A5105925385- Interconnection Networks and Systems
- Parallel Computing and Optimization Techniques
- Advanced Memory and Neural Computing
- Neural dynamics and brain function
- Neural Networks and Applications
- Gene Regulatory Network Analysis
- Embedded Systems Design Techniques
- Complex Network Analysis Techniques
- Complex Systems and Time Series Analysis
- Cloud Computing and Resource Management
- Bioinformatics and Genomic Networks
- Neuroscience and Neural Engineering
- Molecular Communication and Nanonetworks
- Supercapacitor Materials and Fabrication
- Functional Brain Connectivity Studies
- Advancements in Battery Materials
- Low-power high-performance VLSI design
- Fractal and DNA sequence analysis
- EEG and Brain-Computer Interfaces
- Graphene research and applications
- IoT and Edge/Fog Computing
- Advanced Battery Technologies Research
- Topological and Geometric Data Analysis
- Evolutionary Algorithms and Applications
- Chaos control and synchronization
Southern California University for Professional Studies
2016-2025
University of Southern California
2016-2025
Viterbo University
2025
University of Michigan
2022-2023
Weatherford College
2021
Flint Institute Of Arts
2021
Karlsruhe Institute of Technology
2020
Association for Computing Machinery
2019
Engineering Systems (United States)
2019
Rensselaer Polytechnic Institute
2018
Abstract The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has led to millions deaths, and devastated social, financial political entities around world. Without existing effective medical therapy, vaccines are urgently needed avoid this disease. In study, we propose in silico deep learning approach for prediction design a multi-epitope vaccine (DeepVacPred). By combining immunoinformatics neural network strategies, DeepVacPred computational...
The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging deviate their typical trajectories. MRI-derived (BA) estimates are often obtained using deep learning models that may perform relatively poorly on new data or lack interpretability. This study introduces a convolutional neural network (CNN) to estimate BA after training the MRIs 4,681 cognitively normal (CN) participants...
Networks-on-chip (NoCs) have recently emerged as a scalable alternative to classical bus and point-to-point architectures. To date, performance evaluation of NoC designs is largely based on simulation which, besides being extremely slow, provides little insight how different design parameters affect the actual network performance. Therefore, it practically impossible use for optimization purposes. In this paper, we present mathematical model on-chip routers utilize new analysis. The proposed...
Conformal, rechargeable zinc-air batteries from biomimetic materials serving as protective covers replace stand-alone batteries.
Abstract Identification of community structures in complex network is crucial importance for understanding the system’s function, organization, robustness and security. Here, we present a novel Ollivier-Ricci curvature (ORC) inspired approach to identification networks. We demonstrate that intrinsic geometric underpinning ORC offers natural discover inherent within based on interaction among entities. develop an ORC-based algorithm idea sequential removal negatively curved edges symptomatic...
Abstract Understanding the mechanisms by which neurons create or suppress connections to enable communication in brain-derived neuronal cultures can inform how learning, cognition and creative behavior emerge. While prior studies have shown that possess self-organizing criticality properties, we further demonstrate vitro exhibit a self-optimization phenomenon. More precisely, analyze multiscale neural growth data obtained from label-free quantitative microscopic imaging experiments...
DATA REPORT article Front. Psychol., 31 May 2021Sec. Personality and Social Psychology Volume 12 - 2021 | https://doi.org/10.3389/fpsyg.2021.644801
Brain age (BA), distinct from chronological (CA), can be estimated MRIs to evaluate neuroanatomic aging in cognitively normal (CN) individuals. BA, however, is a cross-sectional measure that summarizes cumulative since birth. Thus, it conveys poorly recent or contemporaneous trends, which better quantified by the (temporal) pace P of brain aging. Many approaches map , rely on quantifying DNA methylation whole-blood cells, blood–brain barrier separates neural cells. We introduce...
The Chip Is the Network: Towards a Science of Network-on-Chip Design reviews major design methodologies that have had profound effect on designing future (NoC) architectures. More precisely, it addresses problem NoC in deterministic context, where application and architecture are modeled as graphs with worst-case type information about parameters components influencing network traffic. Rather than simply enumerating proposed approaches, takes formal approach also discusses main features each...
Networks-on-chip (NoCs) have been proposed as a viable solution to solving the communication problem in multicore systems. In this new setup, mapping multiple applications on available computational resources leads interaction and contention at various network resources. Consequently, taking into account traffic characteristics becomes of crucial importance for performance analysis optimization infrastructure, well proper resource management. Although queuing-based approaches traditionally...
Abstract Through an elegant geometrical interpretation, the multi-fractal analysis quantifies spatial and temporal irregularities of structural dynamical formation complex networks. Despite its effectiveness in unweighted networks, geometry weighted role interaction intensity, influence embedding metric spaces design reliable estimation algorithms remain open challenges. To address these challenges, we present a set for quantifying complexity heterogeneity Our methodology uncovers that (i)...
