Area of research
Artificial Intelligence · Computational Mechanics
Research interest
Research interests include Sparse and Compressive Sensing Techniques, Statistical Methods and Inference, Advanced Clustering Algorithms Research, and Bayesian Methods and Mixture Models.
The number of tree species on Earth
Memristor-Based Multiplier and Squarer of Some Numbers of the form 10 l ± m
sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots
TRY plant trait database – enhanced coverage and open access
Robustness of trait connections across environmental gradients and growth forms
A Novel ALU Circuit based on Reversible Logic
Mapping local and global variability in plant trait distributions
III: Small: Stochastic Algorithms for Large Scale Data Analysis
Collaborative Research: Physics-Based Machine Learning for Sub-Seasonal Climate Forecasting
III: Small: Stochastic Algorithms for Large Scale Data Analysis
Collaborative Research: Physics-Based Machine Learning for Sub-Seasonal Climate Forecasting
PFI-TT: Advancing the Technology Readiness of Pylon Fairings for Tidal Turbines
Towards an improved understanding of tidal turbine dynamics in a turbulent marine environment
III: Medium: Collaborative Research: Bayesian Modeling and Inference for Quantifying Terrestrial Ecosystem Functions
CAREER: Transition to Turbulence and Mixing for Rayleigh Taylor Instability with Acceleration Reversal
RI: Small: Finding Patterns in Complex Data with Probablistic Graphical Models
BIGDATA: F: DKA: Collaborative Research: High-Dimensional Statistical Machine Learning for Spatio-Temporal Climate Data
EAGER: Collaborative Research: Learning Relations between Extreme Weather Events and Planet-Wide Environmental Trends
TWC: Medium: Collaborative: HIMALAYAS: Hierarchical Machine Learning Stack for Fine-Grained Analysis of Malware Domain Groups
Buoyancy Driven Turbulence Beyond Self-Similar Equilibrium
CAREER: Combinatorial Online Learning and its Applications
Buoyancy Driven Turbulence Beyond Self-Similar Equilibrium
RI: Small: Statistical Modeling of Dynamic Covariance Matrices
III-COR-Small: Multi-Relational Data Clustering with Probabilistic Mixture Models