Meet ApplyKite Twin, the application assistant that learns with you

Meet your Twin, it learns with you

Your Twin learns with you

Launch week codes:30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Prasanna Balaprakash

Director of AI Programs and Distinguished R&D Scientist

Oak Ridge National Laboratory

United States

Research Interests

Explore related searches

Professors in United States Professors in Artificial Intelligence Artificial Intelligence professors in United States

Articles (18)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Collaborators (6)

Ewa Deelman

Principal Investigator

University of Southern California

UNITED STATES

View details

Jeffrey Vetter

Corporate Fellow, Section Head

Oak Ridge National Laboratory

UNITED STATES

View details

Abhinav Bhatele

University of Maryland

UNITED STATES

View details

Phiala Shanahan

Professor of Physics

Massachusetts Institute of Technology

UNITED STATES

View details

Jaehoon Koo

Assistant Professor

Hanyang University - Ansan Campus

SOUTH KOREA

View details

Rafael Ferreira da Silva

Group Leader / Senior Research Scientist

Oak Ridge National Laboratory

UNITED STATES

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Prasanna Balaprakash

Research Interests

Explore related searches

Articles (18)

Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions

Matrix-free Neural Preconditioner for the Dirac Operator in Lattice Gauge Theory

Scalable Federated Learning for Scientific Foundation Models on Leadership-Class Systems

Ecosystems for Scientific Computing in the Age of Artificial Intelligence

Comparing Llama-2 and GPT-3 LLMs for HPC Kernels Generation

Bridging Speed and Optimality in Job Scheduling: A Hybrid Ant Colony Optimization Approach for Distributed Systems

Evaluating the Efficacy of LLM-Based Reasoning for Multiobjective HPC Job Scheduling

Distributed Cross-Channel Hierarchical Aggregation for Foundation Models

LLM Agents for Interactive Workflow Provenance: Reference Architecture and Evaluation Methodology

The (R)evolution of Scientific Workflows in the Agentic AI Era: Towards Autonomous Science

DeepHyper: A Python Package for Massively Parallel Hyperparameter Optimization in Machine Learning

EFIT-Prime: Probabilistic and physics-constrained reduced-order neural network model for equilibrium reconstruction in DIII-D

Streamlining Ocean Dynamics Modeling with Fourier Neural Operators: A Multiobjective Hyperparameter and Architecture Optimization Approach

Uncertainty Quantification for Traffic Forecasting Using Deep-Ensemble-Based Spatiotemporal Graph Neural Networks

Learning Symbolic Expressions: Mixed-Integer Formulations, Cuts, and Heuristics

Evaluation of OpenAI Codex for HPC Parallel Programming Models Kernel Generation

Code and Data Repository for Learning Symbolic Expressions: Mixed-Integer Formulations, Cuts, and Heuristics

Transfer-learning-based Autotuning using Gaussian Copula

Collaborators (6)

Ewa Deelman

Jeffrey Vetter

Abhinav Bhatele

Phiala Shanahan

Jaehoon Koo

Rafael Ferreira da Silva

Make your next move.