Dhireesha Kudithipudi

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 77

Top Venues

CoRR

ISCAS

IJCNN

ACM J. Emerg. Technol. Comput. Syst.

Publications

Vedant Karia, Abdullah M. Zyarah, Dhireesha Kudithipudi
PositCL: Compact Continual Learning with Posit Aware Quantization. ACM Great Lakes Symposium on VLSI (2024)
Fatima Tuz Zohora, Vedant Karia, Nicholas Soures, Dhireesha Kudithipudi
Probabilistic Metaplasticity for Continual Learning with Memristors. CoRR (2024)
Gido M. van de Ven, Nicholas Soures, Dhireesha Kudithipudi
Continual Learning and Catastrophic Forgetting. CoRR (2024)
Eli Verwimp, Rahaf Aljundi, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven
Continual Learning: Applications and the Road Forward. Trans. Mach. Learn. Res. 2024 (2024)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Time-Series Forecasting and Sequence Learning Using Memristor-based Reservoir System. CoRR (2024)
Truman Hickok, Dhireesha Kudithipudi
Watch Your Step: Optimal Retrieval for Continual Learning at Scale. CoRR (2024)
Nicholas Soures, Vedant Karia, Dhireesha Kudithipudi
Advancing Neuro-Inspired Lifelong Learning for Edge with Co-Design. AAAI Spring Symposia (2024)
Eli Verwimp, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M. van de Ven
Continual Learning: Applications and the Road Forward. CoRR (2023)
Peter Helfer, Corinne Teeter, Aaron J. Hill, Craig M. Vineyard, James B. Aimone, Dhireesha Kudithipudi
Context Modulation Enables Multi-tasking and Resource Efficiency in Liquid State Machines. ICONS (2023)
Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Dimitri Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael L. Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems. CoRR (2023)
Dhireesha Kudithipudi, Anurag Reddy Daram, Abdullah M. Zyarah, Fatima Tuz Zohora, James B. Aimone, Angel Yanguas-Gil, Nicholas Soures, Emre Neftci, Matthew Mattina, Vincenzo Lomonaco, Clare D. Thiem, Benjamin R. Epstein
Design Principles for Lifelong Learning AI Accelerators. CoRR (2023)
Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael L. Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha
A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks 160 (2023)
Anurag Reddy Daram, Dhireesha Kudithipudi
NEO: Neuron State Dependent Mechanisms for Efficient Continual Learning. NICE (2023)
Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander M. Bohté, Younes Bouhadjar, Sonia M. Buckley, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Reddy Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve B. Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos P. Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayça Özcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Pao-Sheng Sun, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine D. Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. CoRR (2023)
Vedant Karia, Fatima Tuz Zohora, Nicholas Soures, Dhireesha Kudithipudi
SCOLAR: A Spiking Digital Accelerator with Dual Fixed Point for Continual Learning. ISCAS (2022)
Hamed Fatemi Langroudi, Vedant Karia, Tej Pandit, Becky Mashaido, Dhireesha Kudithipudi
ACTION: Automated Hardware-Software Codesign Framework for Low-precision Numerical Format SelecTION in TinyML. CoNGA (2022)
Dhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb, Maxim Bazhenov, Douglas Blackiston, Josh C. Bongard, Andrew P. Brna, Suraj Chakravarthi Raja, Nick Cheney, Jeff Clune, Anurag Reddy Daram, Stefano Fusi, Peter Helfer, Leslie Kay, Nicholas Ketz, Zsolt Kira, Soheil Kolouri, Jeffrey L. Krichmar, Sam Kriegman, Michael Levin, Sandeep Madireddy, Santosh Manicka, Ali Marjaninejad, Bruce McNaughton, Risto Miikkulainen, Zaneta Navratilova, Tej Pandit, Alice Parker, Praveen K. Pilly, Sebastian Risi, Terrence J. Sejnowski, Andrea Soltoggio, Nicholas Soures, Andreas S. Tolias, Darío Urbina-Meléndez, Francisco J. Valero Cuevas, Gido M. van de Ven, Joshua T. Vogelstein, Felix Wang, Ron Weiss, Angel Yanguas-Gil, Xinyun Zou, Hava T. Siegelmann
Biological underpinnings for lifelong learning machines. Nat. Mach. Intell. 4 (3) (2022)
Tej Pandit, Dhireesha Kudithipudi
Low-Shot Learning and Pattern Separation using Cellular Automata Integrated CNNs. ICONS (2022)
Fatima Tuz Zohora, Vedant Karia, Anurag Reddy Daram, Abdullah M. Zyarah, Dhireesha Kudithipudi
MetaplasticNet: Architecture with Probabilistic Metaplastic Synapses for Continual Learning. ISCAS (2021)
Humza Syed, Ryan Bryla, Uttam K. Majumder, Dhireesha Kudithipudi
Toward Near-Real-Time Training With Semi-Random Deep Neural Networks and Tensor-Train Decomposition. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14 (2021)
Hamed Fatemi Langroudi, Vedant Karia, Tej Pandit, Dhireesha Kudithipudi
TENT: Efficient Quantization of Neural Networks on the tiny Edge with Tapered FixEd PoiNT. CoRR (2021)
Hamed Fatemi Langroudi, Vedant Karia, Zachariah Carmichael, Abdullah M. Zyarah, Tej Pandit, John L. Gustafson, Dhireesha Kudithipudi
ALPS: Adaptive Quantization of Deep Neural Networks With GeneraLized PositS. CVPR Workshops (2021)
Tej Pandit, Dhireesha Kudithipudi
Relational Neurogenesis for Lifelong Learning Agents. NICE (2020)
Sumin Jot, Abdullah M. Zyarah, Santosh Kurinec, Kai Ni, Fatima Tuz Zohora, Dhireesha Kudithipudi
FeFET-Based Neuromorphic Architecture with On-Device Feedback Alignment Training. ISQED (2020)
Fatima Tuz Zohora, Abdullah M. Zyarah, Nicholas Soures, Dhireesha Kudithipudi
Metaplasticity in Multistate Memristor Synaptic Networks. CoRR (2020)
Hamed Fatemi Langroudi, Vedant Karia, John L. Gustafson, Dhireesha Kudithipudi
Adaptive Posit: Parameter aware numerical format for deep learning inference on the edge. CVPR Workshops (2020)
Fatima Tuz Zohora, Abdullah M. Zyarah, Nicholas Soures, Dhireesha Kudithipudi
Metaplasticity in Multistate Memristor Synaptic Networks. ISCAS (2020)
Abdullah M. Zyarah, Kevin Gomez, Dhireesha Kudithipudi
Neuromorphic System for Spatial and Temporal Information Processing. IEEE Trans. Computers 69 (8) (2020)
Abdullah M. Zyarah, Kevin Gomez, Dhireesha Kudithipudi
End-to-End Memristive HTM System for Pattern Recognition and Sequence Prediction. CoRR (2020)
Hamed Fatemi Langroudi, Zachariah Carmichael, David Pastuch, Dhireesha Kudithipudi
Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge. CoRR (2019)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Neuromorphic Architecture for the Hierarchical Temporal Memory. IEEE Trans. Emerg. Top. Comput. Intell. 3 (1) (2019)
Zachariah Carmichael, Humza Syed, Dhireesha Kudithipudi
Analysis of Wide and Deep Echo State Networks for Multiscale Spatiotemporal Time Series Forecasting. CoRR (2019)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Neuromemristive Multi-Layer Random Projection Network with On-Device Learning. IJCNN (2019)
Nicholas Soures, Dhireesha Kudithipudi
Spiking Reservoir Networks: Brain-inspired recurrent algorithms that use random, fixed synaptic strengths. IEEE Signal Process. Mag. 36 (6) (2019)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis. ACM J. Emerg. Technol. Comput. Syst. 15 (3) (2019)
Zachariah Carmichael, Dhireesha Kudithipudi
Stochastic Tucker-Decomposed Recurrent Neural Networks for Forecasting. GlobalSIP (2019)
Guang-Bin Huang, E. S. Eleftheriou, Dhireesha Kudithipudi, Jonathan Tapson, H. Yu
Guest Editorial: Special Issue on New Trends in Smart Chips and Smart Hardware. IEEE Trans. Emerg. Top. Comput. Intell. 3 (1) (2019)
Zachariah Carmichael, Hamed Fatemi Langroudi, Char Khazanov, Jeffrey Lillie, John L. Gustafson, Dhireesha Kudithipudi
Deep Positron: A Deep Neural Network Using the Posit Number System. DATE (2019)
Hamed Fatemi Langroudi, Zachariah Carmichael, Dhireesha Kudithipudi
Deep Learning Training on the Edge with Low-Precision Posits. CoRR (2019)
Anurag Reddy Daram, Dhireesha Kudithipudi, Angel Yanguas-Gil
Task-Based Neuromodulation Architecture for Lifelong Learning. ISQED (2019)
Hamed Fatemi Langroudi, Cory E. Merkel, Humza Syed, Dhireesha Kudithipudi
Exploiting Randomness in Deep Learning Algorithms. IJCNN (2019)
Zachariah Carmichael, Hamed Fatemi Langroudi, Char Khazanov, Jeffrey Lillie, John L. Gustafson, Dhireesha Kudithipudi
Performance-Efficiency Trade-off of Low-Precision Numerical Formats in Deep Neural Networks. CoRR (2019)
Zachariah Carmichael, Seyed Hamed Fatemi Langroudi, Char Khazanov, Jeffrey Lillie, John L. Gustafson, Dhireesha Kudithipudi
Deep Positron: A Deep Neural Network Using the Posit Number System. CoRR (2018)
Qiuyi Wu, Ernest Fokoué, Dhireesha Kudithipudi
On the Statistical Challenges of Echo State Networks and Some Potential Remedies. CoRR (2018)
James Thesing, Dhireesha Kudithipudi
Secure Neural Circuits to Mitigate Correlation Power Analysis on SHA-3 Hash Function. VLSI Design (2018)
Seyed Hamed Fatemi Langroudi, Tej Pandit, Dhireesha Kudithipudi
Deep Learning Inference on Embedded Devices: Fixed-Point vs Posit. CoRR (2018)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Neuromorphic Architecture for the Hierarchical Temporal Memory. CoRR (2018)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Neuromemrisitive Architecture of HTM with On-Device Learning and Neurogenesis. CoRR (2018)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Learning Accelerator. ACM J. Emerg. Technol. Comput. Syst. 14 (4) (2018)
Yang Cindy Yi, Dhireesha Kudithipudi
Neuromorphic and cognitive computing and communication in hardware. Nano Commun. Networks 16 (2018)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Semi-Trained Memristive Crossbar Computing Engine with In-Situ Learning Accelerator. CoRR (2018)
Seyed Hamed Fatemi Langroudi, Tej Pandit, Dhireesha Kudithipudi
Deep Learning Inference on Embedded Devices: Fixed-Point vs Posit. EMC2@ASPLOS (2018)
Zachariah Carmichael, Humza Syed, Stuart Burtner, Dhireesha Kudithipudi
Mod-DeepESN: Modular Deep Echo State Network. CoRR (2018)
Anurag Reddy Daram, Karan Paluru, Vedant Karia, Dhireesha Kudithipudi
Scalable IP Core for Feed Forward Random Networks. ELM (2018)
Abdullah M. Zyarah, Nicholas Soures, Dhireesha Kudithipudi
On-Device Learning in Memristor Spiking Neural Networks. ISCAS (2018)
Nicholas Soures, Lydia Hays, Dhireesha Kudithipudi
Robustness of a memristor based liquid state machine. IJCNN (2017)
Nicholas Soures, Lydia Hays, Eric Bohannon, Abdullah M. Zyarah, Dhireesha Kudithipudi
On-device STDP and synaptic normalization for neuromemristive spiking neural network. MWSCAS (2017)
Ernest Fokoué, Lakshmi Ravi, Dhireesha Kudithipudi
A penalized maximum likelihood approach to the adaptive learning of the spatial pooler permanence. IJCNN (2017)
