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Shubham Jain
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Publications
- 2024
- [c72]Monodeep Kar, Joel Silberman, Swagath Venkataramani, Viji Srinivasan, Bruce M. Fleischer, Joshua Rubin, JohnDavid Lancaster, Sae Kyu Lee, Matthew Cohen, Matthew M. Ziegler, Nianzheng Cao, Sandra Woodward, Ankur Agrawal, Ching Zhou, Prasanth Chatarasi, Thomas Gooding, Michael Guillorn, Bahman Hekmatshoartabari, Philip Jacob, Radhika Jain, Shubham Jain, Jinwook Jung, Kyu-Hyoun Kim, Siyu Koswatta, Martin Lutz, Alberto Mannari, Abey Mathew, Indira Nair, Ashish Ranjan, Zhibin Ren, Scot Rider, Thomas Roewer, David L. Satterfield, Marcel Schaal, Sanchari Sen, Gustavo Tellez, Hung Tran, Wei Wang, Vidhi Zalani, Jintao Zhang, Xin Zhang, Vinay Shah, Robert M. Senger, Arvind Kumar, Pong-Fei Lu, Leland Chang:
14.1 A Software-Assisted Peak Current Regulation Scheme to Improve Power-Limited Inference Performance in a 5nm AI SoC. ISSCC 2024: 254-256 - [i26]Faith M. Johnson, Bryan Bo Cao, Kristin J. Dana, Shubham Jain, Ashwin Ashok:
Feudal Networks for Visual Navigation. CoRR abs/2402.12498 (2024) - [i25]Faith M. Johnson, Bryan Bo Cao, Kristin J. Dana, Shubham Jain, Ashwin Ashok:
A Landmark-Aware Visual Navigation Dataset. CoRR abs/2402.14281 (2024) - 2023
- [j20]Shubham Jain, Hsinyu Tsai, Ching-Tzu Chen, Ramachandran Muralidhar, Irem Boybat, Martin M. Frank, Stanislaw Wozniak, Milos Stanisavljevic, Praneet Adusumilli, Pritish Narayanan, Kohji Hosokawa, Masatoshi Ishii, Arvind Kumar, Vijay Narayanan, Geoffrey W. Burr:
A Heterogeneous and Programmable Compute-In-Memory Accelerator Architecture for Analog-AI Using Dense 2-D Mesh. IEEE Trans. Very Large Scale Integr. Syst. 31(1): 114-127 (2023) - [j19]Abrar Alali, Stephan Olariu, Shubham Jain:
ADOPT: A system for Alerting Drivers to Occluded Pedestrian Traffic. Veh. Commun. 41: 100601 (2023) - [c67]Martin M. Frank, Ning Li, Malte J. Rasch, Shubham Jain, Ching-Tzu Chen, Ramachandran Muralidhar, Jin-Ping Han, Vijay Narayanan, Timothy Philip, Kevin Brew, Andrew Simon, Iqbal Saraf, Nicole Saulnier, Irem Boybat, Stanislaw Wozniak, Abu Sebastian, Pritish Narayanan, Charles Mackin, An Chen, Hsinyu Tsai, Geoffrey W. Burr:
Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited). IRPS 2023: 1-10 - [c66]Hsinyu Tsai, Pritish Narayanan, Shubham Jain, Stefano Ambrogio, Kohji Hosokawa, Masatoshi Ishii, Charles Mackin, Ching-Tzu Chen, Atsuya Okazaki, Akiyo Nomura, Irem Boybat, Ramachandran Muralidhar, Martin M. Frank, Takeo Yasuda, Alexander M. Friz, Yasuteru Kohda, An Chen, Andrea Fasoli, Malte J. Rasch, Stanislaw Wozniak, Jose Luquin, Vijay Narayanan, Geoffrey W. Burr:
Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited). ISCAS 2023: 1-5 - [c65]Bryan Bo Cao, Abrar Alali, Hansi Liu, Nicholas Meegan, Marco Gruteser, Kristin J. Dana, Ashwin Ashok, Shubham Jain:
ViFiT: Reconstructing Vision Trajectories from IMU and Wi-Fi Fine Time Measurements. ISACom@MobiCom 2023: 13-18 - [c64]Prerna Khanna, Shirin Feiz, Jian Xu, I. V. Ramakrishnan, Shubham Jain, Xiaojun Bi, Aruna Balasubramanian:
