--- markdown_generated_at: "2026-10-14" title: "2025 North America Program Details" url: "https://www.qualcomm.com/research/university-relations/innovation-fellowship/2025-north-america" description: "Apply for the 2025 Qualcomm Innovation Fellowship for the North America region. Application details, participating universities, and areas of interest." canonicalUrl: "https://www.qualcomm.com/research/university-relations/innovation-fellowship/2025-north-america" --- The 2025 Qualcomm Innovation Fellowship Submission Portal is now CLOSED # 2025 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. [Learn about our other QIF programs](https://www.qualcomm.com/research/university-relations/innovation-fellowship) - Winners - Finalist Selections - Finalist Instructions - Timeline - Participating Universities - Selected Abstracts - Areas of Interest - Application & Proposal Phase - File Naming Requirements ## 2025 North American Winners ## Congratulations to the 17 winning teams of Qualcomm Innovation Fellowship North America 2025! We commend each of the finalists on excellent presentations and quality proposals. ![](https://s7d1.scene7.com/is/image/dmqualcommprod/marziyeh-rezaei?$QC_Responsive$&fmt=png-alpha) #### Marziyeh Rezaei Ultra-low power Coherent Front-haul Optical Links to Enable multi-Tb/s Capacity for 6G Massive MIMOs and Edge AI Datacenters Washington ![](https://s7d1.scene7.com/is/image/dmqualcommprod/pengyu-zeng?$QC_Responsive$&fmt=png-alpha) #### Pengyu Zeng Ultra-low power Coherent Front-haul Optical Links to Enable multi-Tb/s Capacity for 6G Massive MIMOs and Edge AI Datacenters Washington ![](https://s7d1.scene7.com/is/image/dmqualcommprod/jonathan-zhou600-1?$QC_Responsive$&fmt=png-alpha) #### Jonathan Zhou AI-Enabled End-to-end Synthesis of Radio Frequency Integrated Circuits and Systems Princeton ![](https://www.qualcomm.com/content/dam/qcomm-martech/dm-assets/images/company/research/university-relations/qif-north-america-2025-winners/Sherif.png?$QC_Responsive$&fmt=png-alpha) #### Sherif Ghozzy AI-Enabled End-to-end Synthesis of Radio Frequency Integrated Circuits and Systems Princeton ![](https://s7d1.scene7.com/is/image/dmqualcommprod/jiangyifei-zhu?$QC_Responsive$&fmt=png-alpha) #### Jiangyifei Zhu Contactless Cardiovascular Health Monitoring using AI-enabled mmWave Radars CMU ![](https://s7d1.scene7.com/is/image/dmqualcommprod/kuang-yuan?$QC_Responsive$&fmt=png-alpha) #### Kuang Yuan Contactless Cardiovascular Health Monitoring using AI-enabled mmWave Radars CMU ![](https://s7d1.scene7.com/is/image/dmqualcommprod/ruiyi-shen?$QC_Responsive$&fmt=png-alpha) #### Ruiyi Shen Joint Communication and Sensing Using Beams Carrying Orbital Angular Momentum Princeton ![](https://s7d1.scene7.com/is/image/dmqualcommprod/poorya?$QC_Responsive$&fmt=png-alpha) #### Poorya Mollahosseini Joint Communication and Sensing Using Beams Carrying Orbital Angular Momentum Princeton ![](https://s7d1.scene7.com/is/image/dmqualcommprod/sandro-papais-1?$QC_Responsive$&fmt=png-alpha) #### Sandro Papais Spatiotemporal Reasoning for Unified Perception and Prediction World Models University of Toronto ![](https://s7d1.scene7.com/is/image/dmqualcommprod/letian-wang?$QC_Responsive$&fmt=png-alpha) #### Letian Wang Spatiotemporal Reasoning for Unified Perception and Prediction World Models University of Toronto ![](https://s7d1.scene7.com/is/image/dmqualcommprod/jiawei-yang?$QC_Responsive$&fmt=png-alpha) #### Jiawei Yang Building Next-Generation Foundation Models for Autonomous Driving through Self-Supervised 4D Neural Reconstruction USC ![](https://s7d1.scene7.com/is/image/dmqualcommprod/cameron-smith-512x512?$QC_Responsive$&fmt=png-alpha) #### Cameron Smith Building Next-Generation Foundation Models for Autonomous Driving through Self-Supervised 4D Neural Reconstruction USC ![](https://s7d1.scene7.com/is/image/dmqualcommprod/deepak-sridhar?$QC_Responsive$&fmt=png-alpha) #### Deepak Sridhar Meta-Prompting for Scalable and Efficient Adaptation, Personalization, and Fine-Grained Control of Foundation Models UCSD ![](https://s7d1.scene7.com/is/image/dmqualcommprod/alakh-desai?$QC_Responsive$&fmt=png-alpha) #### Alakh Himanshu Desai Meta-Prompting for Scalable and Efficient Adaptation, Personalization, and Fine-Grained Control of Foundation Models UCSD ![](https://s7d1.scene7.com/is/image/dmqualcommprod/haoran-geng-1?