GREEN: proactive queue management over a best-effort network. - Wu-chun Feng; Apu Kapadia; Sunil Thulasidasan (GLOBECOM, 2002)

Using Steady- State TCP Behavior for Proactive Queue Management. - Sunil Thulasidasan; Wu-chun Feng (International Conference on Internet Computing, 2002)

Optimizing GridFTP through Dynamic Right-Sizing. - Sunil Thulasidasan; Wu-chun Feng; Mark K. Gardner (HPDC, 2003)

User-space auto-tuning for TCP flow control in computational grids. - Mark K. Gardner; Sunil Thulasidasan; Wu-chun Feng (Comput. Commun., 2004)

Semantic Compression of TCP Traces. - Gabriel Istrate; Anders Hansson; Sunil Thulasidasan; Madhav V. Marathe; Christopher L. Barrett (Networking, 2006)

Designing systems for large-scale, discrete-event simulations: Experiences with the FastTrans parallel microsimulator. - Sunil Thulasidasan; Shiva Prasad Kasiviswanathan; Stephan J. Eidenbenz; Emanuele Galli; Susan M. Mniszewski; Philip Romero (HiPC, 2009)

Large-scale telephone network simulation: discrete event vs. steady state. - Russell Bent; Stephan J. Eidenbenz; Sunil Thulasidasan (SpringSim, 2009)

Accelerating Traffic Microsimulations: A Parallel Discrete-event Queue-based Approach for Speed and Scale. - Sunil Thulasidasan; Stephan J. Eidenbenz (WSC, 2009)

Explicit Spatial Scattering for Load Balancing in Conservatively Synchronized Parallel Discrete Event Simulations. - Sunil Thulasidasan; Shiva Prasad Kasiviswanathan; Stephan J. Eidenbenz; Philip Romero (PADS, 2010)

Criticality analysis of Internet infrastructure. - Guanhua Yan; Stephan J. Eidenbenz; Sunil Thulasidasan; Pallab Datta; Venkatesh Ramaswamy (Comput. Networks, 2010)

Heuristic acceleration of routing in transportation simulations using GPUs. - Sunil Thulasidasan (SimuTools, 2011)

SimCore: A Library for Rapid Development of Large Scale Parallel Simulations. - Sunil Thulasidasan; Lukas Kroc; Stephan J. Eidenbenz (SIMULTECH, 2012)

A comparative study of two models for celebrity identification on Twitter. - M. S. Srinivasan; Srinath Srinivasa; Sunil Thulasidasan (COMAD, 2014)

Efficient Multi-GPU Computation of All-Pairs Shortest Paths. - Hristo N. Djidjev; Sunil Thulasidasan; Guillaume Chapuis; Rumen Andonov; Dominique Lavenier (IPDPS, 2014)

Developing parallel, discrete event simulations in Python - first results and user experiences with the SimX library. - Sunil Thulasidasan; Lukas Kroc; Stephan J. Eidenbenz (SIMULTECH, 2014)

All-Pairs Shortest Path algorithms for planar graph for GPU-accelerated clusters. - Hristo N. Djidjev; Guillaume Chapuis; Rumen Andonov; Sunil Thulasidasan; Dominique Lavenier (J. Parallel Distributed Comput., 2015)

A study of the structure and vulnerabilities of metropolitan area networks. - Jiangzhuo Chen; V. S. Anil Kumar 001; Madhav V. Marathe; Ravi Sundaram; Mayur Thakur; Sunil Thulasidasan (COMSNETS, 2016)

A weakly supervised activity recognition framework for real-time synthetic biology laboratory assistance. - Chandrashekhar Lavania; Sunil Thulasidasan; Anthony LaMarca; Jeffrey Scofield; Jeff A. Bilmes (UbiComp, 2016)

Semi-Supervised Phone Classification using Deep Neural Networks and Stochastic Graph-Based Entropic Regularization. - Sunil Thulasidasan; Jeffrey A. Bilmes (CoRR, 2016)

Efficient Distributed Semi-Supervised Learning using Stochastic Regularization over Affinity Graphs. - Sunil Thulasidasan; Jeffrey A. Bilmes; Garrett T. Kenyon (CoRR, 2016)

Discrete event performance prediction of speculatively parallel temperature-accelerated dynamics. - Richard J. Zamora; Arthur F. Voter; Danny Perez; Nandakishore Santhi; Susan M. Mniszewski; Sunil Thulasidasan; Stephan J. Eidenbenz (Simul., 2016)

AMM: Scalable Memory Reuse Model to Predict the Performance of Physics Codes. - Gopinath Chennupati; Nandakishore Santhi; Stephan J. Eidenbenz; Sunil Thulasidasan (CLUSTER, 2017)

Acoustic classification using semi-supervised Deep Neural Networks and stochastic entropy-regularization over nearest-neighbor graphs. - Sunil Thulasidasan; Jeffrey A. Bilmes (ICASSP, 2017)

A Scalable Analytical Memory Model for CPU Performance Prediction. - Gopinath Chennupati; Nandakishore Santhi; Robert F. Bird; Sunil Thulasidasan; Abdel-Hameed A. Badawy; Satyajayant Misra; Stephan J. Eidenbenz (PMBS@SC, 2017)

An analytical memory hierarchy model for performance prediction. - Gopinath Chennupati; Nandakishore Santhi; Stephan J. Eidenbenz; Sunil Thulasidasan (WSC, 2017)

Combating Label Noise in Deep Learning using Abstention. - Sunil Thulasidasan; Tanmoy Bhattacharya 001; Jeff A. Bilmes; Gopinath Chennupati; Jamal Mohd-Yusof (ICML, 2019)

On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks. - Sunil Thulasidasan; Gopinath Chennupati; Jeff A. Bilmes; Tanmoy Bhattacharya 001; Sarah Michalak (NeurIPS, 2019)

Why I'm not Answering: Understanding Determinants of Classification of an Abstaining Classifier for Cancer Pathology Reports. - Sayera Dhaubhadel; Jamaludin Mohd-Yusof; Kumkum Ganguly; Gopinath Chennupati; Sunil Thulasidasan; Nicolas W. Hengartner; Brent J. Mumphrey; Eric B. Durbin; Jennifer A. Doherty; Mireille Lemieux; Noah Schaefferkoetter; Georgia D. Tourassi; et al. (CoRR, 2020)

Autonomous Control of a Particle Accelerator using Deep Reinforcement Learning. - Xiaoying Pang; Sunil Thulasidasan; Larry Rybarcyk (CoRR, 2020)

An Effective Baseline for Robustness to Distributional Shift. - Sunil Thulasidasan; Sushil Thapa; Sayera Dhaubhadel; Gopinath Chennupati; Tanmoy Bhattacharya 001; Jeff A. Bilmes (ICMLA, 2021)

Smart Camera Traps: Enabling Energy-Efficient Edge-AI for Remote Monitoring of Wildlife. - Dhruv Tulasi; Alys Granados; Prabath Gunawardane; Abhay Kashyap; Zara McDonald; Sunil Thulasidasan (GeoWildLife@SIGSPATIAL, 2023)