Aakaash Jois
Machine Learning Engineer at Xandr
Software Engineer II - Machine Learning Engineer at Xandr (part of AT&T) | Formally Machine Learning Engineer at Kalepa
A graduate from New York University with a Master of Science Degree in Electrical and Electronics Engineering focusing on Deep Learning applied to Image Processing and Machine Learning. I have an interest in Computer Vision.
Xandr
https://www.linkedin.com/company/xandr
New York City Metropolitan Area
https://media-exp1.licdn.com/dms/image/C4D0BAQFCpt8D_P2UTQ/company-logo_100_100/0/1631050100930?e=1655942400&v=beta&t=JzqfeLOloyVZWM8GBgQL8ytdb_hTIuxWhhtyRUwSDDE
Machine Learning Engineer
Kalepa
https://www.linkedin.com/company/kalepa
- Developed from the ground up end-to-end machine learning models and scalable API services in a rapid startup environment
- Created pipelines to ingest and normalize useful information from social media, news, and other public accessible sites
- Contributed to design and implementation of distributed services and data warehousing to handle large data ingestion
- Created explainable AI models to explain predictions and insights
- Developed NLP models based on Spacy, BERT, Universal Sentence Encoder models and deployed on AWS SageMaker
- Implemented classification models to provide high risk insights to insurance underwriters
- Developed computer vision models for risk identification and deployed on Google Cloud
- Experience working with highly imbalanced and noisy datasets
Greater New York City Area
https://media-exp1.licdn.com/dms/image/C560BAQHY0vArjiF_zA/company-logo_100_100/0/1519902295034?e=1655942400&v=beta&t=_T-vf3eKtq14_b-8jMt7Mdbx8sBCGYJRLF8n2Xzd6Os
Machine Learning Engineer
NYU Tandon School of Engineering
https://www.linkedin.com/company/nyutandonschoolofengineering
- Provided guidance to students toward class lectures, assignments, and projects
- Collaborate with the professor on creation and grading of assignments and exams
Greater New York City Area
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Graduate Teaching Assistant for Big Data
Frenzy.ai
https://www.linkedin.com/company/frenzy.me
- Created a Hierarchical CNN model to classify fashion items in images
- Performed data engineering techniques to obtain optimal classification result from the Hierarchical CNN model
Greater New York City Area
https://media-exp1.licdn.com/dms/image/C4D0BAQH9MDmJIntszQ/company-logo_100_100/0/1519895871546?e=1655942400&v=beta&t=b2OWRpGFyo65YV9rkmpTDzgM-_PrW5jNpmqh3Shnluw
Deep Learning Research Volunteer
Frenzy.ai
https://www.linkedin.com/company/frenzy.me
- Worked on multiple Region-based CNN models to identify fashion items in images
- Modified the previous model to increase accuracy by 30%
- Implemented a Pose Estimation model to identify the structural pose of the humans in images
- Created a testing script to increase the inferencing speed of models by 20%
- Developed a fallback method to identify fashion apparel when CNN models fail
Greater New York City Area
https://media-exp1.licdn.com/dms/image/C4D0BAQH9MDmJIntszQ/company-logo_100_100/0/1519895871546?e=1655942400&v=beta&t=b2OWRpGFyo65YV9rkmpTDzgM-_PrW5jNpmqh3Shnluw
Deep Learning Research Intern
Udacity
https://www.linkedin.com/company/udacity
- Provided detailed analysis and actionable feedback for over 4500 projects of students to improve the code and meet standards
- Guided and supported students towards completion of Nanodegree in Data Science and Android Development field
Bengaluru Area, India
https://media-exp1.licdn.com/dms/image/C560BAQGAbiASb657Fg/company-logo_100_100/0/1639683820896?e=1655942400&v=beta&t=VoAj7tltPTdUB0DrFxCI7Tut4a3ckoMlfyLkHDu8OyU
Mentor & Code Reviewer
ISRO Satellite Centre
- Implemented computer vision algorithms on the Chandrayaan-2 project with Controls Division and Electronics Group team
- The algorithm helps the lunar rover identify the distance of objects seen by its stereoscopic camera
Bengaluru Area, India
Project Intern
Master of Science - MS
Electrical Engineering
