QIF 2021 North America

2021 QIF North America Program Details

We believe that research and development is the key to harnessing the power of imagination and to discovering new possibilities. We are excited to announce a new kind of Fellowship that promotes Qualcomm’s core values of innovationexecution and teamwork. Our goal is to enable students to pursue their futuristic innovative ideas.

Selected Abstracts
Application Process
Areas of Interest
Participating Universities
Timeline
University Innovation  Students Recommenders
Caltech Blending Machine Learning and Control in Autonomous Systems Gautam Goel, Taylan Kargin Babak Hassibi 
CMU Collaboration and Competition: Distributed Multi-agent Reinforcement Learning for IoT Jinhang Zuo, Yi Hu Carlee Joe-Wong, Bob Iannucci
CMU Open World 3D Dynamic Reconstruction For Smart Cities Gengshan Yang, Dinesh Reddy Narapureddy Srinivasa Narasimhan, Deva Ramanan
CMU Providing Architectural Support for Building Privacy-Sensitive Smart Home Apps Haojian Jin, Han Zhang Jason Hong, Yuvraj Agarwal
CMU Real-Time Machine Learning Incorporating Radio-Frequency Fingerprint Augmentation for Secure Radar Sensing Yuyi Shen, Jiachen Xu Vanessa Chen 
CMU Safe Adaptive Learning and Control for Autonomous Driving Charles Noren, Weiye Zhao Changliu Liu 
CMU Zero-Shot Accented Speech Recognition Patrick Conrey, Mark Lindsey Bhiksha Raj 
Cornell Continuously tracking full facial expressions with acoustic sensing on minimally-obtrusive wearables Ke Li, Ruidong Zhang Cheng Zhang 
Cornell Logic-Intensive Networks for Secure and Efficient Learning Jordan Dotzel, Yichi Zhang Zhiru Zhang 
Georgia Tech ANALYSER: A Hardware-Software Co-design Framework to Overcome StochasticImperfection of Mixed Signal DNN Accelerators Payman Behnam, Uday Kamal Saibal Mukhopadhyay 
Georgia Tech Design for Compute-in-Memory Accelerators without ADCs Hongwu Jiang, Wantong Li Shimeng Yu 
Georgia Tech On-line Hardware based Malware Detection using Integrated Machine learning Accelerators Nael Mizanur Rahman, Harshit Kumar  Saibal Mukhopadhyay 
Georgia Tech Playing it Safe: Towards Low-Cost and Generalized Memory Safety Gururaj Saileshwar, Yonghae Kim Moinuddin K Qureshi, Hyesoon Kim
Georgia Tech Revolutionizing EDA Flow through Advanced Machine Learning Algorithms Yi-Chen Lu, Anthony Agnesina Sung Kyu Lim
Michigan Deep Systems Consolidation for Task-Incremental Learning Ekdeep Singh Lubana, Puja Trivedi Robert P. Dick, Danai Koutra
Michigan / Washington Machine Learning Designs for Universal Decoders Mohammad Vahid Jamali, Xiyang Liu Sewoong Oh, Hessam Mahdavifar
MIT Algorithm-Hardware Co-Design for Efficient LiDAR-Based Autonomous Driving Zhijian Liu, Yujun Lin Song Han 
MIT Data-driven optimization for fast and agile trajectory generation Gilhyun Ryou, Ezra Tal Sertac Karaman 
MIT Energy-Efficient System Design for Video Understanding on the Edge Miaorong Wang, Ji Lin Song Han, Anantha Chandrakasan
MIT Long Term Multi-Agent Hybrid Prediction through Online Factored Concept Inference and Continual Hierarchical Learning  Xin Huang , Meng Feng   Brian Williams
MIT On-Device NLP Inference and Training with Algorithm-Hardware Co-Design Hanrui Wang, Han Cai Song Han, Hae-Seung Lee