Haibo He, Robert Haas, Jun Fu, Barbara Hammer, Daniel W. C. Ho, Fakhri Karray, Dhireesha Kudithipudi, José Antonio Lozano, Teresa Bernarda Ludermir, Jacek Mandziuk, Stefano Melacci, Antonio Paiva, Hong Qiao, Alain Rakotomamonjy, Shiliang Sun, Johan A. K. Suykens, Meng Wang
Editorial: A Successful Year and Looking Forward to 2017 and Beyond. IEEE Trans. Neural Networks Learn. Syst. 28 (1) (2017)
Swathika Ramakrishnan, Dhireesha Kudithipudi
On accelerating stochastic neural networks. NANOCOM (2017)
Cory E. Merkel, Dhireesha Kudithipudi, Manan Suri, Bryant T. Wysocki
Stochastic CBRAM-Based Neuromorphic Time Series Prediction System. ACM J. Emerg. Technol. Comput. Syst. 13 (3) (2017)
Nicholas Soures, Corey Merkel, Dhireesha Kudithipudi, Clare Thiem, Nathan R. McDonald
Reservoir Computing in Embedded Systems: Three variants of the reservoir algorithm. IEEE Consumer Electron. Mag. 6 (3) (2017)
Dillon Graham, Seyed Hamed Fatemi Langroudi, Christopher Kanan, Dhireesha Kudithipudi
Convolutional Drift Networks for Video Classification. ICRC (2017)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Invited paper: Resource sharing in feed forward neural networks for energy efficiency. MWSCAS (2017)
Alex Pappachen James, Irina Fedorova, Timur Ibrayev, Dhireesha Kudithipudi
HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition. IEEE Trans. Biomed. Circuits Syst. 11 (3) (2017)
Abdullah M. Zyarah, Nicholas Soures, Lydia Hays, Robin Jacobs-Gedrim, Sapan Agarwal, Matthew J. Marinella, Dhireesha Kudithipudi
Ziksa: On-chip learning accelerator with memristor crossbars for multilevel neural networks. ISCAS (2017)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Extreme learning machine as a generalizable classification engine. IJCNN (2017)
Dillon Graham, Seyed Hamed Fatemi Langroudi, Christopher Kanan, Dhireesha Kudithipudi
Convolutional Drift Networks for Video Classification. CoRR (2017)
Anvesh Polepalli, Nicholas Soures, Dhireesha Kudithipudi
Digital neuromorphic design of a Liquid State Machine for real-time processing. ICRC (2016)
Timur Ibrayev, Alex Pappachen James, Cory E. Merkel, Dhireesha Kudithipudi
A design of HTM spatial pooler for face recognition using memristor-CMOS hybrid circuits. ISCAS (2016)
Dan Christiani, Cory E. Merkel, Dhireesha Kudithipudi
Invited: Towards a scalable neuromorphic hardware for classification and prediction with stochastic No-Prop algorithms. ISQED (2016)
Anvesh Polepalli, Dhireesha Kudithipudi
Reconfigurable Digital Design of a Liquid State Machine for Spatio-Temporal Data. NANOCOM (2016)
Cory E. Merkel, Raqibul Hasan, Nicholas Soures, Dhireesha Kudithipudi, Tarek M. Taha, Sapan Agarwal, Matthew J. Marinella
Neuromemristive Systems: Boosting Efficiency through Brain-Inspired Computing. Computer 49 (10) (2016)
Cory E. Merkel, Dhireesha Kudithipudi
Unsupervised Learning in Neuromemristive Systems. CoRR (2016)
James Mnatzaganian, Ernest Fokoué, Dhireesha Kudithipudi
A Mathematical Formalization of Hierarchical Temporal Memory's Spatial Pooler. Frontiers Robotics AI 3 (2016)
James Mnatzaganian, Ernest Fokoué, Dhireesha Kudithipudi
A Mathematical Formalization of Hierarchical Temporal Memory Cortical Learning Algorithm's Spatial Pooler. CoRR (2016)
Lennard Streat, Dhireesha Kudithipudi, Kevin Gomez
Non-volatile Hierarchical Temporal Memory: Hardware for Spatial Pooling. CoRR (2016)
Cory E. Merkel, Dhireesha Kudithipudi
Comparison of Off-Chip Training Methods for Neuromemristive Systems. VLSI Design (2015)
