Ajitesh Srivastava

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 76

Top Topics

Top Venues

Soc. Netw. Anal. Min.

Publications

Alexander Rodríguez, Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Marie-Laure Charpignon, Kai Wang, Serina Chang, Anil Vullikanti, B. Aditya Prakash
epiDAMIK 2024: The 7th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. KDD (2024)
Ajitesh Srivastava, Juan Marcos Ramirez, Sergio Díaz-Aranda, José Aguilar, Antonio Fernández Anta, Antonio Ortega, Rosa Elvira Lillo
Nowcasting Temporal Trends Using Indirect Surveys. AAAI (2024)
Majd Al Aawar, Srikar Mutnuri, Mansooreh Montazerin, Ajitesh Srivastava
Global Prediction of COVID-19 Variant Emergence Using Dynamics-Informed Graph Neural Networks. CoRR (2024)
Zhengtao Yao, Hong Nguyen, Ajitesh Srivastava, Jose Luis Ambite
Task-Agnostic Federated Learning. CoRR (2024)
Bijaya Adhikari, Alexander Rodríguez, Amulya Yadav, Sen Pei, Ajitesh Srivastava, Marie-Laure Charpignon, Anil Vullikanti, B. Aditya Prakash
epiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. KDD (2023)
Sina Jahandari, Ajitesh Srivastava
Detection of Delays and Feedthroughs in Dynamic Networked Systems. IEEE Control. Syst. Lett. 7 (2023)
Yue Niu, Rajgopal Kannan, Ajitesh Srivastava, Viktor K. Prasanna
Reuse Kernels or Activations? A Flexible Dataflow for Low-latency Spectral CNN Acceleration. CoRR (2023)
James Orme-Rogers, Ajitesh Srivastava
Spatio-Temporal Attention in Multi-Granular Brain Chronnectomes For Detection of Autism Spectrum Disorder. ICASSP (2023)
Ajitesh Srivastava, Juan Marcos Ramirez, Sergio Diaz, Jose Aguilar, Antonio Ortega, Antonio Fernández Anta, Rosa Lillo-Rodriguez
Estimating Temporal Trends using Indirect Surveys. CoRR (2023)
Sina Jahandari, Ajitesh Srivastava
Adjusting for Unmeasured Confounding Variables in Dynamic Networks. IEEE Control. Syst. Lett. 7 (2023)
Ajitesh Srivastava
DTW+S: Shape-based Comparison of Time-series with Ordered Local Trend. CoRR (2023)
Sarthak Kumar Maharana, Krishna Kamal Adidam, Shoumik Nandi, Ajitesh Srivastava
Acoustic-to-articulatory inversion for dysarthric speech: Are pre-trained self-supervised representations favorable? CoRR (2023)
Chung Ming Cheung, Sanmukh Rao Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Behind-the-Meter Solar Generation Disaggregation at Varying Aggregation Levels Using Consumer Mixture Models. IEEE Trans. Sustain. Comput. 8 (1) (2023)
Ajitesh Srivastava, Satwant Singh, Fiona Lee
Shape-based Evaluation of Epidemic Forecasts. Big Data (2022)
Pengmiao Zhang, Rajgopal Kannan, Ajitesh Srivastava, Anant V. Nori, Viktor K. Prasanna
ReSemble: Reinforced Ensemble Framework for Data Prefetching. SC (2022)
Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna
Fine-Grained Address Segmentation for Attention-Based Variable-Degree Prefetching. CoRR (2022)
Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware. CoRR (2022)
Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna
Fine-grained address segmentation for attention-based variable-degree prefetching. CF (2022)
Majd Al Aawar, Ajitesh Srivastava
Random Forest of Epidemiological Models for Influenza Forecasting. CoRR (2022)
Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen
Decoupling the Depth and Scope of Graph Neural Networks. CoRR (2022)
Bijaya Adhikari, Amulya Yadav, Sen Pei, Ajitesh Srivastava, Sarah Kefayati, Alexander Rodríguez, Marie-Laure Charpignon, Anil Vullikanti, B. Aditya Prakash
