinking occurs determine the density and uniformity of the resulting network, which in turn determines the gel’s mechanical properties and transport characteristics.
In Justin Jadali’s M.S. research, the comparison between calcium and zinc as divalent cation crosslinkers is structured as a materials science experiment before it is structured as a biological one. Calcium and zinc differ in ionic radius and binding affinity for alginate’s guluronate residues, and these differences produce measurable distinctions in network structure. Calcium forms a more selective and regularly organized gel network; zinc produces a denser crosslink structure with different ion exchange kinetics. These material-level differences have downstream biological consequences, specifically for how growth factors are retained in and released from the scaffold matrix, and how substrate stiffness influences endothelial cell behavior.
Translating Polymer Processing Parameters into Cell Culture Variables
The translation from polymer processing to cell culture requires identifying which material parameters are biologically relevant and designing fabrication protocols that hold those parameters within defined ranges. Substrate stiffness is a well-documented influence on endothelial cell morphology and network-forming behavior. A scaffold that is too stiff restricts the cell deformation required for tubule elongation; one that is too compliant fails to provide adequate structural support for network organization. The elastic modulus target for a vascular tissue engineering scaffold is not arbitrary: it is derived from the mechanical properties of native vascular basement membrane, translated back into fabrication parameters through an understanding of how crosslinker concentration and polymer density determine gel stiffness.
Justin Jadali executes this translation in both directions: from biological requirements to fabrication specifications during experimental design, and from fabrication measurements to biological interpretation during data analysis. This bidirectional translation is the core competency that distinguishes materials science-trained researchers in biological engineering environments. The same discipline extends to bioprinting and additive manufacturing contexts, where scaffold geometry, bioink composition, and print parameters must each be specified with the same tolerance rigor as any other fabrication input.
Processing Parameters and Growth Factor Release Kinetics
Beyond mechanical properties, the processing parameters used to fabricate alginate microparticles directly govern how growth factors encapsulated within the scaffold are released into the surrounding cell culture environment. Growth factor release kinetics depend on the mesh size of the crosslinked gel network, the affinity between the growth factor and the polymer matrix, and the rate at which the network swells or degrades under culture conditions. Each of these factors is a function of fabrication choices: crosslinker identity, crosslinker concentration, polymer molecular weight, and gelation time.
The experimental approach in Justin Jadali’s research at Yale treats growth factor release not as a property of the growth factor but as a property of the fabrication system. By characterizing release profiles across multiple crosslinker conditions and correlating them with the material parameters measured during scaffold characterization, the research establishes a direct, quantitative relationship between processing choices and biological inputs. This mirrors the logic of controlled-release pharmaceutical manufacturing, where coating thickness, polymer composition, and processing conditions determine drug release rate, not the drug itself.
Connecting Release Profiles to Vascular Network Formation
The endpoint biological measurement in this research framework is vascular network formation: the capacity of endothelial cells and pericytes, cultured within three-dimensional alginate scaffold constructs, to organize into tubular networks that recapitulate the structural features of native vasculature. Network formation is quantified through imaging-based metrics including tubule length, branching density, and network interconnectivity. These metrics are sensitive to both the mechanical environment provided by the scaffold and the biochemical environment created by growth factor release.
Because both of these inputs are characterized and controlled through fabrication, the research framework allows the biological output to be interpreted with precision: differences in network formation between crosslinking conditions can be attributed to specific material differences rather than uncontrolled variation.
From the Capstone Lab to the Research Bench
The translation of fabrication knowledge into biological research applications is not only a research practice for Justin Jadali’s work at Yale; it is also a pedagogical one. As a teaching assistant in Yale’s mechanical engineering capstone design program in New Haven, he guides undergraduate students through the process of converting design requirements into fabrication decisions and fabrication decisions into measurable performance outcomes. The core skill developed in that course is the same one applied at the research bench: the ability to specify, execute, and evaluate a fabrication process with enough precision that results can be trusted and interpreted.
This connection between teaching and research reflects a coherent methodological identity, reinforced by the operational accountability he developed managing teams in a startup environment. Materials engineering training in biological research is the capacity to treat every experimental system, including living tissue, as something that can be designed, characterized, and controlled.
About Justin Jadali
Justin Jadali is a graduate student in the Department of Mechanical Engineering and Materials Science at Yale University in New Haven, Connecticut, completing an M.S. degree alongside a certificate in Physical and Engineering Biology. He holds a Bachelor of Science in Mechanical Engineering from UCLA and three Associate of Science degrees from Irvine Valley College in Physics, Mathematics, and Natural Sciences. His research specializes in alginate hydrogel scaffold design, crosslinker-dependent materials processing, growth factor release engineering, vascular network formation, and microscopy-based imaging of tissue engineering outcomes. He also serves as a teaching assistant in Yale’s mechanical engineering capstone design program and has experience building and managing teams in a startup environment. To learn more about his research and academic work, visit Justin Jadali’s academic profile and research portfolio.
