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 innovation, execution and teamwork. Our goal is to enable students to pursue their futuristic innovative ideas.
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 |
APPLICATION:
Each team should submit an application by the specified deadline (see Timeline tab) that must include:
1. One page abstract of innovation proposal
2. Letter from one or two faculty members recommending the innovation
a. Why the proposal is innovative
b. Why the proposal is important
c. Why the current team is likely to succeed in their proposal
3. Each student's CV
4. Signed copy of QIF rules (both students)
SUBMISSIONS SHOULD BE IN A ZIP FILE
The submission portal will open two weeks before the deadline.
PROPOSAL PHASE:
Selected teams will be notified directly to participate in the next phase by submitting a final proposal that must include a Three-page innovation proposal (plus one for reference/bibliography) including:
a. Introduction and problem definition
b. Innovation proposal and relation to the state of the art
c. One-year horizon of the project, even if the proposal is a multi-year project
d. Strength of the team to achieve the proposal milestones
Please upload your proposal in zip format to the QIF submission portal for updates by the specified deadline. Use your access code received in the confirmation email when you submitted your abstract.
SELECTION OF FINALISTS AND WINNERS:
Finalist teams will be selected to participate in the final presentation phase of the Program. Each finalist team must prepare a presentation slide deck for the judges. Presentation must be in PowerPoint or PDF format. The presentation generally includes
Each Finalist team must also prepare a poster for a poster session to be presented to the judges.
Winning teams will be chosen from these finalists after they present to the judging panel.
ADDITIONAL INFO:
• Applications must be submitted online by the specified deadline (see Timeline tab). All proposals and presentations will be reviewed internally by a team of Qualcomm researchers.
• The official rules for the Qualcomm Innovation Fellowship are available for download and set forth the Program’s governing guidelines.
• All QIF-related information will be announced on this webpage. Please check back regularly for updates.
Qualcomm Research is a division of Qualcomm Technologies, Inc.
Qualcomm Research is a division of Qualcomm Technologies, Inc.
We invite teams to submit proposals in the following areas. We also welcome proposals outside of the sub-areas listed below:
Advanced Semiconductor Electronics
Advances in Communication Techniques and Theory
Qualcomm is inviting applications for the Qualcomm Innovation Fellowship 2020 from PhD students in the Electrical Engineering and Computer Science (and related) departments at:
United States
Canada
Info Sessions are scheduled in October 2020 – details in the ‘Info Sessions’ section
Submission site opens: November 2020
Application submission deadline: December 1, 2020 (10:00AM PST)
Selection announcement: December 18, 2020
Proposal submission deadline: January 25, 2021 (10:00AM PST)
Finalists’ announcement: March 2021
Finalist presentations submission deadline: March 2021
Finalist presentations: April 2021
Winners’ announcement: May 2021
QIF Winners’ Day: October 2021
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
1:35
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