From 2d2203e2326dbac13872c2762844c5b12ff80514 Mon Sep 17 00:00:00 2001 From: Medha Sawhney Date: Fri, 15 Mar 2024 16:29:37 +0000 Subject: [PATCH] Update cv.yml --- _data/cv.yml | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/_data/cv.yml b/_data/cv.yml index 5b3edb62..98296196 100644 --- a/_data/cv.yml +++ b/_data/cv.yml @@ -36,12 +36,14 @@ - title: Corporate Experience type: time_table contents: - - title: Deep Learning Intern + - title: Deep Learning Intern institution: NVIDIA + department: Deep Learning Focus Group year: MAY 2024 - AUG 2024 location: Santa Clara - title: Machine Learning Engineering Intern institution: Twitter + department: ML Health Team year: JUN 2022 - AUG 2022 location: US (Remote) description: @@ -49,6 +51,7 @@ - "Boosted Key performance indicators by 74%. Challenges: Data imbalance, feature sparsity, enormous data, data distribution drift" - title: Machine Learning Engineer institution: Hewlett-Packard R&D + department: R&D Data Science Team year: JAN 2020- JUN 2021 location: Bangalore, India description: @@ -61,7 +64,8 @@ type: time_table contents: - title: Graduate Research Assistant - institution: Science Guided Machine Learning Lab, Virginia Tech + institution: Virginia Tech + department: Kowledge Guided Machine Learning Lab year: Since 2021 location: Blacksburg, VA, US description: @@ -69,13 +73,15 @@ - Engineered an approach to predict force applied by a human cell on underlying fiber intersections using multi-object detection techniques in Computer Vision like RetinaNet. - Established a pipeline to convert phased-out microscopic imagery of human cell environment to fluorescent images using Pix2Pix and formulated statistical techniques to quantify the results - title: Graduate Research Assistant - institution: Informatics Lab, University Libraries at Virginia Tech + institution: Virginia Tech + department: Informatics Lab, University Libraries year: AUG 2021 - DEC 2021 location: Blacksburg, VA, US description: - "Developed a Computer Vision solution to detect plant wilting. Improved performance accuracy by 10% with traditional methods like Support Vector Machines and feature engineering. Challenges: class imbalance, small dataset, images of varying resolutions" - title: Research Intern - institution: CVIT Lab, IIIT Hyderabad + institution: IIIT Hyderabad + department: CVIT Lab year: MAY 2019 - JUL 2019 location: Hyderabad, India description: