Publications (24)
Active Learning Guided Computational Discovery of 2D Materials with Large Spin Hall Conductivity
Abhijeet J. Kale, Sanjeev S. Navaratna, Pratik Sahu +3
Two-dimensional (2D) materials are promising candidates for next-generation spintronic devices due to their tunable properties and potential for efficient spin-charge interconversi…
CEGANN: Crystal Edge Graph Attention Neural Network for multiscale classification of materials environment
Suvo Banik, Debdas Dhabal, Henry Chan +4
Machine learning models and applications in materials design and discovery typically involve the use of feature representations or "descriptors" followed by a learning algorithm th…
Molecular-Resolution Imaging of Ice Crystallized from Liquid Water
Jingshan S. Du, Suvo Banik, Henry Chan +6
Despite the ubiquity of ice, a molecular-resolution image of ice crystallized from liquid water or the resulting defect structure has never been obtained. Here, we report the stabi…
Comparison of Deterministic and Probabilistic Machine Learning Algorithms for Precise Dimensional Control and Uncertainty Quantification in Additive Manufacturing
Dipayan Sanpui, Anirban Chandra, Henry Chan +2
We present a probabilistic framework to accurately estimate dimensions of additively manufactured components. Using a dataset of 405 parts from nine production runs involving two m…
Physics-Informed Tree Search for High-Dimensional Computational Design
Suvo Banik, Troy D. Loeffler, Henry Chan +4
High-dimensional design spaces underpin a wide range of physics-based modeling and computational design tasks in science and engineering. These problems are commonly formulated as…
A coarse-grained deep neural network model for liquid water
Tarak K Patra, Troy D. Loeffler, Henry Chan +3
We introduce a coarse-grained deep neural network model (CG-DNN) for liquid water that utilizes 50 rotational and translational invariant coordinates, and is trained exclusively ag…
Active Learning A Neural Network Model For Gold Clusters \& Bulk From Sparse First Principles Training Data
Troy D Loeffler, Sukriti Manna, Tarak K Patra +3
Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs d…
Active Learning the Coarse-Grained Energy Landscape For Water Clusters From Sparse Training Data
Troy D. Loeffler, Tarak K. Patra, Henry Chan +2
ANNs are currently trained by generating large quantities (On the order of or greater) of structural data in hopes that the ANN has adequately sampled the energy landscape…
Cost-sensitive detection with variational autoencoders for environmental acoustic sensing
Yunpeng Li, Ivan Kiskin, Davide Zilli +4
Environmental acoustic sensing involves the retrieval and processing of audio signals to better understand our surroundings. While large-scale acoustic data make manual analysis in…
AutoMOOSE: An Agentic AI for Autonomous Phase-Field Simulation
Sukriti Manna, Henry Chan, Subramanian K. R. S. Sankaranarayanan
Multiphysics simulation frameworks such as MOOSE provide rigorous engines for phase-field materials modeling, yet adoption is constrained by the expertise required to construct val…
Ice grains grow by dissolution, ripening and grain boundary migration
Henry Chan, Mathew J Cherukara, Badri Narayanan +3
Despite the exponential growth in computing resources and the availability of a myriad of different theoretical water models, an accurate, yet computationally efficient molecular l…
Mosquito detection with low-cost smartphones: data acquisition for malaria research
Yunpeng Li, Davide Zilli, Henry Chan +4
Mosquitoes are a major vector for malaria, causing hundreds of thousands of deaths in the developing world each year. Not only is the prevention of mosquito bites of paramount impo…
Impact Of Bike Sharing In New York City
Stanislav Sobolevsky, Ekaterina Levitskaya, Henry Chan +2
The Citi Bike deployment changes the landscape of urban mobility in New York City and provides an example of a scalable solution that many other large cities are already adopting a…
Impact Of Urban Technology Deployments On Local Commercial Activity
Stanislav Sobolevsky, Ekaterina Levitskaya, Henry Chan +6
While smart city innovations seem to be a common and necessary response to increasing challenges of urbanization, foreseeing their impact on complex urban system is critical for in…
Operating advanced scientific instruments with AI agents that learn on the job
Aikaterini Vriza, Michael H. Prince, Tao Zhou +2
Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks…
Real-time 3D Nanoscale Coherent Imaging via Physics-aware Deep Learning
Henry Chan, Youssef S. G. Nashed, Saugat Kandel +4
Phase retrieval, the problem of recovering lost phase information from measured intensity alone, is an inverse problem that is widely faced in various imaging modalities ranging fr…
Opportunities for Retrieval and Tool Augmented Large Language Models in Scientific Facilities
Michael H. Prince, Henry Chan, Aikaterini Vriza +6
Upgrades to advanced scientific user facilities such as next-generation x-ray light sources, nanoscience centers, and neutron facilities are revolutionizing our understanding of ma…
A Continuous Action Space Tree search for INverse desiGn (CASTING) Framework for Materials Discovery
Suvo Banik, Troy Loefller, Sukriti Manna +5
Fast and accurate prediction of optimal crystal structure, topology, and microstructures is important for accelerating the design and discovery of new materials. A challenge lies i…
BLAST: Bridging Length/time scales via Atomistic Simulation Toolkit
Henry Chan, Badri Narayanan, Mathew Cherukara +4
The ever-increasing power of supercomputers coupled with highly scalable simulation codes have made molecular dynamics an indispensable tool in applications ranging from predictive…
AutoPhaseNN: Unsupervised Physics-aware Deep Learning of 3D Nanoscale Bragg Coherent Diffraction Imaging
Yudong Yao, Henry Chan, Subramanian Sankaranarayanan +3
The problem of phase retrieval, or the algorithmic recovery of lost phase information from measured intensity alone, underlies various imaging methods from astronomy to nanoscale i…
Adaptive AI decision interface for autonomous electronic material discovery
Yahao Dai, Henry Chan, Aikaterini Vriza +14
AI-powered autonomous experimentation (AI/AE) can accelerate materials discovery but its effectiveness for electronic materials is hindered by data scarcity from lengthy and comple…
Multicolor -Tilings with High Discrepancy
Henry Chan, Daniel Cheng, Lior Gishboliner +1
We study the minimum degree threshold guaranteeing the existence of -tilings of high discrepancy in any -edge-coloring. Balogh, Csaba, Pluhár and Treglown handl…
Machine Learning the Metastable Phase Diagram of Materials
Srilok Srinivasan, Rohit Batra, Duan Luo +8
Phase diagrams are an invaluable tool for material synthesis and provide information on the phases of the material at any given thermodynamic condition. Conventional phase diagram…
Screening of Therapeutic Agents for COVID-19 using Machine Learning and Ensemble Docking Simulations
Rohit Batra, Henry Chan, Ganesh Kamath +3
The world has witnessed unprecedented human and economic loss from the COVID-19 disease, caused by the novel coronavirus SARS-CoV-2. Extensive research is being conducted across th…