Data Scientist-2 at AWS | IIIT Scholar | ML expert
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aws
Data Scientist
June 18, 2026 – Present
Flower_Classification_Tensorflow.js
May 30, 2021 – November 20, 2021
For this project, I'll be using the 'Flower Classification' dataset which I downloaded from Kaggle. This project has been made using Tensorflow.js.
View ProjectAttention-Mechanism-Basics
August 5, 2019 – August 5, 2019
Attention-Mechanism-Basics — GitHub repository
View ProjectMNIST_GAN
July 31, 2019 – July 31, 2019
In this notebook, we'll be building a generative adversarial network (GAN) trained on the MNIST dataset. From this, we'll be able to generate new handwritten digits! GANs were first reported on in 2014 from Ian Goodfellow and others in Yoshua Bengio's lab. Since then, GANs have exploded in popularity. Here are a few examples to check out: Pix2Pix CycleGAN & Pix2Pix in PyTorch, Jun-Yan Zhu A list of generative models The idea behind GANs is that you have two networks, a generator G and a discriminator D , competing against each other. The generator makes "fake" data to pass to the discriminator. The discriminator also sees real training data and predicts if the data it's received is real or fake. The generator is trained to fool the discriminator, it wants to output data that looks as close as possible to real, training data. The discriminator is a classifier that is trained to figure out which data is real and which is fake. What ends up happening is that the generator learns to make d
View ProjectSemantic-Segmentation
July 4, 2019 – August 7, 2019
Semantic-Segmentation — GitHub repository
View ProjectKalman-Filters
March 8, 2019 – November 20, 2021
Kalman filtering, also known as linear quadratic estimation (LQE), is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. The filter is named after Rudolf E. Kálmán, one of the primary developers of its theory.
View ProjectLandmark-Detection-Tracking-SLAM-
January 31, 2019 – November 20, 2021
SLAM gives you a way to track the location of a robot in the world in real-time and identify the locations of landmarks such as buildings, trees, rocks, and other world features. This is an active area of research in the fields of robotics and autonomous systems.
View ProjectAutomatic-Image-Captioning
January 30, 2019 – November 20, 2021
In this project, I have created a neural network architecture to automatically generate captions from images. After using the Microsoft Common Objects in COntext (MS COCO) dataset to train my network, I have tested my network on novel images!
View ProjectYOLO-Object-Detection
January 5, 2019 – November 20, 2021
YOLO is a state-of-the-art, real-time object detection algorithm. In this notebook, we will apply the YOLO algorithm to detect objects in images.
View ProjectFacial-Keypoint-Detection
January 5, 2019 – November 20, 2021
This project combines the knowledge of computer vision techniques and deep learning architectures to build a facial keypoint detection system that takes in any image with faces, and predicts the location of 68 distinguishing keypoints on each face!
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily focused on personal, academic-style projects, primarily in computer vision and deep learning. While this demonstrates strong technical interest and initiative, there is no information on collaborative projects, open-source contributions, or experience in diverse team environments. The current role at AWS as 'Data Scientist' is listed with a future start date, indicating a lack of current professional experience. This suggests a potential gap in understanding enterprise-level data science practices, MLOps, and cross-functional team collaboration, which might impact cultural fit in a fast-paced, product-oriented environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are clear but do not provide insight into collaboration, problem-solving approaches, or communication style in a team setting.