Prof. Neeraja Yadwadkar — Research Profile
The University of Texas at Austin · Chandra Family Department of Electrical and Computer Engineering
Graduate application deadlines
Chandra Family Department of Electrical and Computer Engineering
PhD in Electrical and Computer Engineering
Fall 2027Application deadline
Dec 1, 2026
Source: ece.utexas.eduChecked Nov 2, 2026MSE in Electrical and Computer Engineering
Fall 2027Application deadline
Dec 1, 2026
Source: ece.utexas.eduChecked Nov 2, 2026
Considering this lab for grad school?
Save it to compare side by side with other labs. Jot a one-line note under each paper below — Application prep gathers your notes into an outline for your email to the PI and your statement of purpose. You do the writing; no AI.
What to prepare before emailing a PIAbout
Prof. Neeraja Yadwadkar at The University of Texas at Austin Chandra Family Department of Electrical and Computer Engineering lists Cloud Computing Systems, Machine Learning, Serverless Computing, Machine Learning for Systems, Systems for Machine Learning as their registered research area.
Research keywords
Recent papers
- DIMWIT: Directly Invoking Models Without Intensive TuningNewPreprintarXiv (Cornell University) · Nov 1
- Agar: What-If Analysis for Microservice ApplicationsNewPreprintarXiv (Cornell University) · Oct 27
- FlowMaker: From Tasks to Cost-Efficient Generative AI Workflow DeploymentsPreprintarXiv (Cornell University) · Oct 17
From OpenAlex · papers whose author affiliation matches this university
Labs doing related research
Labs that recently published on topics this lab's recent papers share
Yufei Ding Lab
University of California, San Diego · Department of Computer Science and Engineering
PLoRA: An NDP-Enhanced Pooled-Memory System for Cost-Efficient Multi-LoRA ServingPreprintarXiv (Cornell University) · Aug 6Shared topic: Parallel Computing and Optimization Techniques
Ion Stoica Lab
University of California, Berkeley · Electrical Engineering and Computer Sciences
Koi: Evidence-Guided, Self-Calibrating Planning for Multi-Cloud, Heterogeneous LLM Inference FleetsPreprintarXiv (Cornell University) · Oct 17Shared topic: Cloud Computing and Resource Management
Christos Kozyrakis Lab
Stanford University · Computer Science
ModelBlaster: Closing the Performance Gap through Learning-Augmented Agents Across Models, Kernels and Hardware BackendsNewPreprintarXiv (Cornell University) · Nov 3Shared topic: Parallel Computing and Optimization Techniques
Other labs in this department
- Power Electronics and Magnetics Lab
Alex J. Hanson
Component- and system-level power electronics, High-frequency magnetics and circuits
- Alex Q. Huang Lab
Power Semiconductor Devices, Advanced Power Electronics, Renewable Energy Integration and Smart Grid, Power Management Integrated Circuits
- Amy Zhang Lab
Reinforcement Learning, Generalization, Representation Learning, Robotics
- Ananth Dodabalapur Lab
Organic, inorganic, hybrid thin-film transistors and Circuits, 2D Materials Device Physics and Chemistry, Nanomanufacturing, Optoelectronic Devices, Chemical sensing and bioelectronics
- System-Level Architecture and Modeling (SLAM) Lab
Andreas Gerstlauer
Embedded system design, Embedded hardware and software synthesis
- Aryan Mokhtari Lab
Optimization, Machine Learning, Artificial Intelligence