AccessWear: Making Smartphone Applications Accessible to Blind Users. MobiCom 2023: 32:1-32:16 - [i22]Bryan Bo Cao, Lawrence O'Gorman, Michael Coss, Shubham Jain:
Data-Side Efficiencies for Lightweight Convolutional Neural Networks. CoRR abs/2308.13057 (2023) - [i21]Bryan Bo Cao, Abrar Alali, Hansi Liu, Nicholas Meegan, Marco Gruteser, Kristin J. Dana, Ashwin Ashok, Shubham Jain:
ViFiT: Reconstructing Vision Trajectories from IMU and Wi-Fi Fine Time Measurements. CoRR abs/2310.03140 (2023) - 2022
- [j18]Md. Rashed Rahman, T. V. Sethuraman, Marco Gruteser, Kristin J. Dana, Shubham Jain, Narayan B. Mandayam, Ashwin Ashok:
Camera-Based Light Emitter Localization Using Correlation of Optical Pilot Sequences. IEEE Access 10: 24368-24382 (2022) - [j17]Tanmay Srivastava, Prerna Khanna, Shijia Pan, Phuc Nguyen, Shubham Jain:
MuteIt: Jaw Motion Based Unvoiced Command Recognition Using Earable. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6(3): 140:1-140:26 (2022) - [j16]Meshari Aljohani, Stephan Olariu, Abrar Alali, Shubham Jain:
A Survey of Parking Solutions for Smart Cities. IEEE Trans. Intell. Transp. Syst. 23(8): 10012-10029 (2022) - [j15]Reena Elangovan, Shubham Jain, Anand Raghunathan:
Ax-BxP: Approximate Blocked Computation for Precision-reconfigurable Deep Neural Network Acceleration. ACM Trans. Design Autom. Electr. Syst. 27(3): 28:1-28:20 (2022) - [c61]Moinak Bhattacharya, Shubham Jain, Prateek Prasanna:
RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-Guided Disease Classification. ECCV (21) 2022: 679-698 - [c59]Hansi Liu, Abrar Alali, Mohamed Ibrahim, Bryan Bo Cao, Nicholas Meegan, Hongyu Li, Marco Gruteser, Shubham Jain, Kristin J. Dana, Ashwin Ashok, Bin Cheng, Hongsheng Lu:
Vi-Fi: Associating Moving Subjects across Vision and Wireless Sensors. IPSN 2022: 208-219 - [c58]Dimitris Vordonis, Dimitris Giannopoulos, Panagiotis Papaioannou, Christos Tranoris, Spyros G. Denazis, Ran Rahav, Baruch Altman, Anne-Marie Bosneag, Shubham Jain, Udi Margolin, Bader Mawasy, Konstantinos Oikonomou, Ioannis Markopoulos:
Monitoring and Evaluation of 5G Key Performance Indicators in Media Vertical Applications. MeditCom 2022: 203-208 - [c57]Moinak Bhattacharya, Shubham Jain, Prateek Prasanna:
GazeRadar: A Gaze and Radiomics-Guided Disease Localization Framework. MICCAI (3) 2022: 686-696 - [c56]Tanmay Srivastava, Prerna Khanna, Shijia Pan, Phuc Nguyen, Shubham Jain:
Leveraging earables for unvoiced command recognition. MobiSys 2022: 622-623 - [c55]Bryan Bo Cao, Abrar Alali, Hansi Liu, Nicholas Meegan, Marco Gruteser, Kristin J. Dana, Ashwin Ashok, Shubham Jain:
ViTag: Online WiFi Fine Time Measurements Aided Vision-Motion Identity Association in Multi-person Environments. SECON 2022: 19-27 - [i17]Moinak Bhattacharya, Shubham Jain, Prateek Prasanna:
RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention-guided Disease Classification. CoRR abs/2202.11781 (2022) - [i16]Nicholas Meegan, Hansi Liu, Bryan Bo Cao, Abrar Alali, Kristin J. Dana, Marco Gruteser, Shubham Jain, Ashwin Ashok:
ViFiCon: Vision and Wireless Association Via Self-Supervised Contrastive Learning. CoRR abs/2210.05513 (2022) - [i15]Abrar Alali, Stephan Olariu, Shubham Jain:
ADOPT: A system for Alerting Drivers to Occluded Pedestrian Traffic. CoRR abs/2212.00137 (2022) - 2021
- [j14]Shubham Jain, Abhronil Sengupta, Kaushik Roy, Anand Raghunathan:
RxNN: A Framework for Evaluating Deep Neural Networks on Resistive Crossbars. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 40(2): 326-338 (2021) - [j13]Sourjya Roy, Shrihari Sridharan, Shubham Jain, Anand Raghunathan:
TxSim: Modeling Training of Deep Neural Networks on Resistive Crossbar Systems. IEEE Trans. Very Large Scale Integr. Syst. 29(4): 730-738 (2021) - [c53]Indranil Chakraborty, Sourjya Roy, Shrihari Sridharan, Mustafa Fayez Ali, Aayush Ankit, Shubham Jain, Anand Raghunathan:
Design Tools for Resistive Crossbar based Machine Learning Accelerators. AICAS 2021: 1-4 - [c49]Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Wang, Sanchari Sen, Jintao Zhang, Ankur Agrawal, Monodeep Kar, Shubham Jain, Alberto Mannari, Hoang Tran, Yulong Li, Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Marcel Schaal, Mauricio J. Serrano, Jungwook Choi, Xiao Sun, Naigang Wang, Chia-Yu Chen, Allison Allain, James Bonanno, Nianzheng Cao, Robert Casatuta, Matthew Cohen, Bruce M. Fleischer, Michael Guillorn, Howard Haynie, Jinwook Jung, Mingu Kang, Kyu-Hyoun Kim, Siyu Koswatta, Sae Kyu Lee, Martin Lutz, Silvia M. Mueller, Jinwook Oh, Ashish Ranjan, Zhibin Ren, Scot Rider, Kerstin Schelm, Michael Scheuermann, Joel Silberman, Jie Yang, Vidhi Zalani, Xin Zhang, Ching Zhou, Matthew M. Ziegler, Vinay Shah, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan:
RaPiD: AI Accelerator for Ultra-low Precision Training and Inference. ISCA 2021: 153-166 - [c43]Hansi Liu, Abrar Alali, Mohamed Ibrahim, Hongyu Li, Marco Gruteser, Shubham Jain, Kristin J. Dana, Ashwin Ashok, Bin Cheng, Hongsheng Lu:
Lost and Found!: associating target persons in camera surveillance footage with smartphone identifiers. MobiSys 2021: 499-500 - [c42]Prerna Khanna, Tanmay Srivastava, Shijia Pan, Shubham Jain, Phuc Nguyen:
JawSense: Recognizing Unvoiced Sound using a Low-cost Ear-worn System. HotMobile 2021: 44-49 - [c41]Prerna Khanna, Tanmay Srivastava, Shijia Pan, Shubham Jain, Phuc Nguyen:
JawSense: Recognizing Unvoiced Sound using a Low-cost Ear-worn System. HotMobile 2021: 177-178 - 2020
- [j11]Swagath Venkataramani, Xiao Sun, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Mingu Kang, Ankur Agarwal, Jinwook Oh, Shubham Jain, Tina Babinsky, Nianzheng Cao, Thomas W. Fox, Bruce M. Fleischer, George Gristede, Michael Guillorn, Howard Haynie, Hiroshi Inoue, Kazuaki Ishizaki, Michael J. Klaiber, Shih-Hsien Lo, Gary W. Maier, Silvia M. Mueller, Michael Scheuermann, Eri Ogawa, Marcel Schaal, Mauricio J. Serrano, Joel Silberman, Christos Vezyrtzis, Wei Wang, Fanchieh Yee, Jintao Zhang, Matthew M. Ziegler, Ching Zhou, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Vijayalakshmi Srinivasan, Leland Chang, Kailash Gopalakrishnan:
