Sucheta Naik
Firmware Developer
Management: 1-2 years (1-5 people)
MATLAB
C
Active 3 days ago
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Overview
Technical skills
Timeline
Roles
Overview
MATLAB medical imaging practitioner (junior) specializing in multimodal image fusion for brain tumor analysis. The strongest proven skill is implementing DWT and MSVD fusion pipelines and computing image-quality metrics as demonstrated in algorithms/dwt/common/dwtfeature.m and algorithms/msvd/common/msvdfusdemo.m. The public code lacks modular engineering, reproducible experiment infrastructure, automated tests, and rigorous statistical validation of reported claims.
Phone
Technical skills
MATLAB
C
MATLAB
Computer Vision Toolbox
DevOps
Amazon S3
TCP/IP
GitHub
Wi-Fi
IoT
ESP-IDF
FreeRTOS
Timeline
Firmware Developer
•
Middle
SmartBuild Automation Pvt Ltd
•
Full-Time
Develops ESP32-S3-WROOM-1 firmware in C with FreeRTOS, adding UART-based command handling and network communication via TCP/IP and UDP over Wi‑Fi, plus BLE features. Builds and validates RF communication behavior with reliability and fault handling during live testing. Works on motor and channel control logic, including NVS-based recovery and resume after reboot/reset, and implements user-configurable scheduling and touch-display control flows.
C
FreeRTOS
ESP-IDF
TCP/IP
Wi-Fi
Quality Assurance Automation Testing Intern
•
Junior
Pepperl+Fuchs India Pvt Ltd
•
Internship
Performs QA testing for sensor batches using calibration and measurement equipment. Configures and calibrates sensors with PACTware and Sonprog, and verifies IP settings and client-specific communication requirements using Docklight-based TCP/UDP validation. Maintains documentation for large test volumes and supports process improvements with engineering based on workshop feedback.
Junior Data Scientist
Confidence: Medium ML Practitioner
MATLAB medical imaging practitioner (junior) specializing in multimodal image fusion for brain tumor analysis. The strongest proven skill is implementing DWT and MSVD fusion pipelines and computing image-quality metrics as demonstrated in algorithms/dwt/common/dwtfeature.m and algorithms/msvd/common/msvdfusdemo.m. The public code lacks modular engineering, reproducible experiment infrastructure, automated tests, and rigorous statistical validation of reported claims.
Statistical Rigor
2/10
Correct use of statistics
Uses common image-quality metrics and basic summary statistics but no statistical tests, uncertainty quantification, or rigorous experiment design.
Evidence
algorithms/msvd/common/msvdfusdemo.m: computes M, E, S, mi and sums ma+mb
algorithms/dwt/common/dwtfeature.m: calls pereval to compute RMSE,PFE,MAE,CORR,SNR,PSNR,MI,QI,SSIM
Data Wrangling & Cleaning
2/10
Preparing and cleaning data
Basic image I/O and preprocessing are present but file paths are hardcoded and there is no dataset provenance, missing-value handling, or contamination checks.
Evidence
algorithms/dwt/common/dwtfeature.m: imread/imresize/rgb2gray/im2bw with relative filenames
Glioblastoma/MSVD/msvdfusdemo.m: imread with absolute D:\Glioblastoma\ paths
Exploratory Analysis & Visualization
3/10
Exploring and visualizing data
Includes direct visualizations and figures that help inspect results but lacks written interpretation or structured EDA; plots are used for inspection rather than storytelling.
Evidence
algorithms/dwt/common/dwtfeature.m: multiple figure/imshow calls to display decomposition and fused image
algorithms/msvd/common/msvdfusdemo.m: figure/imshow sequence for input and fused images
Predictive Modeling
1/10
Building models that predict
No predictive modeling workflow is present; work focuses on signal processing/image fusion and computing evaluation metrics rather than model training, cross-validation or error analysis.
Evidence
algorithms/dwt/common/dwtfeature.m: fusion implementation and metric evaluation but no model training
algorithms/msvd/common/msvdfusdemo.m: MSVD fusion script without modeling or CV
Business Insight & Impact
1/10
Turning analysis into business value
No business framing, cost-of-error analysis, or actionable recommendations are present in the code; emphasis is technical and experimental.
Evidence
algorithms/msvd/common/msvdfusdemo.m: computes numeric quality metrics but no business/clinical decision logic
algorithms/dwt/common/dwtfeature.m: prints evaluation metrics without interpretation or operational guidance
Reproducibility & Notebook Hygiene
1/10
Clean, repeatable analysis
Reproducibility is limited; scripts use clear workspace clearing and hardcoded paths, but there are no pinned environments, data versioning, seeds, or modular pipeline structure.
Evidence
algorithms/dwt/common/dwtfeature.m: uses clc; close all; clear all and hardcoded filenames
Glioblastoma/MSVD/msvdfusdemo.m: writes outputs to absolute paths and lacks configuration or reproducibility metadata
Industries
Health Care• Junior
Technologies
MATLAB• since 2025 • Junior
Computer Vision Toolbox
Datasets• mentioned only
Recommendations
- Prototype and refine multimodal image-fusion algorithms and evaluation scripts in MATLAB for research-stage medical imaging tasks.
- Convert the current scripts into modular functions and add reproducible experiment tooling such as configuration files, deterministic seeds, and unit tests.
- Implement rigorous evaluation pipelines with dataset provenance, controlled experiments, and documented statistical analyses to support any diagnostic accuracy claims.
Repositories
The developer's experience in this domain has been verified based on AI analysis of the following repositories: