Mehdi Javanmard

About Mehdi Javanmard

Mehdi Javanmard, With an exceptional h-index of 25 and a recent h-index of 18 (since 2020), a distinguished researcher at Rutgers, The State University of New Jersey, specializes in the field of Biosensing, Microfluidics, Proteomics, Genomics, Metabolomics.

His recent articles reflect a diverse array of research interests and contributions to the field:

High Sensitivity and High Throughput Magnetic Flow CMOS Cytometers with 2D Oscillator Array and Inter-Sensor Spectrogram Cross-correlation

Integrating Optical and Electrical Sensing with Machine Learning for Advanced Particle Characterization

Clinical evaluation of a fully electronic microfluidic white blood cell analyzer

A computer vision enhanced smart phone platform for microfluidic urine glucometry

Multi-modal sensing with integrated machine learning to differentiate specific leukocytes targeted by electrically sensitive hybrid particles

Cell phone microscopy enabled low-cost manufacturable colorimetric urine glucose test

Advancing Healthcare: Synergizing Biosensors and Machine Learning for Early Cancer Diagnosis

Digital assay for rapid electronic quantification of clinical pathogens using DNA nanoballs

Mehdi Javanmard Information

University

Position

Associate Professor NJ

Citations(all)

1939

Citations(since 2020)

1186

Cited By

1171

hIndex(all)

25

hIndex(since 2020)

18

i10Index(all)

53

i10Index(since 2020)

37

Email

University Profile Page

Google Scholar

Mehdi Javanmard Skills & Research Interests

Biosensing

Microfluidics

Proteomics

Genomics

Metabolomics

Top articles of Mehdi Javanmard

High Sensitivity and High Throughput Magnetic Flow CMOS Cytometers with 2D Oscillator Array and Inter-Sensor Spectrogram Cross-correlation

IEEE Transactions on Biomedical Circuits and Systems

2024/2/23

Integrating Optical and Electrical Sensing with Machine Learning for Advanced Particle Characterization

2024/1/23

Clinical evaluation of a fully electronic microfluidic white blood cell analyzer

Plos one

2024/1/18

A computer vision enhanced smart phone platform for microfluidic urine glucometry

Analyst

2024

Multi-modal sensing with integrated machine learning to differentiate specific leukocytes targeted by electrically sensitive hybrid particles

Biosensors and Bioelectronics

2023/12/1

Cell phone microscopy enabled low-cost manufacturable colorimetric urine glucose test

Biomedical Microdevices

2023/12

Advancing Healthcare: Synergizing Biosensors and Machine Learning for Early Cancer Diagnosis

2023/9/13

Darshan Singh
Darshan Singh

H-Index: 15

Mehdi Javanmard
Mehdi Javanmard

H-Index: 18

Digital assay for rapid electronic quantification of clinical pathogens using DNA nanoballs

Science Advances

2023/9/6

A two-minute assay for electronic quantification of antibodies in saliva enabled through a reusable microfluidic multi-frequency impedance cytometer and machine learning analysis

Biomedical Microdevices

2023/6

A Time-Frequency Deep Learning Classification Model for Metal Oxide Coated Particles

2023/5/8

Use of multi-frequency impedance cytometry in conjunction with machine learning for classification of biological particles

2023/3/14

Nucleic acid quantification by multi-frequency impedance cytometry and machine learning

Biosensors

2023/2/24

A smartphone-based disposable hemoglobin sensor based on colorimetric analysis

Sensors

2022/12/30

Method and apparatus for electrochemical screening of chemicals in the environment and biological samples

2022/12/29

MEMS Sensor Development for In-Situ Quantification of Toxic Metals in Sediment

2022/12/1

A portable analog front-end system for label-free sensing of proteins using nanowell array impedance sensors

Scientific reports

2022/11/22

Wearable impedance cytometer

2022/11/22

MACHINE LEARNING ENABLES QUANTIFYING CELL-JANUS PARTICLE CONJUGATES THROUGH MICROFLOWING IMPEDANCE SIGNALS

Micro total analysis systems: proceedings of the...[Mu] TAS International Conference on Miniaturized Chemical and Biochemical Analysis Systems.[Mu] TAS (Conference)

2022/10

Novel, Rapid Breathalyzer Diagnostic Device for the Presence of SARS-CoV-2

2022/9/8

Biosensors and machine learning for enhanced detection, stratification, and classification of cells: A review

2022/9

See List of Professors in Mehdi Javanmard University(Rutgers, The State University of New Jersey)

Co-Authors

academic-engine