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PhD in Computer Vision - Interned @ Facebook AI, Microsoft, Qualcomm
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
vivit_pytorch
April 23, 2021 – June 10, 2021
Implementation of ViViT: A Video Vision Transformer - Zipping Coding Challenge
View Projecttimeception
April 15, 2019 – May 3, 2019
Timeception for Complex Action Recognition, CVPR 2019 (Oral Presentation)
View ProjectTrafficSignRecognition
June 28, 2015 – February 7, 2017
TrafficSignRecognition — GitHub repository
View ProjectImageEvolution
June 12, 2015 – June 12, 2015
Generating an image using simple genetic algorithm
View ProjectFingerprintRecognition
May 9, 2015 – September 22, 2016
Fingerprint Recognition in runtime using images captured from mobile. Built using Android and OpenCV. Also built in MATLAB.
View ProjectTimeSeriesAnalysis
May 1, 2015 – May 21, 2015
Analysis of financial time series using Kalman filter.
View ProjectDerivativesPricingNN
April 5, 2015 – April 11, 2015
Discussing pricing the options using non-parametric models. RBF (Radial Basis Function), MLP (Multi Layer Perceptron), PPR (Projection Pursuit Regression) and SVR (Support Vector Regression).
View ProjectRecommenderSystem
February 27, 2015 – March 10, 2015
Recommender system to predict the ratings of the users for 'Jokes'.
View ProjectPortfolioOptimization
February 23, 2015 – February 26, 2015
Portfolio Optimization and efficient frontier using MATLAB. This project is a part of assignment for COMP6212 Computational Finance course, 2nd semester, MSc AI, University of Southampton.
View ProjectSceneRecognition
January 21, 2015 – February 28, 2015
Scene recognition using multiple feature extractors (tiny-images, D-SIFT, BoVW, PHoW) and different classifiers (KNN, SVM).
View ProjectCultural Fit Analysis
The candidate's project portfolio demonstrates a strong individual initiative and a passion for diverse technical challenges, particularly in computer vision, machine learning, and computational finance. However, all listed projects are personal, which limits insight into team collaboration or experience in a structured organizational environment. The target role is 'Data Scientist', and while the projects align well with the technical aspects of this role, the lack of professional experience or team-based projects makes it difficult to fully assess cultural fit for a collaborative team setting.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise and technically focused, but do not provide insight into collaboration, problem-solving approach, or communication style.