There exists an urgent need for determining the right amount and type of specialization while making a heterogeneous system as programmable flexible possible. Therefore, in this paper, we pioneer self-optimizing selfprogramming computing (SOSPCS) design framework that achieves both programmability flexibility exploits heterogeneity [e.g., CPUs, GPUs, hardware accelerators (HWAs)]. First, at compile time, form task pool consisting hybrid tasks with different processing element (PE) affinities...
Social media became popular and percolated almost all aspects of our daily lives. While online posting proves very convenient for individual users, it also fosters fast-spreading various rumors. The rapid wide percolation rumors can cause persistent adverse or detrimental impacts. Therefore, researchers invest great efforts on reducing the negative impacts Towards this end, rumor classification system aims to detect, track, verify in social media. Such systems typically include four...
The solution of a partial differential equation can be obtained by computing the inverse operator map between input and space. Towards this end, we introduce \textit{multiwavelet-based neural learning scheme} that compresses associated operator's kernel using fine-grained wavelets. By explicitly embedding multiwavelet filters, learn projection onto fixed polynomial bases. projected is trained at multiple scales derived from repeated computation transform. This allows complex dependencies...
Abstract Network theory helps us understand, analyze, model, and design various complex systems. Complex networks encode the topology structural interactions of systems in nature. To mine multiscale coupling, heterogeneity, complexity natural technological systems, we need expressive rigorous mathematical tools that can help understand growth, topology, dynamics, structures, functionalities their interrelationships. Towards this end, construct node-based fractal dimension (NFD) multifractal...
Abstract Chronic obstructive pulmonary disease (COPD) is one of the leading causes death worldwide. Current COPD diagnosis (i.e., spirometry) could be unreliable because test depends on an adequate effort from tester and testee. Moreover, early challenging. The authors address detection by constructing two novel physiological signals datasets (4432 records 54 patients in WestRo dataset 13824 medical 534 Porti dataset). demonstrate their complex coupled fractal dynamical characteristics...
As CMOS technology scales down into the deep-submicron (DSM) domain, costs of design and verification for Systems-on-Chip (SoCs) are rapidly increasing. Relaxing requirement <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>100</mml:mn><mml:mi>%</mml:mi></mml:mrow></mml:math> correctness devices interconnects drastically reduces but, at same time, requires SoCs to be designed with some degree system-level fault-tolerance. Towards this end, paper introduces a novel...
Reducing energy consumption in multi-processor systems-on-chip (MPSoCs) where communication happens via the network-on-chip (NoC) approach calls for multiple voltage/frequency island (VFI)-based designs. In turn, such multi-VFI architectures need efficient, robust, and accurate run-time control mechanisms that can exploit workload characteristics order to save power. Despite being tractable, linear models power management cannot capture some important (e.g., fractality, non-stationarity)...
Bacteria-based networks are formed using native or engineered bacteria that communicate at nano-scale. This definition includes the micro-scale molecular transportation system which uses chemotactic for targeted cargo delivery, as well genetic circuits intercellular interactions like quorum sensing light communication. To characterize dynamics of bacterial accurately, we introduce BNSim, an open-source, parallel, stochastic, and multiscale modeling platform integrates various simulation...
Compared to conventional internal combustion engine (ICE) propelled vehicles, hybrid electric vehicles (HEVs) can achieve both higher fuel economy and lower pollution emissions. The HEV consists of a propulsion system containing one ICE or more motors (EMs). use EM increases the complexity power management, therefore requires advanced management policies performance consumption. Towards this end, our work aims at minimizing consumption over any driving cycle (without prior knowledge cycle)...
Capturing the mathematical features of physical and cyber processes is essential for endowing CPS with built-in intelligence. In this paper, we develop a compact yet accurate model able to capture spatio-temporal fractal cross-dependencies between coupled illustrate its benefits within context brain-machine-body interface. Our generalized improves modeling accuracy dynamics biological validated against medical observations.
Abstract Analyzing drug-drug interactions may unravel previously unknown drug action patterns, leading to the development of new discovery tools. We present a approach analyzing interaction networks, based on clustering and topological community detection techniques that are specific complex network science. Our methodology uncovers functional categories along with intricate relationships between them. Using modularity-based energy-model layout algorithms, we link clusters 9 relevant...
Today's multiprocessor platforms employ the network-on-chip (NoC) architecture as preferable communication backbone. Conventional NoCs are designed predominantly for unicast data exchanges. In such NoCs, multicast traffic is generally handled by converting each message to multiple transmissions. Hence, applications dominated experience high queuing latencies and significant performance penalties when running on systems with unicast-based NoC architectures. Various mechanisms XY-tree path...
Building autonomous data-centers-on-chip (DCoC) for exascale computing requires mathematical frameworks that account and exploit the non-stationary multi-fractal characteristics of computation communication workloads. Towards this end, relying on DCoC (Intel's SCC) measurements, we propose a complex dynamical modeling approach captures observed inter-event times between successive workload changes magnitude increments in Our novel framework allows analysis higher order moments enables...