QIF 2020 India

Qualcomm Technologies, Inc. is inviting applications for the Qualcomm Innovation Fellowship India 2020 from undergraduate and postgraduate students in the Electrical Engineering and Computer Science (and related) departments at:

• Indian Institute of Science, Bangalore
• Indian Institute of Technology, BHU
• Indian Institute of Technology, Bombay
• Indian Institute of Technology, Delhi
• Indian Institute of Technology, Guwahati
• Indian Institute of Technology, Hyderabad
• Indian Institute of Technology, Kanpur
• Indian Institute of Technology, Kharagpur
• Indian Institute of Technology, Madras
• Indian Institute of Technology, Roorkee
• International Institute of Information Technology, Hyderabad
• Indian Statistical Institute, Kolkata

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 envelop tracker, embedded regulation)
• ASIC implementation methodology development for improved Performance, Power, Area, Yield. On-die power grid analysis and optimization, dynamic and static power optimizations, silicon-driven static timing analysis, design optimization for yield improvement

Advances in Communication Techniques & Theory

• Reliable low latency communications for low unlicensed and mmWave spectrum
• Machine learning designs for wireless communications systems and algorithms
• Advanced communication and positioning techniques for licensed and unlicensed spectrum
• Vehicle-vehicle and vehicle-pedestrian communications design
• Low energy networks (Bluetooth LE, 802.15.4, Zigbee, Wi-Fi, etc.)
• Low power signal-processing algorithms for mmW massive-MIMO communication systems
• Advanced low power HW/FW/SW modem implementation approaches
• New signal-processing techniques and use-cases using RF sensing (wireless channel capture)
• Iterative detection and decoding algorithms

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
• Deep generative modeling and unsupervised learning
• Bayesian deep learning and uncertainty estimation
• Federated learning and quantum machine learning

Multimedia Computing

• Real Time 3D perception, mapping, reconstruction, scene understanding and geometry interpretation
• Real time 3D graphics rendering
• 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
• Machine learning CAD for VLSI HW design

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
• Solutions for data provenance, privacy and security

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

• Call for Proposal opens: January 14, 2020
• Proposal submission deadline: March 9, 2020 (23:59h India time)
• Proposal presentation by selected ideas (Venue: TBA): First half of May, 2020
• Winning team announcements: Second half of May, 2020
• QIF India Day: June, 2020
• Project presentations (Venue: TBA): May 2021
• Funding renewal announcement: May 2021

Dates subject to change