Efficient AI System Design With Cross-Layer Approximate Computing. Proc. IEEE 108(12): 2232-2250 (2020) - [j10]Indranil Chakraborty, Mustafa Fayez Ali, Aayush Ankit, Shubham Jain, Sourjya Roy, Shrihari Sridharan, Amogh Agrawal, Anand Raghunathan, Kaushik Roy:
Resistive Crossbars as Approximate Hardware Building Blocks for Machine Learning: Opportunities and Challenges. Proc. IEEE 108(12): 2276-2310 (2020) - [j9]Shubham Jain, Anand Raghunathan:
CxDNN: Hardware-software Compensation Methods for Deep Neural Networks on Resistive Crossbar Systems. ACM Trans. Embed. Comput. Syst. 18(6): 113:1-113:23 (2020) - [j8]Shubham Jain, Sumeet Kumar Gupta, Anand Raghunathan:
TiM-DNN: Ternary In-Memory Accelerator for Deep Neural Networks. IEEE Trans. Very Large Scale Integr. Syst. 28(7): 1567-1577 (2020) - [c38]Sandeep Krishna Thirumala, Shubham Jain, Sumeet Kumar Gupta, Anand Raghunathan:
Ternary Compute-Enabled Memory using Ferroelectric Transistors for Accelerating Deep Neural Networks. DATE 2020: 31-36 - [c37]David Brooks, Martin M. Frank, Tayfun Gokmen, Udit Gupta, Xiaobo Sharon Hu, Shubham Jain, Ann Franchesca Laguna, Michael T. Niemier, Ian O'Connor, Anand Raghunathan, Ashish Ranjan, Dayane Reis, Jacob R. Stevens, Carole-Jean Wu, Xunzhao Yin:
Emerging Neural Workloads and Their Impact on Hardware. DATE 2020: 1462-1471 - [i12]Sourjya Roy, Shrihari Sridharan, Shubham Jain, Anand Raghunathan:
TxSim: Modeling Training of Deep Neural Networks on Resistive Crossbar Systems. CoRR abs/2002.11151 (2020) - [i10]Reena Elangovan, Shubham Jain, Anand Raghunathan:
Ax-BxP: Approximate Blocked Computation for Precision-Reconfigurable Deep Neural Network Acceleration. CoRR abs/2011.13000 (2020) - 2019
- [j6]Shubham Jain, Aayush Ankit, Indranil Chakraborty, Tayfun Gokmen, Malte J. Rasch, Wilfried Haensch, Kaushik Roy, Anand Raghunathan:
Neural network accelerator design with resistive crossbars: Opportunities and challenges. IBM J. Res. Dev. 63(6): 10:1-10:13 (2019) - [j5]Sanchari Sen, Shubham Jain, Swagath Venkataramani, Anand Raghunathan:
SparCE: Sparsity Aware General-Purpose Core Extensions to Accelerate Deep Neural Networks. IEEE Trans. Computers 68(6): 912-925 (2019) - [j4]Shubham Jain, Marco Gruteser:
Recognizing Textures with Mobile Cameras for Pedestrian Safety Applications. IEEE Trans. Mob. Comput. 18(8): 1911-1923 (2019) - [c31]Ashish Ranjan, Shubham Jain, Jacob R. Stevens, Dipankar Das, Bharat Kaul, Anand Raghunathan:
X-MANN: A Crossbar based Architecture for Memory Augmented Neural Networks. DAC 2019: 130 - [c30]Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang:
BiScaled-DNN: Quantizing Long-tailed Datastructures with Two Scale Factors for Deep Neural Networks. DAC 2019: 201 - [c28]Sandeep Krishna Thirumala, Shubham Jain, Anand Raghunathan, Sumeet Kumar Gupta:
