A5064919717- Microbial Metabolic Engineering and Bioproduction
- Biofuel production and bioconversion
- Viral Infectious Diseases and Gene Expression in Insects
- Enzyme Production and Characterization
- Privacy-Preserving Technologies in Data
- Real-time simulation and control systems
- Advanced MIMO Systems Optimization
- Process Optimization and Integration
- Model-Driven Software Engineering Techniques
- Civil and Structural Engineering Research
- Advanced Machining and Optimization Techniques
- Corporate Governance and Management
- Age of Information Optimization
- Modular Robots and Swarm Intelligence
- Advanced Control Systems Optimization
- thermodynamics and calorimetric analyses
- Electric and Hybrid Vehicle Technologies
- Stochastic Gradient Optimization Techniques
- Enzyme Catalysis and Immobilization
- Microbial Metabolites in Food Biotechnology
- Sugarcane Cultivation and Processing
- Forest Biomass Utilization and Management
- Energy Harvesting in Wireless Networks
- Engineering and Materials Science Studies
- Control Systems in Engineering
United States Army Combat Capabilities Development Command
2024
Purdue University West Lafayette
2022-2023
Chalmers University of Technology
2019-2020
PTV Group (Germany)
2018
Technische Universität Berlin
2014-2016
We present an integrated framework for the online optimal experimental re-design applied to parallel nonlinear dynamic processes that aims precisely estimate parameter set of macro kinetic growth models with minimal effort. This provides a systematic solution rapid validation specific model new strains, mutants, or products. In biosciences, this is especially important as identification long and laborious process which continuing limit use mathematical modeling in field. The strength...
Lignocellulosic biomass is an abundant and sustainable feedstock, which represents a promising raw material for the production of lactic acid via microbial fermentation. However, toxic compounds that affect growth metabolism are released from upon thermochemical pre-treatment. So far, susceptibility bacterial strains to biomass-derived inhibitors still major barrier lignocellulose. Detoxification pre-treated lignocellulosic by water washing commonly performed alleviate inhibition...
Abstract Bioprocess development, optimization, and control in mini‐bioreactor systems require information about essential process parameters, high data densities, the ability to dynamically change conditions. We present an integration approach combining a parallel system integrated into liquid handling station (LHS) with second LHS for offline analytics. Non‐invasive sensors measure pH DO online. Offline samples are collected every 20 min acetate, glucose, OD 620 subsequently analyzed...
The demand for intelligent services at the network edge has introduced several research challenges. One is need a machine learning architecture that achieves personalization (to individual clients) and generalization unseen data) properties concurrently across different applications. Another an inference strategy can satisfy resource latency constraints during testing-time. Existing techniques in federated have encountered steep trade-off between generalization, not explicitly considered...
Bioprocesses based on (ligno-)cellulosic biomass are highly prone to batch-to-batch variations. Varying raw material compositions and enzyme activities hamper the prediction of process yields, economic feasibility environmental impacts. Commonly, these performance indicators averaged over several experiments select suitable designs. The variabilities in resulting from variable inputs often neglected, causing a risk for faulty predictions poor design choices during scale-up. In this paper,...
Federated learning (FL) has emerged as a popular technique for distributing machine across wireless edge devices. We examine FL under two salient properties of contemporary networks: device-server communication delays and device computation heterogeneity. Our proposed StoFedDelAv algorithm incorporates local-global model combiner into the synchronization step. theoretically characterize convergence behavior obtain optimal weights, which consider global delay expected local gradient error at...
<title>ABSTRACT</title> <p>Evolving requirements for combat vehicles to provide increased mission capability and/or crew safety necessitate the addition of components and add-on armor currently-fielded vehicles. These new result in weight electrical needs, which reduced mobility. The APD is built from ground up optimize a powertrain solution using cutting-edge technology specifically designed harsh military environments, use both vehicle retrofits designs. combines an...
Federated learning (FL) has emerged as a popular technique for distributing machine across wireless edge devices. We examine FL under two salient properties of contemporary networks: device-server communication delays and device computation heterogeneity. Our proposed StoFedDelAv algorithm incorporates local-global model combiner into the synchronization step. theoretically characterize convergence behavior obtain optimal weights, which consider global delay expected local gradient error at...