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amanchadha/README.md

About

🔭 I'm passionate about Artificial Intelligence, Deep Learning, Machine Learning, Computer Vision and Natural Language Processing. I have previously worked in the fields of Computer Architecture, Signal and Image Processing, Biometrics and Pattern Recognition.

💭 My personal mission is to build AI-based solutions that solve a high-impact problem for people around the globe and simplify everyday living.

👯 I'm interested in mentoring, coaching and collaborating with fellow enthusiasts in the field of AI. If you have an idea related to my areas of interest, feel free to shoot me an email!

👉🏼 Follow me on LinkedIn or NeuralNets to stay updated with my AI primers and papers.

Bio

🧠 I currently head a Generative AI R&D team of Scientists and Managers at AWS. Previously, I led Speaker Understanding and Personalization at Amazon Alexa AI.

⌛️ Prior to Amazon, I was part of the Machine Intelligence Neural Design (MIND) team at Apple, where I specialized in designing AI models for a wide range of applications including Natural Language Processing, Speech Recognition, and Computer Vision. Prior to that, I was one of the early architects of Apple's M1 chip, which involved developing models for estimating performance of future Macs years in advance. Before Apple, I spent a couple of years at Nvidia and Qualcomm working on GPUs and ML Accelerators. I am a recipient of the EB-1 "Einstein Visa" (conferred by the US Government for extraordinary ability and acclaim in a specialized field).

🌱 I pursued my graduate studies part-time in Computer Science with a specialization in Artificial Intelligence from Stanford University.

🎓 I received my Masters in Electrical and Computer Engineering with a specialization in Computer Architecture from the University of Wisconsin-Madison and graduated in 2014 with an outstanding graduate student award.

📚 I am a distinguished alumnus of the University of Mumbai, one of the largest universities in the world.

📝 As a Research Fellow at universities around the US and India, I advise AI research projects and have published in leading venues such as ACL, EMNLP (Outstanding Paper Award '23), AAAI, EACL, ECIR, ECML, WSDM, ICASSP, etc. Our work has been featured in The Washington Post, Wikipedia, New Scientist, Analytics India Magazine, YourStory, etc.

🏃🏻‍♂️ Outside of work, I like hiking, gardening, skiing, and working out.

Personal Profile

🧑🏻‍💻 aman.info

AI Portfolio

💼 aman.ai, which contains course notes and learning material for Artificial Intelligence and Deep Learning Stanford classes.

AI Community

🌎 neuralnets.ai, a one-stop shop for AI learning resources.

Connect

Aman Chadha's LinkedIn Aman Chadha's Google Scholar Aman Chadha's Twitter

GitHub Stats

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  1. iSeeBetter iSeeBetter Public

    iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computat…

    C++ 360 68

  2. FRVSR-GAN FRVSR-GAN Public

    A Novel Approach to Video Super-Resolution using Frame Recurrence and Generative Adversarial Networks | Python3 | PyTorch | OpenCV2 | GANs | CNNs

    Python 59 13

  3. MDVC MDVC Public

    Forked from v-iashin/MDVC

    PyTorch implementation of Multi-modal Dense Video Captioning (CVPR 2020 Workshops)

    Python 2

  4. 100-nlp-papers 100-nlp-papers Public

    Forked from mhagiwara/100-nlp-papers

    100 Must-Read NLP Papers

    40 19

  5. sotawhat sotawhat Public

    Forked from chiphuyen/sotawhat

    Returns latest research results by crawling arxiv papers and summarizing abstracts. Helps you stay afloat with so many new papers everyday.

    Python 5 1

  6. LeetCode-Solutions LeetCode-Solutions Public

    Forked from kamyu104/LeetCode-Solutions

    :octocat: (Weekly Update) Python / Modern C++ Solutions of All 1643 LeetCode Problems

    C++ 11 14