MIT Privacy-Preserving Collaborative Inference Abhishek Singh, Praneeth Vepakomma Ramesh Raskar, Mehdi Bennis
MIT Sequential tailoring: interleaving learning and decision-making by optimizing unsupervised objectives Ferran Alet, Maria Bauza Leslie Pack Kaelbling, Alberto Rodriguez
MIT Towards Understanding Implicit Biases in Deep Learning Jacob Huh, Hyojin Bahng Pulkit Agrawal, Phillip Isola
Princeton Non-uniform Spectrally Agile Arrays, Multi-band Antenna and Transmitter Front-ends for Spectrum Sharing in mm-Wave Wireless Links Zheng Liu, Hooman Saeidi Kaushik Sengupta 
Princeton Optimization Inspired Neural Architectures for 3D Reconstruction Zachary Teed, Ankit Goyal Jia Deng 
Princeton Quantum Computation for Wireless Networks Sai Srikar Kasi, Minsung Kim Kyle Jamieson 
Purdue University A Generalized Framework for Optimizing ML Workload Acceleration in Processing-in/near Memory Architectures Mustafa Ali, Tanvi Sharma Kaushik Roy 
Purdue University High Performance, Energy-Efficient, and Accurate in-Memory Computing Accelerators for ML Workloads Mustafa Ali, Dong Eun Kim Kaushik Roy 
Purdue University Next-generation Virtual Machine Enclaves Adil Ahmad, Sishuai Gong Pedro Fonseca, Byoungyoung Lee
Purdue University Simily: Precise Control-flow Graph Embedding Space for Measuring Code Similarity Charitha Saumya Gusthinna Waduge, Kirshanthan Sundararajah Milind Kulkarni 
Stanford Implicit Representations for Compositional, Generalizable Scene Understanding Honging Yu, Michelle Guo Jiajun Wu 
Stanford Predicting hand-object interaction for improved haptic feedback in extended reality Mike Salvato, Negin Heravi Allison Okamura, Jeannette Bohg
Stanford Towards Human-like Compositional Generalization in Machines  Eric Mitchell, Shikhar Murty  Chelsea Finn  
Stanford / MIT Efficient & Robust Scene Understanding using Neuro-Symbolic AI Sumith Kulal, Jiayuan Mao Jiajun Wu 
UCB Algorithms for Safe and Data Efficient Reinforcement Learning Ashwin Balakrishna, Brijen Thananjeyan Ken Goldberg, Joseph E. Gonzalez
UCB Asynchronous Neural Accelerator for NP-Hard Optimization Philip Canoza, Saavan Patel Sayeef Salahuddin, Jan M. Rabaey
UCB High-Speed Spatial Light Modulators for Holographic Near Eye Displays Cem Yalcin, Nathan Tessema Ersumo Rikky Muller, Laura Waller
UCB Learning Decentralized Autonomous Vehicle Controllers for Traffic Smoothing Eugene Vinitsky, Abdul Rahman Kriedieh Alexandre Bayen, Dan Work
UCB Practical Lifting for Verification of Trusted Platform Software Kevin Cheang, Federico Mora Sanjit A. Seshia, Alvin Cheung
UCLA A Distributed Privacy-Preserving Machine Learning Framework Using 5G Network Hao-Jen Chien, Shashank Balla Nader Sehatbakhsh 
UCLA A Programmable Receiver with Adaptive Blocker Suppression Vinod Kurian Jacob, Avantika Singh Sudhakar Pamarti 
UCLA A Stochastic Compute-In-Memory Neural Network Accelerator with Variable Precision Tuning Jiyue Yang, Tianmu Li Sudhakar Pamarti, Puneet Gupta
UCLA Breaking one-time authentication in 4G/5G: New attacks and countermeasures Zhaowei Tan, Boyan Ding Songwu Lu 
UCLA High Resolution and Wideband ADC for Sub-6 GHz receiver systems Avantika Singh, Jiazhang Song Sudhakar Pamarti 
UCSD Adapting Articulated 3D Reconstructions at Test-Time Jiteng Mu, Brandon Leung Nuno Vasconcelos, Xiaolong Wang