Non-Volatile Memory utilizing Reconfigurable Ferroelectric Transistors to enable Differential Read and Energy-Efficient In-Memory Computation. ISLPED 2019: 1-6 - [c27]Hansi Liu, Pengfei Ren, Shubham Jain, Mohannad Murad, Marco Gruteser, Fan Bai:
FusionEye: Perception Sharing for Connected Vehicles and its Bandwidth-Accuracy Trade-offs. SECON 2019: 1-9 - [p1]Ashish Ranjan, Swagath Venkataramani, Shubham Jain, Younghoon Kim, Shankar Ganesh Ramasubramanian, Arnab Raha, Kaushik Roy, Anand Raghunathan:
Automatic Synthesis Techniques for Approximate Circuits. Approximate Circuits 2019: 123-140 - [i9]Shubham Jain, Sumeet Kumar Gupta, Anand Raghunathan:
TiM-DNN: Ternary in-Memory accelerator for Deep Neural Networks. CoRR abs/1909.06892 (2019) - [i8]Sandeep Krishna Thirumala, Yi-Tse Hung, Shubham Jain, Arnab Raha, Niharika Thakuria, Vijay Raghunathan, Anand Raghunathan, Zhihong Chen, Sumeet Kumar Gupta:
Valley-Coupled-Spintronic Non-Volatile Memories with Compute-In-Memory Support. CoRR abs/1912.07821 (2019) - 2018
- [j3]Olivier Bernard, Alain Lalande, Clément Zotti, Frederic Cervenansky, Xin Yang, Pheng-Ann Heng, Irem Cetin, Karim Lekadir, Oscar Camara, Miguel Ángel González Ballester, Gerard Sanroma, Sandy Napel, Steffen E. Petersen, Georgios Tziritas, Elias Grinias, Mahendra Khened, Alex Varghese, Ganapathy Krishnamurthi, Marc-Michel Rohé, Xavier Pennec, Maxime Sermesant, Fabian Isensee, Paul Jaeger, Klaus H. Maier-Hein, Peter M. Full, Ivo Wolf, Sandy Engelhardt, Christian F. Baumgartner, Lisa M. Koch, Jelmer M. Wolterink, Ivana Isgum, Yeonggul Jang, Yoonmi Hong, Jay Patravali, Shubham Jain, Olivier Humbert, Pierre-Marc Jodoin:
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved? IEEE Trans. Medical Imaging 37(11): 2514-2525 (2018) - [j2]Shubham Jain, Ashish Ranjan, Kaushik Roy, Anand Raghunathan:
Computing in Memory With Spin-Transfer Torque Magnetic RAM. IEEE Trans. Very Large Scale Integr. Syst. 26(3): 470-483 (2018) - [j1]Hang Qiu, Jinzhu Chen, Shubham Jain, Yurong Jiang, Matthew McCartney, Gorkem Kar, Fan Bai, Donald Grimm, Marco Gruteser, Ramesh Govindan:
Towards Robust Vehicular Context Sensing. IEEE Trans. Veh. Technol. 67(3): 1909-1922 (2018) - [c24]Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Pierce Chuang, Leland Chang:
Compensated-DNN: energy efficient low-precision deep neural networks by compensating quantization errors. DAC 2018: 38:1-38:6 - [c23]Shubham Jain, Sachin S. Sapatnekar, Jianping Wang, Kaushik Roy, Anand Raghunathan:
Computing-in-memory with spintronics. DATE 2018: 1640-1645 - [c22]Christianne Nesbitt, Ajay Gupta, Shubham Jain, Kurt Maly, Hamid Reza Okhravi:
Reliability of Wearable Sensors to Detect Agitation in Patients with Dementia: A Pilot Study. ICBBT 2018: 73-77 - [i7]Shubham Jain, Abhronil Sengupta, Kaushik Roy, Anand Raghunathan:
Rx-Caffe: Framework for evaluating and training Deep Neural Networks on Resistive Crossbars. CoRR abs/1809.00072 (2018) - 2017
