aadya natesan
Software Development Engineer II at Amazon
software development engineer amazon
Amazon
https://www.linkedin.com/company/amazon
Seattle, Washington, United States
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Software Development Engineer II
Amazon
https://www.linkedin.com/company/amazon
Seattle
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Software Development Engineer
Carnegie Mellon University
https://www.linkedin.com/company/carnegie-mellon-university
Greater Pittsburgh Area
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Graduate Research Assistant
IIT Madras
Interned under Dr. Anil Prabhakar for a period of 2 months. Conducted extensive research and prepared a literature survey on the working of “LIGO- Laser Interferometer Gravity Wave Observatory” to be used in building a working prototype.
Chennai Area, India
Summer Research Intern
Master of Science - MS
Electrical and Computer Engineering
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Carnegie Mellon University
https://www.linkedin.com/school/carnegie-mellon-university/
Bachelor of Engineering (BE)
Electrical, Electronics and Communications Engineering
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Sri Sivasubramaniya Nadar College Of Engineering
https://www.linkedin.com/school/sri-sivasubramaniya-nadar-college-of-engineering/
A miniature two‐element MIMO multiband planar patch antenna with potential applications in the ISM bands is presented.
A Penta-band Hybrid Fractal MIMO Antenna for ISM Applications
International Journal of RF and Microwave Computer-Aided Engineering
https://doi.org/10.1002/mmce.21185
Scholarship for Higher Education  under the Innovation in Science Pursuit for Inspired Research (INSPIRE) program for the top 1% all India in ISC 2013.
Department of Science and Technology, Govt of India
Scholarship for Higher Education Top 1% All India
Sishya School, Chennai
Lakshmi Sarma Muthuswamy Prize for Best Performance in ISC Mathematics
Sishya School, Chennai
Kalyani Sundaram Memorial Prize for Best Performance in ICSE English
Advanced Digital Signal Processing
-
Algorithms and Advanced Data Structures
15650
Applied Stochastic Processes
18751
Computer Vision
16720
Introduction to Deep Learning
11785
Introduction to Machine Learning
10601
Methods in Medical Image Analysis
16725
Natural Language Processing
11611
Visual Learning and Recognition
16824
Kaizen Robotics Program - Basic Level
-
Transcribe a given speech utterance to its corresponding transcript by implementing an encoder with Pyramidal BiLSTM Structure with pooling, attention networks over high level representations and a decoder to predict the next word on each timestep, with the beam search algorithm. Based on the Listen, Attend and Spell model.
Attention-based End-to-End Speech-to-Text Deep Neural Network
Using MRI Scans from the Human Connectome project to convert between T1 and T2 weighted images by performing medical image translation. Used conditional GANs by testing the capabilities of the Unsupervised Image to Image Translation Network by NVIDIA. Improvements made included implementing self-attention layers, spectral normalization and charbonnier loss, and evaluation performed using SSIM Index.
GAN Based Translation between Medical Image Modalities
Implemented a Lucas-Kanade tracker with accommodations for large appearance variation and template correction, including motion subtraction to track moving pixels in a scene, perform efficient tracking using inverse composition and correlation filters.
Object Tracking in Videos
Implemented and trained a fully connected neural network to recognize handwritten letters and digits from the NIST36 dataset, visualize weights, perform image compression and learning using Variational Autoencoders and compare its performance to Principle Component Analysis.
Convolutional Neural Networks for OCR
Design a recurrent neural network to predict phonemes present in input speech recordings. Trained with unaligned phoneme labels, using stacked BiLSTM layers, Adam optimizer and CTC Loss to infer alignment. Predictions are decoded with beam search.
Prediction of Phonemes contained in Speech Segments using RNNs
Computing the Fundamental Matrix between a pair of images using the Eight and Seven Point Algorithm, finding the Essential Matrix, reconstructing the 3d scene structure, visualizing it and performing bundle adjustment for correction.
3D Reconstruction of Scenes
Designed a RESNET to determine whether two speech segments were uttered by the same speakers. Convolutional layers are used to extract shift invariant features and to create speaker embeddings from input utterances, training is performed through n way classification and cosine similarity used to generate similarity scores between pairs of recordings.
Speaker Verification with CNNs
Computing SIFT, BRIEF descriptors and RANSAC to find homographies between multiple images, to use in image warping and transformations for applications in Panoramic Image Stitching and Augmented Reality.
