
Hi, I’m Sadanand Singh. I work at Micron. I lead teams building AI models and DS solutions in DRAM and NAND manufacturing. I am an avid lover of Algorithms, Python, Rust, C++, Javascript. My background is in computational physics, numerical modeling and optimization and software design. I have a PhD in computational physics/chemical engineering focusing on computational models of nano-materials and bio-molecules.
My active area of research is in applications of statistics, machin learning, deep learning and computer vision in manufacturing, medical imaging and in the radiology business. I am specifically interested in designing AI models that are explainable and tractable.
Research Interests
- Applications of deep learning algorithms to multi-modal screening mammography for classification and localization of cancer
- Development of explainable AI models for medical applications.
- Domain adaptation of Deep Leaning and Machine Learning models
- Self-supervised learning to incorporate large amounts of unlabeled medical data
- Applications of modern web technologies to make deep learning research more transparent, reproducible and easy to share.
- Using fundamentals of stochastic learning to model consumer behavior.
CV
AI and Computer Vision Skills
Skills I acquired during 10+ years of being in grad school and tech industry
Deep Learning / Machine Learning
- PyTorch, Tensorflow and Keras
- Self Supervised Learning
- GANs & Autoencoders
- Mlflow Development
- Tree-based Models
- Support Vector Machines
- Clustering Algorithms
- Mixture Models
Medical Imaging
- Breast Screening
- Tomography Synthesis Images
- Anamoly Detection
- Object Detection with Detectron2
- Medical Imaging In-painting via GANs
- Trust in Medical AI systems
- Explanatory Models
Web Development Skills
Skills I learned during my free time and special during the quarantine
Front-end Development
- React: Gatsby
- Tailwind CSS and Component Libraries
- 11ty
- SEO-friendly and Accessible Designs
Backend Development
- MongoDB
- PostgreAQL
- Flask
- Graphql
Publications
2022
Deep is a Luxury We Don't Have
Ahmed Taha, Nhi Truong Vu, Brent Mombourquette, Thomas P. Matthews, Jason Su, Sadanand Singh
2021
An improved mammography malignancy model with self-supervised learning
Nhi Truong Vu, Trevor Tsue, Jason Su, Sadanand SinghA Multisite Study of a Breast Density Deep Learning Model for Full-Field Digital Mammography and Synthetic Mammography
Thomas P. Matthews, Sadanand Singh, Brent Mombourquette, Jason Su, Meet P. Shah, Stefano Pedemonte, Aaron Long, David Maffit, Jenny Gurney, Rodrigo Morales Hoil, Nikita Ghare, Douglas Smith, Stephen M. Moore, Susan C. Marks, Richard L. Wahl
2020
Adaptation of a deep learning malignancy model from full-field digital mammography to digital breast tomosynthesis
Sadanand Singh, Thomas P. Matthews, Meet Shah, Brent Mombourquette, Trevor Tsue, Aaron Long, Ranya Almohsen, Stefano Pedemonte, Jason SuA hypersensitive breast cancer detector
Stefano Pedemonte, Brent Mombourquette, Alexis Goh, Trevor Tsue, Aaron Long, Sadanand Singh, Thomas P. Matthews, Meet Shah, Jason Su
2019
2013
Ultrastable glasses from in silico vapour deposition
Sadanand Singh, M. D. Ediger, Juan J. de Pabloα-helix to β-hairpin transition of human amylin monomer
Sadanand Singh, Chi-Cheng Chiu, Allam S. Reddy, Juan J. de PabloEffect of Proline Mutations on the Monomer Conformations of Amylin
Chi-Cheng Chiu, Sadanand Singh, Juan J. de PabloStructure and Thermodynamic Stability of Islet Amyloid Polypeptide Monomers and Small Aggregates
Chi-Cheng Chiu, Sadanand Singh, Juan J. de Pablo
2012
Efficient Free Energy Calculation of Biomolecules from Diffusion-Biased Molecular Dynamics
Sadanand Singh, Chi-Cheng Chiu, Juan J. de PabloDensity of States–Based Molecular Simulations
Sadanand Singh, Manan Chopra, Juan J. de PabloTwo-dimensional infrared spectroscopy reveals the complex behaviour of an amyloid fibril inhibitor
Chris T. Middleton, Peter Marek, Ping Cao, Chi-Cheng Chiu, Sadanand Singh, Ann M. Woys, Juan J.de Pablo, Daniel P. Raleigh, Martin T.ZanniMolecular modeling of ultra-stable vapor deposited glasses
Sadanand Singh, Chi-Cheng Chiu, Devin Averett, Juan J. de PabloEffect of Lipid Bilayer on Human Islet Amyloid Polypeptide Self Assembly
Sadanand Singh, Chi-Cheng Chiu, Juan J. de Pablo
2011
Flux Tempered Metadynamics
Sadanand Singh, Chi-Cheng Chiu, Juan J. de PabloA molecular view of vapor deposited glasses
Sadanand Singh, Juan J. de Pablo2DIR Spectroscopy of Human Amylin Fibrils Reflects Stable β-Sheet Structure
Lu Wang, Chris T. Middleton, Sadanand Singh, Allam S. Reddy, Ann M. Woys, David B. Strasfeld, Peter Marek, Daniel P. Raleigh, Juan J.de Pablo, Martin T.Zanni, James L.SkinnerEarly aggregation studies of diabetic amyloid in solution
Sadanand Singh, Juan J. de PabloStrategies to counter aggregation of human amylin in solution
Sadanand Singh, Juan J. de PabloEarly stage aggregation studies of diabetic amyloid in solution and membranes
Sadanand Singh, Chi-Cheng Chiu, Allam S. Reddy, Juan J. de PabloMolecular characterization of dimerization of human amylin peptide in solution
Sadanand Singh, Chi-Cheng Chiu, Juan J. de PabloStructures of human amylin in the presence of lipid bilayers
K. Q. Hoffmann, Sadanand Singh, Chi-Cheng Chiu, Juan J. de Pablo
2010
Stable and Metastable States of Human Amylin in Solution
Allam S. Reddy, Lu Wang, Sadanand Singh, Yun L. Ling, Lauren Buchanan, Martin T.Zanni, James L.Skinner, Juan J.de PabloMolecular modeling of a stable glass -- the case of trehalose
Sadanand Singh, Devin Averett, Juan J. de PabloMisfolding of diabetic amyloid in solution
Sadanand Singh, Allam S. Reddy, Juan J. de PabloAggregation of diabetic amyloid at biological interfaces
Sadanand Singh, Chi-Cheng Chiu, K. Q. Hoffmann, Allam S. Reddy, Juan J. de Pablo
2009
Molecular modeling of physical vapor deposited stable glasses
Sadanand Singh, Juan J. de Pablo
2008
Case Study on Tubular Reactor Hot-Spot Temperature Control for Throughput Maximization
Sadanand Singh, Shivangi Lal, Nitin Kaistha