- [c20]Gorkem Kar, Shubham Jain, Marco Gruteser, Jinzhu Chen, Fan Bai, Ramesh Govindan:
PredriveID: pre-trip driver identification from in-vehicle data. SEC 2017: 2:1-2:12 - [c19]Gorkem Kar, Shubham Jain, Marco Gruteser, Fan Bai, Ramesh Govindan:
Real-time traffic estimation at vehicular edge nodes. SEC 2017: 3:1-3:13 - [c17]Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron C. Courville, Yoshua Bengio:
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model. ICLR (Poster) 2017 - [c16]Shubham Jain, Viet Nguyen, Marco Gruteser, Paramvir Bahl:
Panoptes: servicing multiple applications simultaneously using steerable cameras. IPSN 2017: 119-130 - [c15]Jay Patravali, Shubham Jain, Sasank Chilamkurthy:
2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation. STACOM@MICCAI 2017: 130-139 - [i6]Shubham Jain, Ashish Ranjan, Kaushik Roy, Anand Raghunathan:
Computing in Memory with Spin-Transfer Torque Magnetic RAM. CoRR abs/1703.02118 (2017) - [i5]Jay Patravali, Shubham Jain, Sasank Chilamkurthy:
2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation. CoRR abs/1707.09813 (2017) - [i4]Shubham Jain, Marco Gruteser:
Recognizing Textures with Mobile Cameras for Pedestrian Safety Applications. CoRR abs/1711.00558 (2017) - [i3]Sanchari Sen, Shubham Jain, Swagath Venkataramani, Anand Raghunathan:
SparCE: Sparsity aware General Purpose Core Extensions to Accelerate Deep Neural Networks. CoRR abs/1711.06315 (2017) - 2016
- [c11]Shubham Jain, Swagath Venkataramani, Anand Raghunathan:
Approximation through logic isolation for the design of quality configurable circuits. DATE 2016: 612-617 - [i2]Soroush Mehri, Kundan Kumar, Ishaan Gulrajani, Rithesh Kumar, Shubham Jain, Jose Sotelo, Aaron C. Courville, Yoshua Bengio:
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model. CoRR abs/1612.07837 (2016) - 2015
- [c8]Shubham Jain, Carlo Borgiattino, Yanzhi Ren, Marco Gruteser, Yingying Chen, Carla-Fabiana Chiasserini:
LookUp: Enabling Pedestrian Safety Services via Shoe Sensing. MobiSys 2015: 257-271 - [c7]Shubham Jain, Carlo Borgiattino, Yanzhi Ren, Marco Gruteser, Yingying Chen, Carla-Fabiana Chiasserini:
Video: LookUp!: Enabling Pedestrian Safety Services via Shoe Sensing. MobiSys 2015: 435 - 2014
- [c6]Trisha Datta, Shubham Jain, Marco Gruteser:
Towards City-Scale Smartphone Sensing of Potentially Unsafe Pedestrian Movements. MASS 2014: 663-667 - [c5]Shubham Jain, Carlo Borgiattino, Yanzhi Ren, Marco Gruteser, Yingying Chen:
On the limits of positioning-based pedestrian risk awareness. MARS@MobiSys 2014: 23-28 - [c4]Ashwin Ashok, Shubham Jain, Marco Gruteser, Narayan B. Mandayam, Wenjia Yuan, Kristin J. Dana:
Capacity of pervasive camera based communication under perspective distortions. PerCom 2014: 112-120 - 2013
- [c2]Prateek Prasanna, Shubham Jain, Neelakshi Bhagat, Anant Madabhushi:
Decision support system for detection of diabetic retinopathy using smartphones. PervasiveHealth 2013: 176-179
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