Panoramic Image Stitching
Perform frame level phoneme state classification of raw mel spectrogram frames of speech recording by implementing a feedforward neural network and adding temporal context to each sample.
Speech Recognition by Performing Frame Level Classification
Perform K-means clustering on DoG Pyramid of Images and classify using K-Nearest Neighbours.
Scene Classification using Bag of Words
Using methods such as Region Growing, Thresholding and Masking to perform automatic segmentation of pulmonary nodules and lesions from a dataset of CT scans of the lungs, implemented with SimpleITK.
Segmentation of Pulmonary Nodules
Final Year Project to build a voice activated security system that uses continuous digit recognition along with randomly generated passwords to distinguish between the user and recordings of the user. Implemented using Mel Frequence Cepstrum Coefficients, Guassian Mixture Models and Fuzzy Vector Quantization
Speech Recognition Security System
Interact: Rotary Sponsored Club
https://www.linkedin.com/company/rotary-interact
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Office Head
https://www.linkedin.com/in/kaitlyn-lewis-096870158
Sammamish, WA
Kaitlyn Lewis
Master of Science - MS in Mechanical Engineering at the University of Washington
https://in.linkedin.com/in/sanjithkanagavel
Hyderabad
Sanjith Jothi Kanagavel
Software Engineering Lead - macOS at Apple
https://www.linkedin.com/in/nandagopal-srinivasan
Boston, MA
Nandagopal Srinivasan
Engineer (Motion Planning) at Motional
https://www.linkedin.com/in/anuj-ahluwalia
Seattle, WA
Anuj Ahluwalia
Machine Learning @ Amazon | Carnegie Mellon University
https://uk.linkedin.com/in/sri-vishnu-kumar-karlapati
Greater Cambridge Area
Sri Vishnu Kumar Karlapati
Applied Scientist II at Amazon | MSc in Computer Science - University of Oxford '18 | Ex-Software Engineer at Microsoft
https://www.linkedin.com/in/shreyas-chaudhari
Amherst, MA
Shreyas Chaudhari
PhD Candidate at UMass | CMU | IIT Madras
https://www.linkedin.com/in/akshayravichandran
San Francisco Bay Area
Akshay Ravichandran
Software Engineer at Google
https://ca.linkedin.com/in/apeksha-avinash
Greater Toronto Area, Canada
Apeksha Avinash
Research Engineer at RoboEye.ai
https://www.linkedin.com/in/abhijith-mandya
Greater Boston
Abhijith Mandya
Senior Data Scientist at Red Hat
https://www.linkedin.com/in/sanjana-smruthi-srinivasan
San Francisco, CA
Sanjana Smruthi Srinivasan
Product Manager at Vicarious AI
https://www.linkedin.com/in/amrithasudarsan
Hyattsville, MD
Amritha Sudarsan
Human Computer Interaction Master's student at University of Maryland
https://in.linkedin.com/in/om-prakash-s-661757167
Chennai
Om Prakash S
labview and python developer at HCL Technologies
https://www.linkedin.com/in/nandan-pitre
Pittsburgh, PA
Nandan Pitre
Ph.D Student at University of Pittsburgh, Bioengineering
https://www.linkedin.com/in/varsha-murali-930a04154
Seattle, WA
Varsha Murali
Software Engineer at Microsoft
https://in.linkedin.com/in/adithya-prem-anand
Chennai
Adithya Prem Anand
Machine Learning Engineer at Mad Street Den
https://www.linkedin.com/in/amelia-barr
Seattle, WA
Amelia Barr
Mechanical Engineering Student at the University of Washington
https://www.linkedin.com/in/swasthik
Greater Hartford
Swasthik B.
MS in Mechanical Engineering | 6+ years of industry experience in Manufacturing | FEA | CAE | CAD | Product Design
https://in.linkedin.com/in/naveen-k-533b081a1
Chidambaram
Naveen K.
Learner |Cricket lover|
https://www.linkedin.com/in/rahul95ram
Palo Alto, CA
Rahul Ramanarayanan
Robotics Engineer at Bear Flag Robotics | Human Robot Interaction, Computer Vision and Product
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At The Slime Space, we are all about employing creative and unique ways to promote our products on social media. Majority of our customers find us…
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So many people would tell me that this business was just a waste of time and to focus on my college course. But I managed to prove them wrong and…
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The Slime Space is launching a new product very soon! So excited to finally tell you all that we’ve been working on a prototype of an extremely cool…