UCSD An Energy Efficient 5G LNA Exploiting Current Reuse Abhishek Agarwal, Tyler Hack Drew Hall 
UCSD Analog Neuromorphic Computing System based on 2D Oxide Materials Chi-Hsin Huang, Hsuan (Amanda) Chang Kenji Nomura 
UCSD Best-of-Class Digital PLL Frequency Synthesis IC Development Eslam Helal, Amr Eissa Ian Galton 
UCSD Controllable Spatiotemporal Deep Generative Model Rui Wang, Weitang Liu Rose Yu 
UCSD COOPRAD: Cooperative Radar Perception Kshitiz Bansal, Aditya Arun Dinesh Bharadia 
UCSD Deep Early-Fusion Approaches for Autonomous Driving: A Holistic Framework, Models & Analysis Akshay Rangesh, Nachiket Deo  Mohan M. Trivedi 
UCSD Deep Reinforcement Learning for detailed placement optimization Uday Mallappa , Chester Holtz   Chung-Kuan Cheng
UCSD Dual Contradistinctive Variational Transformer Yifan Xu, Zheng Ding Zhuowen Tu 
UCSD End-to-End Scalable AI Accelerator with Hierarchical Reprogrammable Interconnects Sangheon Oh, Gopabandhu Hota Duygu Kuzum, Gert Cauwenberghs
UCSD Generative 3D Modeling and its Applications Chih-Hui Ho, Simeng Zheng Nuno Vasconcelos, Paul H. Siegel
UCSD Grounding neural language models with human sensorimotor judgments James Michaelov, Sean Trott Benjamin Bergen 
UCSD Hardware-friendly Neural Architecture Search for Multi-device System Cheng Fu, Huili Chen Farinaz Koushanfar 
UCSD Headset Facial Expression Tracking with Deep Learning of Skewed Angle Cameras Yinan Xuan, Varun Viswanath Edward Wang 
UCSD High-sensitive Wearable Biosensor using Oxide Semiconductor Yong Zhang, Alex Lee Kenji Nomura 
UCSD Learning Language Representations for Voice-based Conversational Agents for Older Adults Khalil Mrini, Chen Chen Ndapa T. Nakashole, Nadir Weibel
UCSD Learning-Aided Estimation for Situational Awareness in Future Wireless Networks Mingchao Liang, Wenyu Zhang Florian Meyer 
UCSD Lightweight Human Digitization Kunyao Chen, Bang Du Truong Nguyen 
UCSD Neural Network-based Program Decompiler Cheng Fu, Huili Chen Jishen Zhao, Farinaz Koushanfar
UCSD Towards a Systems Perspective on Neural Network Robustness Malhar Jere, Xinqiao Zhang Farinaz Koushanfar 
UCSD Transforming Microarchitectural Predictors with the Power of Neural Transformers Fatemehsadat Mireshghallah, Mohammadkazem Taram Taylor Berg-Kirkpatrick, Dean Tullsen
UIUC Commutated-Circuit-and-Acoustic-Delay-Line-based Adaptive Canceller (CADELAC) Hyungjoo Seo, Steffen Link Songbin Gong, Jin Zhou
UIUC Fine-grained and Generic Acceleration for Data- and Compute-intensive Workloads in the Cloud Yifan Yuan, Dong Kai Wang Nam Sung Kim 
UIUC Improved Security and Efficiency in Mobile Systems via Software Debloating Chaitra Niddodi, Hsuan-Chi Kuo Sibin Mohan, Tianyin Xu
UIUC Monolithic Machine Learning-based Plastic Systems for Patient Monitoring Nathaniel Bleier, Muhammad Husnain Mubarik Rakesh Kumar 
UMD Adaptive Massively Parallel Algorithms for Large-Scale Graph Mining with Low Communication Marina Knittel, Hamed Saleh MohammadTaghi Hajiaghayi 
UMD Toward battery-free continuous sensing for on-body health monitoring Nakul Garg, Yang Bai Nirupam Roy, Kanad Basu
UMD WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic Renkun Ni, Hong-min Chu Tom Goldstein 
University of Toronto Learning Long-Range 3D Object Detectors for High-Speed Autonomous Driving Anas Mahmoud, Juan Carrillo Steven Waslander 
