Direct digital manufacturing (DDM) is the practice of creating a physical part directly from a computer-aided design (CAD) model with minimal process planning. DDM is typically applied in additive manufacturing (AM) processes, which offer rapid implementation and the ability to produce complex geometry. However, the treatment of subtractive manufacturing (SM) in the context of DDM is still lacking. SM is a decades- old process that is responsible for the production of many parts in the world today. SM and AM have distinct advantages and disadvantages.

Machining is a fundamental processing capability critical to production of end-user goods and systems, as well as components used in virtually every industrial process. Machine tool programming to support these processes is critical for production and cost estimation. Unfortunately, currently available automated process planning methods constrain the process along geometrically simple trajectories due to computational constraints, this at the sacrifice of final processing efficiency.

The project is developing novel architectures for control and diagnosis of complex cyber-­‐physical  systems  subject to stringent performance  requirements  in  terms  of safety, resilience, and adaptivity. These ever-­‐increasing demands necessitate the use of    formal    model-­‐based    approaches    to    synthesize    provably-­‐correct    feedback controllers.

Complex, networked, distributed cyber-physical systems (CPSs) are emerging in many safety-critical application domains such as aerospace and automotive. Design of such systems heavily relies on insights and experiences of engineers as principled design methodologies that can cope with the complexity of these systems are lacking. As a result, extensive testing and fine-tuning is required to ensure that the final product satisfies the design objectives.

Design of cyber-physical systems today relies on executable models. Designers develop models, simulate them, nd defects, and improve their designs before the system is built, thus greatly reducing the design costs. However, current model-based design methods lack support for model libraries (creating and exchanging models as "black boxes"), tool interoperability (allowing models to be co-simulated by multiple tools), and multi-view modeling (allowing to combine models that "live in different worlds", for instance, a control-logic model with an energy-consumption model).

The artificial pancreas (AP) is a set of increasingly sophisticated devices and algorithms that will automate the delivery of insulin to patients with type-1 diabetes. While the AP concept promises to alleviate the burden posed by the self-management of blood glucose levels, it also poses significant risks arising from a combination of external disturbances such as patient meals, physical activity, sensor errors, network delays and physiological variations.

Our proposal’s main objective is to realize cyber-physical platform and principles for (i) interrogating global modalities of intracellular transport with causative factors isolated at the single-molecule scale and (ii) realizing efficient and robust infrastructure for transporting micron/molecular scale cargo using distributed strategies We are realizing in-vitro, a transport network with roadways formed by microtubules where motorproteins, kinesin and dynein, will form vehicles ferrying cargo.