Software Engineer @ Observe.AI | Computer Vision | Deep Learning
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Observe.AI
Data Scientist
June 20, 2026 – Present
Local-RPCA-Defense
March 2, 2023 – September 21, 2023
This repository is official implementation of paper titled "Adversarial Defense with Local Robust Principal Component Analysis and Wavelet Denoising"
View ProjectNOMARO_defense
May 27, 2021 – December 30, 2021
Official Implementation of Paper "NOMARO: Defending against Adversarial Attacks by NOMA-Inspired Reconstruction Operation"
View ProjectstAdv-PyTorch
March 14, 2021 – May 16, 2021
This Repository contains the PyTorch Implementation of the Spatially Transformed Adversarial Attack (ICLR'18).
View ProjectDeep-Generative-Filter-For-Motion-Deblurring-PyTorch
December 5, 2020 – August 14, 2022
This repository contains the PyTorch implementation of the ICCV'17 Paper, "Deep Generative Filter for Motion Deblurring"
View ProjectZOO_Attack_PyTorch
November 15, 2020 – February 25, 2023
This repository contains the PyTorch implementation of Zeroth Order Optimization Based Adversarial Black Box Attack (https://arxiv.org/abs/1708.03999)
View ProjectAdversarial-Example-Attack-and-Defense
August 8, 2020 – December 17, 2020
This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defense against all attacks using MNIST dataset.
View ProjectFundamental-Brain-Waves-Extractor
April 14, 2020 – August 9, 2020
The implementation of the multiband filtering system to extract the five fundamental Brain Waves from given EEG Signal.
View ProjectAdversarial-Examples-of-Pokemon
April 10, 2020 – December 17, 2020
The implementation of DCGAN using PyTorch to generate adversarial examples of pokemon.
View ProjectPSOC_LAB
February 9, 2020 – February 13, 2020
This contains normal coursework of Power System Operation and Control Laboratory
View ProjectMultimodal-Brain-Tumor-Segmentation
December 24, 2019 – March 24, 2021
Multimodal Brain Tumor Segmentation using BraTS 2018 Dataset.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily focused on personal research and implementation in adversarial machine learning and medical imaging. While this demonstrates strong technical initiative, the lack of team-based or collaborative projects in the provided data makes it difficult to assess cultural fit comprehensively. The projects are highly specialized, which could be a strong fit for a research-oriented data science role but might require adaptation for broader industry applications. The experience level is listed as 0, which contradicts the current full-time Data Scientist role, making it hard to gauge professional maturity.
Soft Skills & Operational Fit
The candidate's project descriptions are concise, indicating a focus on technical implementation. However, without direct assessment data for soft skills or operational fit, it is difficult to provide a comprehensive evaluation. The project diversity suggests an ability to work on varied technical challenges.