USC Federated Deep Learning: On-device Learning of CV and NLP with Transformers and CNNs Chaoyang He, Saurav Prakash Salman Avestimehr 
USC Planning and Learning for Environmental Adaptive Sampling Christopher Denniston, Gautam Salhotra Gaurav Sukhatme 
USC Secure Privacy-Preserving Machine Learning at the Edge Jinhyun So, Saurav Prakash Salman Avestimehr 
UT Austin Automating Layout Synthesis for Analog and Mixed-Signal Circuits with Human and Machine Intelligence Keren Zhu, Mingjie Liu David Z. Pan 
UT Austin Domain Adaptation Meets Meta-Learning: New Perspectives and Techniques Liam Collins, Matthew Faw Sanjay Shakkottai, Constantine Caramanis
UT Austin Efficient Heterogeneous Federated Learning with Lottery Tickets Allen Farcas, Xiaohan Chen Radu Marculescu, Atlas Wang
UT Austin Federated Generative Learning for Channel Estimation in mmWave and THz systems Akash Doshi, Manan Gupta Jeffrey G. Andrews 
Virginia Tech A Sample-Efficient Deep Reinforcement Learning Framework for 5G Dynamic Spectrum Access and Dynamic Spectrum Sharing Hao-Hsuan Chang, Jiarui Xu Lingjia Liu 
Virginia Tech Deep Reinforcement Learning Meets Resource Allocation in Radio Access Network (RAN) Slicing EMADELDIN Abbas Mazied ABDRABOU, Nima Mohammadi Lingjia Liu 
Virginia Tech mmWave Vehicular Communications: A Road to the Future paved with Better Information and Better Beams! Tarun Cousik, Biplav Choudhury Jeffrey H Reed, Vijay K Shah
Washington Closing the Gap: From Innovation to Real-world Impact Matthew Wallingford, Aditya Kusupati Ali Farhadi 
Washington Cross-Modality Supervision for Object Detection and Tracking under Adverse Autonomous Driving Scenarios Haotian Zhang, Yizhou Wang Jenq-Neng Hwang 
Washington Decentralized Cooperative 5G: Enabling Efficient Handover and Spectrum Coordination Sudheesh Singanamalla, Sachin Nayak Kurtis Heimerl 
Washington Enhanced Automotive Object Recognition in Mutual Radar Interference Sian Jin, Xiangyu Gao Sumit Roy 
Washington Enhanced Self-Interference Suppression with Phase Noise Cancellation for use in Full-duplex Radios YI-HSIANG HUANG, Xichen Li Chris Rudell, Visvesh Sathe
Washington Hybrid Molecular-Electronic Computing for Ubiquitous Biological Sensing Applications Jason Hoffman, Alyssa La Fleur Shwetak Patel, Georg Seelig
Washington / CMU Merging with Confidence: Formally Safe Intention Estimation and Merging Behavior Planning under Uncertainty Anqi Li, Yiwei Lyu Byron Boots, John M. Dolan
Wisconsin-Madison Autonomous Vehicle Domain Adaptation Using Fairness Harrison Rosenberg, Brian Tang Kassem Fawaz 
Wisconsin-Madison Model Backtracking on the Edge Liu Yang, Shashank Rajput Dimitris Papailiopoulos, Kangwook Lee
Wisconsin-Madison PriMon: Monitoring Privacy Compliance at Run-Time for Smart Devices Rishabh Khandelwal, Jingjie Li Kassem Fawaz, Younghyun Kim

Fellowship Winners and Finalists

The Qualcomm Innovation Fellowship began in 2009, and has continued to grow with the addition of more universities, more candidates, and expansion to our research centers internationally. Take a look at a list of all our fellowship winners and finalists from years past:

Qualcomm Innovation Fellowship Finalists' Day

Oct 19, 2020

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