QIF 2019 North America

2019 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 partnership. Our goal is to enable students to pursue their futuristic innovative ideas.

Application Process
Participating Universities
Areas of Interest
Timeline
Winners

Application:

Each team shall submit an application by the specified deadline (see Timeline tab) that must include:

  • 1-page abstract of innovation proposal
  • Letter from one or two faculty members recommending the innovation
    • Why the proposal is innovative
    • Why the proposal is important
    • Why the current team is likely to succeed in their proposal
  • Each student's CV
  • Signed copy of QIF rules (both students)

Submissions should be in a .zip file

The submission portal will open two weeks before the deadline.

 

Next Phase:

Selected teams will be notified directly to participate in the next phase by submitting a final proposal that must include:

Three-page innovation proposal (plus one for reference/bibliography) including:

  • Introduction and problem definition
  • Innovation proposal and relation to the state of the art
  • One-year horizon of the project, even if the proposal is a multi-year project
  • Strength of the team to achieve the proposal milestones

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 12-minute presentation for the judges. Presentation must be in PowerPoint or PDF format. The presentation generally includes:

  • The idea
  • The differentiating factors from state of the art
  • The execution plan / strength of the team

The winning teams will be chosen from these finalists after they present to the judging panel.

 

Additional Information:

  • 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.

More Info?

See FAQs for more details

Do you need further information? Please direct your questions to: innovation.fellowship@qualcomm.com

Qualcomm Research is a division of Qualcomm Technologies, Inc.

Qualcomm is inviting applications for the Qualcomm Innovation Fellowship 2019 from PhD students in the Electrical Engineering and Computer Science (and related) departments at:

United States

  • California Institute of Technology
  • Carnegie Mellon University (CMU)
  • Columbia University
  • Cornell University
  • Georgia Institute of Technology
  • Massachusetts Institute of Technology (MIT)
  • Princeton University
  • Rutgers University
  • Stanford University
  • UC Berkeley (UCB)
  • UC Los Angeles (UCLA)
  • UC San Diego (UCSD)
  • UC Santa Barbara (UCSB)
  • University of Illinois at Urbana-Champaign (UIUC)
  • University of Maryland, College Park
  • University of Michigan
  • University of Southern California (USC)
  • University of Texas at Austin
  • University of Washington
  • University of Wisconsin-Madison

Canada

  • University of Montreal
  • University of Toronto

We invite teams to submit proposals in the following areas. We also welcome proposals outside of the sub-areas listed below:

Advanced Semiconductor Electronics

  • Ultra-low (uW) power embedded platform for edge computing (ULP architectures and designs, HW accelerators, power generation and management, novel memories, security)
  • Novel materials and heterogeneous integration (2D semiconductors, GaAs, GaN, etc.)
  • CMOS package integration (thermal-aware designs or circuits, advanced packaging techniques, antenna-in-package etc.)
  • RF / analog ASICs and architectures (Sub-6GHz 5G power amplifiers, mmWave RFIC and Data Converters for 5G NR, adaptive RF signal processing algorithms, etc.)
  • Advanced antenna (millimeter-wave and phase-array antennas), novel antenna materials, structures and implementations
  • Power Management ASICs (wide bandwidth SMPS, wide bandwidth envelope tracker, embedded regulation)

Advances in Communication Techniques and Theory

  • Ultra-reliable and low latency communications
  • Wide-area wireless networks using high-frequency and mmWave spectrum
  • Massive MIMO, network MIMO, and coordinated multipoint processing
  • Wireless systems for unlicensed/shared spectrum
  • Low energy networks (Bluetooth LE, 802.15.4, Zigbee, Wi-Fi, etc.)
  • Advanced low power HW/FW/SW modem implementation approaches

Autonomous Driving

  • Advanced sensors and sensor fusion
  • Imaging radar
  • Computer vision for autonomy
  • Sensor fusion with deep learning
  • Behavior planning with uncertainty

Machine Learning

  • Natural language processing
  • Computer vision
  • Reinforcement and continual learning
  • On-device training
  • Intermediate representation for machine learning workloads/compilers
  • Transfer learning and Knowledge distillation
  • Novel compute architectures for ML tasks, e.g. in-memory compute, analog compute
  • Extreme energy efficient inference hardware accelerators for ML loads and lower complexity algorithms and convolutional nets
  • Generic Attribution methods for deriving non NN-based solutions and NN simplification