Abdullah M. Zyarah, Dhireesha Kudithipudi
Reconfigurable hardware architecture of the spatial pooler for hierarchical temporal memory. SoCC (2015)
Qutaiba Saleh, Cory E. Merkel, Dhireesha Kudithipudi, Bryant T. Wysocki
Memristive computational architecture of an echo state network for real-time speech-emotion recognition. CISDA (2015)
Colin Donahue, Cory E. Merkel, Qutaiba Saleh, Levs Dolgovs, Yu Kee Ooi, Dhireesha Kudithipudi, Bryant T. Wysocki
Design and analysis of neuromemristive echo state networks with limited-precision synapses. CISDA (2015)
Cory E. Merkel, Dhireesha Kudithipudi
A current-mode CMOS/memristor hybrid implementation of an extreme learning machine. ACM Great Lakes Symposium on VLSI (2014)
Cory E. Merkel, Dhireesha Kudithipudi
A stochastic learning algorithm for neuromemristive systems. SoCC (2014)
Cory E. Merkel, Dhireesha Kudithipudi
Neuromemristive Extreme Learning Machines for Pattern Classification. ISVLSI (2014)
Cory E. Merkel, Dhireesha Kudithipudi
Temperature Sensing RRAM Architecture for 3-D ICs. IEEE Trans. Very Large Scale Integr. Syst. 22 (4) (2014)
Dhireesha Kudithipudi, Cory E. Merkel, Yu Kee Ooi, Quitaba Saleh, Garrett S. Rose
On designing circuit primitives for cortical processors with memristive hardware. SoCC (2014)
Cory E. Merkel, Qutaiba Saleh, Colin Donahue, Dhireesha Kudithipudi
Memristive Reservoir Computing Architecture for Epileptic Seizure Detection. BICA (2014)
Cory E. Merkel, Dhireesha Kudithipudi, Nick Sereni
Periodic activation functions in memristor-based analog neural networks. IJCNN (2013)
Michael Soltiz, Dhireesha Kudithipudi, Cory E. Merkel, Garrett S. Rose, Robinson E. Pino
Memristor-Based Neural Logic Blocks for Nonlinearly Separable Functions. IEEE Trans. Computers 62 (8) (2013)
Cory E. Merkel, Dhireesha Kudithipudi
Towards Thermal Profiling in CMOS/Memristor Hybrid RRAM Architectures. VLSI Design (2012)
David Brenner, Cory E. Merkel, Dhireesha Kudithipudi
Design-time performance evaluation of thermal management policies for SRAM and RRAM based 3D MPSoCs. ACM Great Lakes Symposium on VLSI (2012)
Matthew Catanzaro, Dhireesha Kudithipudi
Reconfigurable RRAM for LUT logic mapping: A case study for reliability enhancement. SoCC (2012)
Dhireesha Kudithipudi, Ayse K. Coskun, Sherief Reda, Qinru Qiu
Temperature-aware computing: Achievements and remaining challenges. IGCC (2012)
Ganesh Khedkar, Dhireesha Kudithipudi
RRAM Motifs for Mitigating Differential Power Analysis Attacks (DPA). ISVLSI (2012)
Michael Soltiz, Cory E. Merkel, Dhireesha Kudithipudi, Garrett S. Rose
RRAM-based adaptive neural logic block for implementing non-linearly separable functions in a single layer. NANOARCH (2012)
Cory E. Merkel, Dhireesha Kudithipudi, Andres Kwasinski
Lightweight energy prediction framework for solar-powered wireless sensor networks. SoCC (2012)
Pradeep S. Nair, Dhireesha Kudithipudi, Eugene B. John, Fred W. Hudson
Execution characteristics of embedded applications on a Pentium 4-based personal computer. J. Embed. Comput. 4 (3-4) (2011)
Satish G. Kandlikar, Dhireesha Kudithipudi, Carlos A. Rubio-Jimenez
Cooling mechanisms in 3D ICs: Thermo-mechanical perspective. IGCC (2011)
J. Kevin Hicks, Dhireesha Kudithipudi
Hybrid Subthreshold and Nearthreshold Design Methodology for Energy Minimization. J. Low Power Electron. 7 (2) (2011)
Cory E. Merkel, Nakul Nagpal, Sindhura Mandalapu, Dhireesha Kudithipudi
Reconfigurable N-level memristor memory design. IJCNN (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Dhireesha Kudithipudi