epiDAMIK 5.0: The 5th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. KDD (2022)
Pengmiao Zhang, Ajitesh Srivastava, Anant V. Nori, Rajgopal Kannan, Viktor K. Prasanna
TransforMAP: Transformer for Memory Access Prediction. CoRR (2022)
James Orme-Rogers, Ajitesh Srivastava
Spatio-Temporal Attention in Multi-Granular Brain Chronnectomes for Detection of Autism Spectrum Disorder. CoRR (2022)
Pengmiao Zhang, Ajitesh Srivastava, Ta-Yang Wang, César A. F. De Rose, Rajgopal Kannan, Viktor K. Prasanna
C-MemMAP: clustering-driven compact, adaptable, and generalizable meta-LSTM models for memory access prediction. Int. J. Data Sci. Anal. 13 (1) (2022)
Carson Gray, Trevor Webster, Brian Ozarowicz, Yuhang Chen, Timothy Bui, Ajitesh Srivastava, Naomi T. Fitter
"This Bot Knows What I'm Talking About!" Human-Inspired Laughter Classification Methods for Adaptive Robotic Comedians. RO-MAN (2022)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Accurate, efficient and scalable training of Graph Neural Networks. J. Parallel Distributed Comput. 147 (2021)
Ajitesh Srivastava, Tianjian Xu, Viktor K. Prasanna
The EpiBench Platform to Propel AI/ML-based Epidemic Forecasting: A Prototype Demonstration Reaching Human Expert-level Performance. CoRR (2021)
Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna
Accelerating Large Scale Real-Time GNN Inference using Channel Pruning. Proc. VLDB Endow. 14 (9) (2021)
Hongkuan Zhou, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, Viktor K. Prasanna
Accelerating Large Scale Real-Time GNN Inference using Channel Pruning. CoRR (2021)
Ajitesh Srivastava, Naomi T. Fitter
A Robot Walks into a Bar: Automatic Robot Joke Success Assessment. ICRA (2021)
Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Sarah Kefayati, Rose Yu, Amulya Yadav, Alexander Rodríguez, Arvind Ramanathan, Anil Vullikanti, B. Aditya Prakash
The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021). KDD (2021)
Ta-Yang Wang, William Chang, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Monte Carlo Tree Search for Task Mapping onto Heterogeneous Platforms. HiPC (2021)
Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Andrey Malevich, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Ren Chen
Decoupling the Depth and Scope of Graph Neural Networks. NeurIPS (2021)
Naifeng Zhang, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
GenMAT: A General-Purpose Machine Learning-Driven Auto-Tuner for Heterogeneous Platforms. PEHC@SC (2021)
Yuan Meng, Sanmukh R. Kuppannagari, Rachit Rajat, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators. IPDPS Workshops (2020)
Yang Yang, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
FASTHash: FPGA-Based High Throughput Parallel Hash Table. ISC (2020)
Ajitesh Srivastava, Naifeng Zhang, Rajgopal Kannan, Viktor K. Prasanna
Towards High Performance, Portability, and Productivity: Lightweight Augmented Neural Networks for Performance Prediction. CoRR (2020)
Ta-Yang Wang, Ajitesh Srivastava, Viktor K. Prasanna
A Framework for Task Mapping onto Heterogeneous Platforms. HPEC (2020)
Yue Niu, Rajgopal Kannan, Ajitesh Srivastava, Viktor K. Prasanna
Reuse Kernels or Activations?: A Flexible Dataflow for Low-latency Spectral CNN Acceleration. FPGA (2020)
Rachit Rajat, Yuan Meng, Sanmukh R. Kuppannagari, Ajitesh Srivastava, Viktor K. Prasanna, Rajgopal Kannan
QTAccel: A Generic FPGA based Design for Q-Table based Reinforcement Learning Accelerators. FPGA (2020)
Ajitesh Srivastava, Viktor K. Prasanna
