# Sadanand Singh

Principal AI Research Scientist

More than 12 years of experience with deep learning, machine learning, numerical modeling and scientific computing in production environments. Proficient in Python, C++ and Linux.

Technical Skills

Languages - Python, C++/C, Rust, R, JavaScript, Bash/zsh

Concepts - Deep Learning, Machine Learning, Medical Imaging, Computer Vision, Numerical Optimization

Tools/Environment - PyTorch, Tensorflow/Keras, SciKit-Learn, Pandas, Git

Frameworks/Libraries - React, Astro, Typescript, TailwindCSS

Data - PostgreSQL, MongoDB, GraphQL, JSON

Experience

CEO and Director of Research

Quantbox NA - 2023 - present | USA (Remote)

  • Cooking something cool and exciting…

Principal Scientist

MICRON - 2022 - 2023 | Hyderabad, India

  • 2 patents in applications of ML in semiconductor manufacturing
  • Developed causal analysis solutions for physical systems with minimal data
  • ML framework development for DRAM Layout Design optimization

Principal Research Scientist

WHITERABBIT.AI - 2018 - 2022 | Santa Clara, CA

  • Multiple publications in medical imaging AI for breast cancer detection
  • FDA approval process for breast density estimation
  • Models for customer engagement and prediction

Staff Engineer - Machine Learning

SAMSUNG - March 2018 - Aug 2018 | San Jose, CA

  • Deep learning research on anomaly detection
  • Machine learning solutions for extremely imbalanced data in manufacturing

Deep Learning Research Scientist

KLA TENCOR - 2017 - 2018 | Milpitas, CA

  • Developed deep learning applications in lithography, defect detection and image translation
  • Designed auto-encoder models for learning ellipsometry signals
  • Designed product for defect detection in lithography

RET Design Engineer

INTEL - 2013 - 2017 | Hillsboro, OR

  • Built efficient machine learning models to identify defects prior to production
  • Designed and built deep learning models for the optimal placement of sub-resolution features on PSM masks
  • Developed models and algorithms to design optical masks to enable lithography of 14nm, 10 nm and 7 nm nodes
  • Designed new python and C++ libraries and APIs for RET data analysis, visualization and debugging

Education

PhD in Chemical Engineering

University of Wisconsin - Madison - 2008 - 2013 | Madison, WI

Advisor: Prof. Juan de Pablo Thesis: Energy landscapes of proteins and glassy materials

B.Tech in Chemical Engineering

Indian Institute of Technology Kanpur - 2004 - 2008 | Kanpur, UP, India

Accomplishments

  • Six Intel Achievement Awards
  • 10+ publications in the highest profile journals including Nature Materials and Nature Chemistry
  • Work on ultra-stable glasses covered in regular media Source 1 Source 2
  • Work on diabetes protein structure modeling highlighted in media Source
  • Received one of the swiftest promotions in less than 3 years at Intel Corp. 2016
  • International student academic achievement award, UW-Madison, 2012-13
  • Ranked among top 0.5% of 400000+ students in nation-wide IIT entrance examination, 2004

Publications

I have 30+ publications in high-profile journals including Nature Materials, Nature Chemistry, and various medical imaging conferences. My work spans computational physics, medical AI, and semiconductor manufacturing. A selection of my most important publications:

  • Deep is a Luxury We Don’t Have - MICCAI 2022
  • An improved mammography malignancy model with self-supervised learning - SPIE Medical Imaging 2021
  • A Multisite Study of a Breast Density Deep Learning Model - Radiology: Artificial Intelligence 2021
  • Ultrastable glasses from in silico vapour deposition - Nature Materials (2013)
  • Two-dimensional infrared spectroscopy reveals the complex behaviour of an amyloid fibril inhibitor - Nature Chemistry (2012)

For a complete list of publications with full details, PDFs, and ArXiv links, visit my publications page or Google Scholar profile.