Renu Rani

CS Graduate Student | renu170987@gmail.com


I'm a Graduate student of Computer Science at Stony Brook University. I bring along 4 years of Software Development experience in Adobe Systems accompanied with strong fundamentals of computer science, a zest for challenges, and enthusiastic desire to learn all I can. My experience in writing customer facing application generating revenue in billions of dollars makes me mature enough to write high standard of code while following the industry standards. The knowledge from my graduate and undergraduate courses and projects make me equipped to solve the real-world challenges. I look forward to add more versatility to my career and establish myself by gaining expertise in architecting innovative solutions.



Master of Science in Computer Science
Stony Brook University
GPA: 4.0/4.0
Member of Human Interaction Lab: Generative Adversarial Networks (GANs) and Machine Learning


Bachelor of Technology in Computer Engineering
National Institute of Technology Kurukshetra (NIT KKR)

JULY 2009 - JUNE 2013


Adobe Systems
Memeber of Technical Staff 2

  • Worked on different components of AEM (Adobe Experience Manager) such as CM, Forms, etc. AEM helps businesses to deliver a uniform experience across multiple platforms. Implemented responsive UI framework from scratch for AEM Workflow, a model that enables the user to automate processes for managing resources, and integrated it with other AEM components.
  • Worked on CM (Correspondence Management), a solution that streamlines personalized correspondence creation, its management, and secure delivery. Worked on various POC for CM such as Mobile Form integration and lead them to management approval and final delivery. Implemented various features, handled migrations, and delivered hotfixes and various customization support.
  • Moved Form Management, a tool for non-IT users to create an engaging end-to-end experience, from flex framework to HTML UI to make it a part of AEM Forms and added new features to it.
  • Contributed to CoralUI, an Adobe‚Äôs internal open source UI framework used in Adobe Marketing Cloud products, and also implemented pluggable components such as Color Picker and Coral Tree.
  • Represented AEM Forms in UI Extended Team, a platform for engagement between Platform UI team and other AEM teams, making UI designing easy and standardized across all AEM components.

JUNE 2013 - AUGUST 2017






Html 5 / CSS 3



GANs Research Project

Generated fake yet real single-channel images of yeast cell by modifying BIO-GAN convolution neural network. Currently, trying to come up with a method to generate corresponding segmentation mask along with the generated image for bio-medical data using Generative Adversarial Networks.
Technologies used: DCGAN, Python 3, CUDA.

FALL 2017

Infant Mortality Data Analysis

A framework to help achieve UN's SDG 3.2. This framework can predict the risk of infant death and provide similar pregnancy cases for reference to aid the doctors in taking informed decisions.
Technologies used: Python 3, Spark, Machine learning, PCA, K-means Clustering, Similarity Search.

FALL 2017

Face Detection and Tracking

Implemented a face detector using Viola-Jones and tracking the detected face using Camshift, Kalman filter, Particle filter, and Optical Flow tracker.
Technologies used: Python 2.7, OpenCV.

FALL 2017

Image Segmentation and Panorama

Implemented an interface to segment foreground and background of an image using SLIC superpixels and graph cuts. Also, implemented image panorama stitching by matching SIFT features and blending the output images using Laplacian pyramid.
Technologies used: Python 2.7, OpenCV.

FALL 2017


Reconstructed a 3-D scene of an object by calculating depth map using multiple structured light scanning, projector-camera calibration, and stereo triangulation.
Technologies used: Python 2.7, OpenCV.

FALL 2017

Convolution Neural Network

Trained an MNIST CNN classifier for digits 1,4,5,9 and added new layers on top of this trained model to classify the remaining digits: 0,2,3,6,7,8.
Technologies used: Python 2.7, TensorFlow.

FALL 2017

Spam Filter

Implemented a spam/ham filter using Multinomial Naive Bayes classifier.
Technologies used: Python 2.7

FALL 2017

Blood Bank Management System

Designed an Android app to fulfill the blood requirements in an emergency by informing the user about the donors and hospitals having stock of the blood group needed.
Technologies used: Android, Java.

FALL 2012

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