Data-driven Identification of Number of Unreported Cases for COVID-19: Bounds and Limitations. CoRR (2020)
Connor Imes, Alexei Colin, Naifeng Zhang, Ajitesh Srivastava, Viktor K. Prasanna, John Paul Walters
Compiler Abstractions and Runtime for Extreme-scale SAR and CFD Workloads. ESPM2@SC (2020)
Hanqing Zeng, Muhan Zhang, Yinglong Xia, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna, Long Jin, Andrey Malevich, Ren Chen
Deep Graph Neural Networks with Shallow Subgraph Samplers. CoRR (2020)
Ajitesh Srivastava, Tianjian Xu, Viktor K. Prasanna
Fast and Accurate Forecasting of COVID-19 Deaths Using the SIkJα Model. CoRR (2020)
Ajitesh Srivastava, Ta-Yang Wang, Pengmiao Zhang, César Augusto Fonticielha De Rose, Rajgopal Kannan, Viktor K. Prasanna
MemMAP: Compact and Generalizable Meta-LSTM Models for Memory Access Prediction. PAKDD (2) (2020)
Pengmiao Zhang, Ajitesh Srivastava, Benjamin Brooks, Rajgopal Kannan, Viktor K. Prasanna
RAOP: Recurrent Neural Network Augmented Offset Prefetcher. MEMSYS (2020)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
GraphSAINT: Graph Sampling Based Inductive Learning Method. ICLR (2020)
Ajitesh Srivastava, Viktor K. Prasanna
Learning to Forecast and Forecasting to Learn from the COVID-19 Pandemic. CoRR (2020)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Accurate, Efficient and Scalable Training of Graph Neural Networks. CoRR (2020)
Ajitesh Srivastava, Naifeng Zhang, Rajgopal Kannan, Viktor K. Prasanna
Towards High Performance, Portability, and Productivity: Lightweight Augmented Neural Networks for Performance Prediction. HiPC (2020)
Max Noormohammadpour, Ajitesh Srivastava, Cauligi S. Raghavendra
Optimizing Inter-Datacenter Tail Flow Completion Times using Best Worst-case Routing. Allerton (2019)
Chuanxiu Xiong, Ajitesh Srivastava, Rajgopal Kannan, Omkar Damle, Viktor K. Prasanna, Erroll Southers
On Predicting Crime with Heterogeneous Spatial Patterns: Methods and Evaluation. SIGSPATIAL/GIS (2019)
Yue Niu, Hanqing Zeng, Ajitesh Srivastava, Kartik Lakhotia, Rajgopal Kannan, Yanzhi Wang, Viktor K. Prasanna
SPEC2: SPECtral SParsE CNN Accelerator on FPGAs. HiPC (2019)
Ajitesh Srivastava, Robin Petering, Nicholas Barr, Rajgopal Kannan, Eric Rice, Viktor K. Prasanna
Network-based intervention strategies to reduce violence among homeless. Soc. Netw. Anal. Min. 9 (1) (2019)
Ajitesh Srivastava, Angelos Lazaris, Benjamin Brooks, Rajgopal Kannan, Viktor K. Prasanna
Predicting memory accesses: the road to compact ML-driven prefetcher. MEMSYS (2019)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Accurate, Efficient and Scalable Graph Embedding. IPDPS (2019)
Ajitesh Srivastava, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna
RecANt: Network-based Recruitment for Active Fake News Correction. IEEE BigData (2019)
Yue Niu, Hanqing Zeng, Ajitesh Srivastava, Kartik Lakhotia, Rajgopal Kannan, Yanzhi Wang, Viktor K. Prasanna
SPEC2: SPECtral SParsE CNN Accelerator on FPGAs. CoRR (2019)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
GraphSAINT: Graph Sampling Based Inductive Learning Method. CoRR (2019)
Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware. HPEC (2019)
Kartik Lakhotia, Rajgopal Kannan, Aditya Gaur, Ajitesh Srivastava, Viktor K. Prasanna
Parallel edge-based sampling for static and dynamic graphs. CF (2019)
Max Noormohammadpour, Ajitesh Srivastava, Cauligi S. Raghavendra
Optimizing Inter-Datacenter Tail Flow Completion Times using Best Worst-case Routing. CoRR (2019)