Multimedia Computing

  • Real Time 3D perception, mapping, reconstruction, and geometry interpretation
  • Eye-tracking devices and algorithms
  • Hand skeleton and multimodal human body pose estimation and tracking
  • Low power/complexity rendering systems
  • Lighting/illumination modelling
  • Multi-focal, near eye displays
  • High efficiency video coding techniques
  • Deep learning based image and video compression (intra and inter prediction, in-loop filters, transforms, entropy coding)
  • Deep learning based optimized video encoding
  • Perceptually optimized video coding
  • Image and video quality assessment
  • 6DoF video compression, Point Cloud compression

Processor Architecture and Implementation

  • Novel processor architectures, microarchitectures, extensions, and accelerators
  • Multimedia and gaming architectures (not limited to GPU, GPGPU, VLIW, DSP, etc.)
  • Novel architectures for artificial intelligence, edge training and inference
  • Security features of CPUs and accelerators at the instruction set, memory system, and SOC levels

Secure System Design

  • Isolation technologies: Virtualization, enclaves, and software sandboxing
  • Key management for IoT: Establishing trust between embedded devices
  • Machine learning model security: DRM for learning models
  • Protocol security: Analysis and verification of communication protocols
  • SoC security: Security of heterogeneous systems on chip
  • Software-based exploitation of hardware vulnerabilities: Micro-architectural attacks, side-channels, and associated countermeasures
  • User authentication: Biometric and behavioral authentication of users by mobile and embedded devices
  • Vulnerability detection: New tools and techniques for finding exploitable vulnerabilities in C software, with a focus on embedded systems

Semiconductor Test, Quality and Yield Learning

  • Defect-oriented testing and fault modeling in deep sub-micron process nodes
  • Applications of Data Analytics, Machine Learning and AI in Test
  • Test Challenges for 2.5D/3D Systems in Packages

Submission site opens: December 17, 2018

Application submission deadline: January 9, 2019 (10:00AM PST)

Selection announcement: January 22, 2019

Proposal submission deadline: February 12, 2019 (10:00AM PST)

Finalist presentations submission deadline: March 25, 2019

Finalist presentations: April 3 & 4, 2019

Winners’ announcement: May 29, 2019

QIF Winners’ Day: October 2019

2018 U.S. Winners

This year 70 proposals were selected from 174 abstracts submitted by teams from 20 QInF schools. Of the 30 finalists chosen (acceptance rate: 17.24%) we selected 8 winning teams (acceptance rate: 4.60%). Each winning team will be awarded a $100,000 fellowship and receive mentorship from Qualcomm engineers.

School

Students

Recommender(s)

Title

UCSD

Jiun-Ting Huang, Alankrita Bhatt

Young-Han Kim

Monte Carlo Decoding of Error-Correcting Codes

Stanford

Jiaming Song, Shengjia Zhao

Stefano Ermon

Safe Multi-Agent Imitation Learning for Self-Driving

UCSD

Hardik Sharma, Mohammad Ghasemzadeh

Hadi Esmaeilzadeh, Farinaz Koushanfar

Magneto: Hardware-Algorithm Co-design for Training at the Edge using MRAM

MIT

Davis Blalock, Jose Javier Gonzalez

John Guttag

Deep Learning Using Radically Less Time, Space, and Data

Georgia Tech

Fei Wang, Kyle Xu

Hua Wang, Justin Romberg

An Artificial-Intelligence (AI) Assisted Mm-Wave Multi-Band Doherty Transmitter with Rapid Mixed-Mode In-Field Performance Optimization and Digital Pre-Distortion Compensation

Caltech

Ehsan Abbasi, Fariborz Salehi

Babak Hassibi

Efficient Near ML Data Recovery in Massive MIMO

CMU

Dimitrios Stamoulis, Zhuo Chen

Diana Marculescu

Towards Efficient Hardware-Constrained Deep Learning

Stanford

Karen Leung, Sumeet Singh

Marco Pavone, Dorsa Sadigh

Interpretable Algorithms for Intent Inference and Decision-Making on the Road

 

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

May 14, 2018

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