https://media-exp1.licdn.com/dms/image/C4D0BAQFDeOVQn-KX0Q/company-logo_100_100/0/1559248562866?e=1655942400&v=beta&t=yxJEGZ-wlddG1Az5UcW47Ma84btJmmKiIUt7gLBWC98
NYU Tandon School of Engineering
https://www.linkedin.com/school/nyutandonschoolofengineering/
Bachelor of Engineering - BE
Electronics and Communications Engineering
https://media-exp1.licdn.com/dms/image/C4D0BAQEXLsH7UX9uMw/company-logo_100_100/0/1519865269158?e=1655942400&v=beta&t=A8DkvtSozacTw7aXChbN-wvrxmiFcqmEMIgn6oGpHVw
Visvesvaraya Technological University
https://www.linkedin.com/school/visvesvaraya-technological-university/
Pre University
Electronics
Sri Kumarans Children's Home Composite Pre-University College
High School
Little Flower Public School
Primary School
Auden Public School
Digital Communication has become an essential part of real world applications. A lot of applications are internet based and in some cases, it is desirable for the communication to be carried out in secret. Information hiding is a technique of hiding a secret/confidential data into a host medium in such a way that the hidden data is imperceptible but known by the intended recipient. In this paper, Data hiding techniques using various Least Significant Bit (LSB) Substitution Techniques are explored. A comparative analysis is made using 4 different LSB substitution methods, Simple LSB Substitution, Fibonacci Decomposition LSB Substitution, Prime Number Decomposition LSB Substitution and Natural Number Decomposition LSB Substitution. The advantages and disadvantages of each method over the previous are expressed in this paper.
Survey on LSB Data hiding techniques
IEEE
http://ieeexplore.ieee.org/abstract/document/7566214/
Audio Content Analysis
EL - GY 9173
Digital Signal Processing - I
EL-GY 6113
Fundamentals of Robot Mobility
ECE-GY 9253
Image and Video Processing
EL-GY 6123
Introduction to Machine Learning
EL-GY 9123
Probability and Stochastic Processes
EL-GY 6303
Programming for Big Data Analytics
CS-GY 9223
Android Basics Nanodegree - Udacity
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Shaw Academy - Diploma in Photography
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Thinkful - Front End Web Developer
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Plant Tracer is an app which tracks the apex of a plant in a time-lapse video of the plant growing. My part in this project involved, annotating the time-lapse videos to find the apex of the plant and trying to create a robust deep learning model to track the apex of the plant. The model was designed to be simple and light so that it can be deployed on mobile apps in the future. The model was based on a well-known object tracking architecture "GOTURN". The architecture was improved to track the plant apex during occlusions.
Plant Tracer
https://github.com/aakaashjois/Plant-Tracer
News Dashboard is a large scale news summarizer working to simplify the lives of its user by providing shortened, easily readable news and various insights.

News Dashboard utilizes Big Data Technologies available to extract news articles from multiple sources, create a summary using NLP techniques and extract keywords to provide insights and visualizations related to the news articles.
News Dashboard
https://github.com/aakaashjois/News-Dashboard
Convert grayscale image to a colored image using different deep learning techniques. We use 4 different models to try and colorize the grayscale image.
1. Deep Koalarization
2. Inception-VGG AutoEncoder
3. VGG AutoEncoder
4. GAN (Experimental)
Colorizing Grayscale Images
https://github.com/aakaashjois/Colorizing-Grayscale-Images
The project involved classifying one-second long human speech commands. Three models were implemented in Keras with 3 different models:

1. ConvNet
2. DenseNet
3. Dense-Recurrent Net

The project validates that a variety of end-to-end deep learning architectures can be used reliably to classify human speech commands. A comprehensive evaluation metric was explored to convey a realistic expectation of the model's performance.
