
Electrical Engineering Student, IIT Madras.
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Assessing your cultural and operational fit
Radio-frequency-Energy-Harvesting-Project
March 16, 2019 – March 21, 2019
Wireless Sensor Network Utilizing Radio-Frequency Energy Harvesting for Smart Building Applications
View ProjectEE5111-Channel-Sim
February 17, 2019 – May 3, 2019
EE 5111: Estimation Theory; Miniproject
View Projectconv-numba
October 3, 2018 – October 5, 2018
Implementation of Image Convolutions using Numba
View Projectdilated-dense-fusion-networks
September 21, 2018 – November 3, 2018
Deep Boosting for Image Denoising (ECCV 2018)
View Projectfast-cv
September 7, 2018 – November 13, 2018
Parallelized Video Processing implementations using OpenCV in Python, ffmpeg
View ProjectDBPN-tf
August 27, 2018 – October 15, 2018
Implementation of Deep Back-Projection Networks For Super-Resolution using Tf and Keras
View ProjectCSRNet-tf
August 25, 2018 – September 8, 2018
Unofficial Implementation of CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
View ProjectFast-image-classification
June 15, 2018 – July 18, 2018
Fast image classification using Bottlenecks
View ProjectEmotion-detection
August 6, 2017 – August 30, 2024
Real-time Facial Emotion Detection using deep learning
View ProjectObject-Localization-and-Tracking
March 31, 2017 – January 15, 2018
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View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards individual research and development in deep learning and computer vision. The diversity of projects, all within the AI/ML domain, aligns well with a specialized Data Scientist role. However, the lack of team projects or professional experience makes it difficult to assess broader cultural fit aspects like collaboration or adaptability in a corporate environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise, but there is no information on collaboration, communication style, or problem-solving approach in a team setting.