QIF 2022 North America

2022 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 innovation, execution and teamwork. Our goal is to enable students to pursue their futuristic innovative ideas.

Winners
Finalist Selections
Finalist Instructions
Selected Abstracts
Application Process
Areas of Interest
Participating Universities
Timeline

 

We are pleased to announce 19 winners for the Qualcomm Innovation Fellowship (North America) – 2022. Congratulations to the winners!

We commend each of the finalist teams on excellent presentations and quality proposals.

 

University Innovation Title Students Recommender(s)
CMU Safety-Critical Scenarios Generation and Generalization for Autonomous Driving Wenhao Ding, Jiacheng Zhu Ding Zhao, Bo Li
CMU Near and Far-Field Sensor Fusion for 3D Body Pose Estimation and Tracking Yu-Jhe Li, Zhengyi Luo Kris Kitani
CMU/MIT Holistic Distributed Deep Learning Compilation with Automated Cross-stack Optimization Byungsoo Jeon, Sunghyun Kim Tianqi Chen, Zhihao Jia
Cornell Power Inference with Self-Supervised Learning Chenhui Deng, Andrew Butt Zhiru Zhang
Georgia Tech/UT Austin Real-time Visual Processing for Autonomous Driving via Video Transformer with Data-Model-Accelerator Tri-design Rishov Sarkar, Zhiwen Fan Callie Hao, Atlas Wang
Michigan Algorithm-Hardware Co-Design for Energy-Efficient Autonomous Planning Anthony Opipari, Alphonsus Adu-Bredu Odest Chadwicke Jenkins
MIT Gallium Nitride CMOS Technology for the Next Generation of RF Front End Modules Qingyun Xie, John Niroula Tomas Palacios
MIT System-Algorithm Co-Design for Efficient On-Device Training Ji Lin, Ligeng Zhu Song Han
Princeton Bridging the Gap between Domain-Specific Languages and Hardware Accelerators with Unified Software/Hardware Abstractions Yu Zeng, Yi Li Sharad Malik
UCB High-Speed SerDes with Feed-Forward Non-Linear Equalizer on Silicon Photonics for Immersive AR/VR Hardware Kunmo Kim, Sunjin Choi Ali Niknejad, Vladimir Stojanovic
UCSD Neural-Enhanced Multipath-Aided Positioning Mingchao Liang, Wenyu Zhang Florian Meyer
UCSD Augmenting environment sensing with multi-beam 5G mmWave systems Ish Kumar Jain, Raghav Subbaraman Dinesh Bharadia, Aaron Schulman
UCSD Active Learning for Efficient Annotations of Very Large Datasets: Framework, Models, Metrics, and Case Studies in Autonomous Driving Ross Greer, Kuan-Lin Chen Mohan Trivedi, Bhaskar Rao
UCSD Transformers as Meta-Learners for Neural Fields Yinbo Chen, Jiarui Xu Xiaolong Wang
UCSD Bridging Semantic, Geometric and Physical Reasoning in Indoor 3D Scenes Yu-Ying Yeh, Rui Zhu Manmohan Chandraker
UCSD Robust Machine Learning in IoT Devices Xiyuan Zhang, Ranak Roy Chowdhury Rajesh Gupta, Jingbo Shang
UIUC Provably Robust Machine Learning for Wireless Systems Zikun Liu, Calvin Xu Deepak Vasisht, Gagandeep Singh
UT Austin Tunable ultra-small monolithically-rolled-up filter network by piezoelectric actuation Zhendong Yang, Kristen Nguyen Xiuling Li, Songbin Gong
UT Austin Many-domain Processors: Securing 100s of Concurrent Security Domains Shijia Wei, Prateek Sahu Mohit Tiwari

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:

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Qualcomm Innovation Fellowship Finalists' Day

May 28, 2016 | 1:35

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