QIF 2020 India

2020 India Program Details

Qualcomm Technologies, Inc. proudly announces the launch of Qualcomm Innovation Fellowship 2020-2021 program for selected Indian universities. Each winning team (up to 2 students and 1 faculty) will receive a financial award for the academic year 2020-21, plus assignment of a Qualcomm researcher(s) as a mentor to facilitate close interaction with Qualcomm.

The Program is sponsored by Qualcomm Technologies, Inc. and Qualcomm Technology Licensing headquartered at 5775 Morehouse Drive, San Diego, CA 92121 (“Sponsor”).

Qualcomm Research is a division of Qualcomm Technologies, Inc.

Winners

Application Process

Participating Universities

Areas of Interest

Timeline

University	Student(s)	Recommendor(s)	Innovation Title
IIT – Kanpur	Dhanajit Brahma	Piyush Rai	Continual Semi-Supervised Multi-Objective Learning
IIT – Madras	Salman Siddique Khan	Kaushik Mitra	Data-driven Reconstruction and Joint Design of Optics for Lensless Cameras
IISc – Bangalore	V. Arvind Rameshwar, Aashish Tolambiya	Navin Kashyap	Designing Capacity-Achieving Codes for Channels With Memory Using Reinforcement Learning
IISc – Bangalore	Anjana Mahesh	B Sundar Rajan	Embedded Index Coding for D2D Communication
IIT – Madras	Lakshmy A V	Chester Rebeiro	Instant Side-Channel Vulnerability Estimation of Digital Designs
IIIT – Hyderabad	Unni Krishnan R Nair, Nivedita Rufus	K Madhava Krishna, Vineet Gandhi	Language-Based Navigation with Object Referenced Spatiotemporal Constraints in Autonomous Driving
IISc – Bangalore	Kartheek Kumar Reddy Nareddy	Chandra Sekhar Seelamantula	On the Representation Capability of Binary Neural Networks
IISc – Bangalore	Jogendra Nath Kundu	R. Venkatesh Babu	Self-Supervised Human Mesh Recovery From In-the-wild Videos
IIT – Kharagpur	Manashi Chakraborty, Sohan Rudra	Prabir Kumar Biswas, Pabitra Mitra	Texture Aware CNN for End-to-End Trainable Iris Recognition System
IIT – Bombay	Ganpat Parulekar, Sandeep Goyal	Shalabh Gupta	True Full-Duplex High Speed IOs/Interconnects for Smartphones and AI/ML Hardware
IIT – Kanpur	Mohmad Aasif Bhat, Anteshwar Chimadge	Imon Mondal	Wideband Delay Lines with Reduced Insertion Loss for Beamforming at mm-wave Frequencies

The submission deadline has been extended to March 9, 2020 (23:59h India time). Template is provided on this website for proposal submission by the teams.

The team can be comprised of up to 2 students, wherein at least one student member of the team has to be enrolled as a Masters (MS / M.Tech.), Dual degree (B.Tech + M.Tech/MS) or PhD student in the Electrical Engineering or Computer Science department (or related department) for the entire 2020-21 academic year. In case of dual degree, the student should have completed his/her bachelor’s degree requirements by the end of 2019-2020 academic year. A second student team member is optional and may even be a final year under-graduate. Each student on a team is an “Entrant” and needs to be enrolled as a full- time student in one of the participating institutes. Also, each team must have one or more faculty advisors supporting the proposal and all the team members, and the faculty advisor(s) should be from the same institute. The Masters or PhD entrants from each team may elect to choose ideas from their on-going or planned research and/or thesis projects in accordance with their university policies.

Each team shall submit an innovation proposal (download the template) that must include the following:

Three page innovation proposal (plus optional page for bibliography/references)
- Introduction and problem definition
- Innovation proposal and relation to the state of the art
- The one-year horizon of the project, even if the proposal is a multi-year project
Letter from one or more faculty members recommending the innovation including:
- Why the proposal is innovative
- Why the proposal is important
- Why the current team is likely to succeed in their proposal
Each student's Curriculum Vitae
Signed agreement form by the team members (acknowledging the official rules of Qualcomm Innovation Fellowship program in India). Download the official rules, and sign at the marked location in the rules document thus agreeing to the competition rules.

STRICT ADHERENCE TO THE SUBMISSION TEMPLATE INCLUDING FONT SIZE, PAGE LIMIT ETC. IS MANDATORY. SUBMISSIONS SHOULD BE IN A ZIP FILE. THE SUBMISSION SHOULD BE MADE THROUGH AN ONLINE SUBMISSION PORTAL, FOR CONSIDERATION IN THE QIF 2020 INDIA PROGRAM. THE ONLINE SUBMISSION PORTAL WILL BEGIN ACCEPTING SUBMISSIONS FROM JANUARY 14, 2020.

See FAQs for more details.

Winners will be selected through a multi-phase process:

Idea selection for presentation: Applications must be submitted online by the specified deadline (see Timeline tab). All proposals will be reviewed internally by a team of Qualcomm researchers. A subset of teams will be selected as Program Finalists and notified according to the timelines mentioned in the Timelines tab of this website. Selected (“finalist”) teams will be invited to a Sponsor facility to make a presentation of the research proposal described in their Application to a judging panel.
Final proposals selection: Each selected (“finalist”) team must prepare a presentation for the judges. Presentations must be in PowerPoint or PDF format. Templates for this presentation will be provided. The presentation generally include:

The proposal idea

The differentiating factors from state of the art

The execution plan / strength of the team

Nine winning teams will be chosen from this pool of selected teams after they present to the judging panel.

The winning teams will be invited to a Sponsor facility for presenting the proposal details.

All QIF-related information will be announced on this webpage. Please check back regularly for updates.

Faculty & Mentor

In addition to the faculty advisor(s) guiding the fellowship research, Qualcomm Technologies, Inc. will help with assigning mentor(s) to facilitate periodic interaction opportunities with Qualcomm.

Funding Renewal Opportunity

The QIF India 2020 winning proposals will be re-evaluated in Apr/May 2021 in the form of a project presentation, with one team being granted a funding renewal from Qualcomm Technologies, Inc.

More Info?

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

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

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

Finalists

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