Akshit Goel, Sanmukh R. Kuppannagari, Yang Yang, Ajitesh Srivastava, Viktor K. Prasanna
Parallel Totally Induced Edge Sampling on FPGAs. PARCO (2019)
Mohammad Noormohammadpour, Ajitesh Srivastava, Cauligi S. Raghavendra
On Minimizing the Completion Times of Long Flows Over Inter-Datacenter WAN. IEEE Commun. Lett. 22 (12) (2018)
Ajitesh Srivastava, Rajgopal Kannan, Charalampos Chelmis, Viktor K. Prasanna
FActCheck: Keeping Activation of Fake News at Check. AAMAS (2018)
Ajitesh Srivastava, Robin Petering, Rajgopal Kannan, Eric Rice, Viktor K. Prasanna
How to Stop Violence Among Homeless: Extension of Voter Model and Intervention Strategies. ASONAM (2018)
Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Accurate, Efficient and Scalable Graph Embedding. CoRR (2018)
Chung Ming Cheung, Wen Zhong, Chuanxiu Xiong, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Behind-the-Meter Solar Generation Disaggregation using Consumer Mixture Models. SmartGridComm (2018)
Mohammad Noormohammadpour, Ajitesh Srivastava, Cauligi S. Raghavendra
On Minimizing the Completion Times of Long Flows over Inter-Datacenter WAN. CoRR (2018)
Michail Misyrlis, Chung Ming Cheung, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
Spatio-Temporal Modeling of Criminal Activity. SocialSens@CPSWeek (2017)
Shreyas G. Singapura, Ajitesh Srivastava, Rajgopal Kannan, Viktor K. Prasanna
OSCAR: Optimizing SCrAtchpad reuse for graph processing. HPEC (2017)
Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna
Mining Large Dense Subgraphs. WWW (Companion Volume) (2016)
Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna
Computing competing cascades on signed networks. Soc. Netw. Anal. Min. 6 (1) (2016)
Ajitesh Srivastava, Ren Chen, Viktor K. Prasanna, Charalampos Chelmis
A hybrid design for high performance large-scale sorting on FPGA. ReConFig (2015)
Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna
Social Influence Computation and Maximization in Signed Networks with Competing Cascades. ASONAM (2015)
Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna
The unified model of social influence and its application in influence maximization. Soc. Netw. Anal. Min. 5 (1) (2015)
Ajitesh Srivastava, Charalampos Chelmis, Viktor K. Prasanna
Influence in social networks: A unified model? ASONAM (2014)
Charalampos Chelmis, Ajitesh Srivastava, Viktor K. Prasanna
Computational models of technology adoption at the workplace. Soc. Netw. Anal. Min. 4 (1) (2014)
Ajitesh Srivastava, Axel J. Soto, Evangelos E. Milios
Text clustering using one-mode projection of document-word bipartite graphs. SAC (2013)
Ajitesh Srivastava, Axel J. Soto, Evangelos E. Milios
A graph-based topic extraction method enabling simple interactive customization. ACM Symposium on Document Engineering (2013)
Saptarshi Ghosh, Sudipta Saha, Ajitesh Srivastava, Tyll Krueger, Niloy Ganguly, Animesh Mukherjee
Understanding Evolution of Inter-Group Relationships Using Bipartite Networks. IEEE J. Sel. Areas Commun. 31 (9-Supplement) (2013)
Saptarshi Ghosh, Ajitesh Srivastava, Niloy Ganguly
Effects of a soft cut-off on node-degree in the Twitter social network. Comput. Commun. 35 (7) (2012)
Niloy Ganguly, Saptarshi Ghosh, Tyll Krueger, Ajitesh Srivastava
Degree distributions of evolving alphabetic bipartite networks and their projections. Theor. Comput. Sci. 466 (2012)
Saptarshi Ghosh, Ajitesh Srivastava, Niloy Ganguly
Assessing the Effects of a Soft Cut-Off in the Twitter Social Network. Networking (2) (2011)