$QC_Responsive$&fmt=png-alpha) #### Haoran Geng Bridging the Real2Sim2Real Gap for Generalizable Robot Learning with Dynamic 3D Modeling UCB ![](https://s7d1.scene7.com/is/image/dmqualcommprod/junyi-zhang?$QC_Responsive$&fmt=png-alpha) #### Junyi Zhang Bridging the Real2Sim2Real Gap for Generalizable Robot Learning with Dynamic 3D Modeling UCB ![](https://s7d1.scene7.com/is/image/dmqualcommprod/paschal-amusuo-1?$QC_Responsive$&fmt=png-alpha) #### Paschal Amusuo AutoUP: Unit Proof Generation for Enabling Code-level Security Verification Purdue University ![](https://s7d1.scene7.com/is/image/dmqualcommprod/dharun-anandayuvaraj-1?$QC_Responsive$&fmt=png-alpha) #### Dharun Anandayuvaraj AutoUP: Unit Proof Generation for Enabling Code-level Security Verification Purdue University ![](https://s7d1.scene7.com/is/image/dmqualcommprod/dhruv-thapar?$QC_Responsive$&fmt=png-alpha) #### Dhruv Thapar SMART: Scalable Machine Learning-Assisted Routing-Aware Testing for Many-Chiplet FOWLP ASU ![](https://s7d1.scene7.com/is/image/dmqualcommprod/partho-bhoumik-1?$QC_Responsive$&fmt=png-alpha) #### Partho Bhoumik SMART: Scalable Machine Learning-Assisted Routing-Aware Testing for Many-Chiplet FOWLP ASU ![](https://s7d1.scene7.com/is/image/dmqualcommprod/jiho-kim?$QC_Responsive$&fmt=png-alpha) #### Jiho Kim Network-on-X: Hierarchical Modeling and DSE for 3D Heterogeneous Chiplet Architectures Georgia Tech ![](https://s7d1.scene7.com/is/image/dmqualcommprod/danish-baig?$QC_Responsive$&fmt=png-alpha) #### Danish Baig Network-on-X: Hierarchical Modeling and DSE for 3D Heterogeneous Chiplet Architectures Georgia Tech ![](https://s7d1.scene7.com/is/image/dmqualcommprod/sujay-pandit-2?$QC_Responsive$&fmt=png-alpha) #### Sujay Pandit Machine learning based power estimation for reconfigurable SoCs Purdue University ![](https://s7d1.scene7.com/is/image/dmqualcommprod/aradana-mohan-parvathy?$QC_Responsive$&fmt=png-alpha) #### Aradhana Mohan Parvathy Machine learning based power estimation for reconfigurable SoCs Purdue University ![](https://s7d1.scene7.com/is/image/dmqualcommprod/megan-frisella?$QC_Responsive$&fmt=png-alpha) #### Megan Frisella Productive Programming of Multi-Threaded Hardware Accelerators Washington ![](https://s7d1.scene7.com/is/image/dmqualcommprod/andrew-alex?$QC_Responsive$&fmt=png-alpha) #### Andrew Alex Productive Programming of Multi-Threaded Hardware Accelerators Washington ![](https://s7d1.scene7.com/is/image/dmqualcommprod/shwai-he?$QC_Responsive$&fmt=png-alpha) #### Shwai He Less Attention, Much Faster: Toward a Future of Efficiency-Optimized Transformer Architectures UMD ![](https://s7d1.scene7.com/is/image/dmqualcommprod/guoheng-sun?$QC_Responsive$&fmt=png-alpha) #### Guoheng Sun Less Attention, Much Faster: Toward a Future of Efficiency-Optimized Transformer Architectures UMD ![](https://s7d1.scene7.com/is/image/dmqualcommprod/shiyu-wang-1?$QC_Responsive$&fmt=png-alpha) #### Shiyu Wang Fast Manifold Denoising by Learning Traversals Columbia ![](https://s7d1.scene7.com/is/image/dmqualcommprod/miriam-avagyan-1?$QC_Responsive$&fmt=png-alpha) #### Mariam Avagyan Fast Manifold Denoising by Learning Traversals Columbia ![](https://s7d1.scene7.com/is/image/dmqualcommprod/zixian-ma?$QC_Responsive$&fmt=png-alpha) #### Zixian Ma Learning Multi-modal Agents that Can Reason and Act for Complex Multi- modal Tasks with Synthetic Data Washington ![](https://s7d1.scene7.com/is/image/dmqualcommprod/yushi-hu?$QC_Responsive$&fmt=png-alpha) #### Yushi Hu Learning Multi-modal Agents that Can Reason and Act for Complex Multi- modal Tasks with Synthetic Data Washington ![](https://s7d1.scene7.com/is/image/dmqualcommprod/christophe-gyurgyik-2?$QC_Responsive$&fmt=png-alpha) #### Christophe Gyurgyik Decoupling Algorithms from Data Structures for High-Performance Computing Stanford ![](https://s7d1.scene7.com/is/image/dmqualcommprod/alexander-root-1?$QC_Responsive$&fmt=png-alpha) #### Alexander J Root Decoupling Algorithms from Data Structures for High-Performance Computing Stanford ## 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: [Winners](https://www.qualcomm.com/research/university-relations/innovation-fellowship/winners) [Finalists](https://www.qualcomm.com/research/university-relations/innovation-fellowship/finalists)