Dense Recurrent Net For Speech Command Classification
https://github.com/aakaashjois/Dense-Recurrent-Net-For-Speech-Command-Classification
The aim of this project is to perform pixel-wise classification on a car image dataset. Each pixel
on the image should be classified as either ’background’ or ’car’ class, forming a mask on the car
image. This type of image classification is called Image Segmentation. A neural network model
with U-Net architecture has been implemented to achieve this goal. The U-Net performance
was tested on 4 different training setups with changing input sizes and added image augmentations.
Our best model has achieved an accuracy of 98.96% in this image segmentation problem.
Background Separation using U-Net
https://github.com/aakaashjois/Background-Separation-using-U-Net
Implemented edge and feature detection, feature description, feature matching and point cloud generation from scratch in MATLAB to work with a stereoscopic camera mounted on top of a lunar rover. The algorithm was able to identify distance of object with a resolution of 10 centimeters and determine the orientation tilt of the rover.
Depth and Orientation Estimation using Stereo-Vision
https://www.linkedin.com/in/roshansridhar
New York City Metropolitan Area
Roshan Sridhar
Data Scientist II at Verisk
https://www.linkedin.com/in/vikrambajaj22
New York City Metropolitan Area
Vikram Sunil Bajaj
Associate Software Engineer - Machine Learning at Deutsche Bank | NYU Alumnus
https://in.linkedin.com/in/akshaydeo27
Pune
Akshay Deo
Senior Software Engineer at Xandr Go | AWS | Terraform | React | Rust
https://www.linkedin.com/in/gaurisarode
San Francisco Bay Area
Gauri Sarode
Machine Learning Engineer at Grubhub
https://www.linkedin.com/in/sameer-korlahalli
Bellevue, WA
Sameer Korlahalli
Software Development Engineer I at Amazon
https://www.linkedin.com/in/shradhataneja
Brooklyn, NY
Shradha Taneja
Software Development Engineer at Amazon Web Services (AWS) | NYU
https://www.linkedin.com/in/gavin-hackeling-91668820
Brooklyn, NY
Gavin Hackeling
Author, Engineer, Data Scientist. Hiring engineers and data scientists
https://www.linkedin.com/in/nirupamasuresh
Greater Boston
Nirupama Suresh
SDE at Amazon Robotics
https://pl.linkedin.com/in/marcin-kuczara
Warsaw
Marcin Kuczara
Senior Software Engineer at Kalepa
https://www.linkedin.com/in/akhil-wadhwa
Colorado Springs, CO
Akhil Wadhwa
Firmware Engineer at Sanmina | NYU'20
https://www.linkedin.com/in/tronak19
Greater Seattle Area
Ronak Thakkar
Software Engineer II at Microsoft
https://in.linkedin.com/in/varun-krishna-965303ab
Bengaluru
Varun Krishna
Data Platform Engineer at Xandr | AT&T
https://www.linkedin.com/in/adarsh-patel-12546a101
Marlboro, NJ
Adarsh Patel
Software Engineer at Xandr (an AT&T Company)
https://www.linkedin.com/in/yashsshah
New York, NY
Yash Shah
Director of Data Science at Xandr, a Warner Media company
https://www.linkedin.com/in/tejaswinil
Boulder, CO
Tejaswini Lakshminarayan
Actively seeking internship opportunities for summer 2022 | Teaching Assistant and Graduate Student at University of Colorado Boulder
https://www.linkedin.com/in/prafulb
Rockville, MD
Praphulla Bhawsar
AI Engineer | PhD Student | Data Scientist in-the-making
https://www.linkedin.com/in/rachit-saluja
San Francisco Bay Area
Rachit Saluja
Machine Learning Engineer at Galileo CDS
Liked by Aakaash Jois
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Excited to share the news that Xandr is being acquired by Microsoft, so proud of our team and great to build upon a valued ten year partnership to…
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We are excited to share Kalepa's full conversation with Steve Eginoire, former Chairman & CEO of Lockton Affinity. A simple maxim: Enduring success…
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