Resume
Adwait Dongare
| Palo Alto, CA | email: FirstNameAbbreviated+n+LastName@gmail.com |
| adwait.dongare.com |
Professional Summary
Technical leader with 5+ years shipping end-to-end systems deployed on 1.5B+ devices including ML pipelines, wireless protocols, and sensor fusion architectures. Architect solutions spanning training infrastructure design, model architecture decisions, synthesis-based data generation, and on-device deployment under strict power/latency/privacy constraints. Lead cross-functional engineering teams (5-10 engineers) through problem formulation, strategic system design, and production deployment. PhD in ECE from CMU with expertise in distributed optimization and multi-sensor fusion. 3 granted US patents, best paper awards (IPSN, RTAS), DARPA SubT finalist (4th overall).
Research Interests
Building foundation models and scalable training infrastructure for physical domains beyond language—3D perception and manipulation, contact-rich tasks, deformable objects, and multi-modal sensor fusion. Focus on designing simulation-based training systems that generate diverse, physically-realistic scenarios at scale. Bridging sim-to-real gap for physical interactions (contact dynamics, material properties) while leveraging production experience shipping ML under strict compute/power/privacy constraints to inform foundation model architecture and training infrastructure design.
Technical Skills
Programming & Development: Languages (Python, C/C++, Objective-C, Swift), Specializations (Embedded, Firmware, iOS/macOS, Low-power, Real-time, Secure ML deployment)
Machine Learning & Computer Vision: Deep learning architectures (CNNs, hybrid models, RLHF), Synthetic data generation and training pipelines, On-device ML deployment and optimization, Vision-based sensing and 3D object tracking, Multi-modal sensor fusion, Human factors research for ML problem formulation
ML Frameworks & Tools: PyTorch, CoreML, On-device inference optimization, Privacy-preserving ML systems, LLM APIs and agent frameworks, AI-assisted development tools
Wireless Technologies & Protocols: Radio technologies (UWB, BLE, WiFi, LoRa), Signal processing techniques (Coherent Combining, Clock Synchronization, Time-of-Flight), ML for RF performance optimization
Simulation & 3D Tools: Physics simulation platforms (MuJoCo), CAD software (Fusion 360, FreeCAD, OpenSCAD), Circuit design (KiCad, EAGLE), 3D rendering and scene generation (Blender, Unreal Engine), Simulation-based training data generation
Research & Innovation: 3 granted US patents, Best paper awards (IPSN 2018, RTAS 2017), Distributed systems architecture, Research-to-product translation
Work Experience
Apple: Cupertino, CA
Senior Software Developer - 2023 - Present
Software Developer - 2020 - 2023
Technical leader for ML-driven proximity technologies using vision and wireless sensors, deployed on over 1.5 billion devices.
Leadership in Applied ML:
- Implemented multi-model scheduling, memory optimization, and trusted execution features for privacy-preserving ML deployment on specialized Apple hardware
- Led vision ML team (5-10 engineers) developing gesture detection and 3D object perception; architected synthesis-based training pipeline generating millions of scenarios with perfect ground truth, now in production
- Designed hybrid CNN for HomePod RF optimization combining physics-informed features with learned representations, unblocking product launch
- Led team adoption of generative AI workflows, guiding development of automated debugging agents and log analysis tools
Systems and Wireless Innovation:
- Technical lead for U2 UWB chip software bring-up; designed and implemented software system managing chip lifecycle, power states, and resource allocation across iOS and watchOS under strict power budgets and latency requirements
- Implemented deep sleep software architecture for U2-equipped Apple Watch devices, contributing to significant battery life improvements enabling all-day battery life with UWB features active
- Architected multi-modal sensor fusion system for in-development Apple product combining vision, motion and wireless signals (UWB, BLE, WiFi) for proximity detection and device localization.
- Technical lead for UWB localization and wireless-vision sensor fusion systems, developing algorithms and software infrastructure for device positioning across product line. Shipped content handoff feature between iPhones and HomePods.
Apple: Cupertino, CA
Software Engineering Internship - Summer 2019
Prototyped scalable UWB localization algorithms; developed algorithms that evolved into two granted patents for UWB synchronization and localization. This work later evolved into a patent on localization.
Texas Instruments: Dallas, TX
Design Engineering Internship - Summer 2017
Benchmarked new oscillator technology for microcontrollers with integrated radios. Helped identify new use-cases and product areas.
Apple: Cupertino, CA
Software Engineering Internship - Summer 2015
Developed system firmware for low-power always-on processors on iOS and watchOS devices.
Education
Carnegie Mellon University: Pittsburgh, PA
PhD in Electrical and Computer Engineering - 2014-2020
Thesis: A distributed reception architecture for low-power wide-area networks. Advised by Prof. Anthony Rowe
Relevant Coursework: Wireless Communications, Graduate Artificial Intelligence (game theory, planning, neural networks), Introduction to Machine Learning (kernel methods, Bayesian inference, neural networks), Real-Time Embedded Systems
Indian Institute of Technology Bombay: Mumbai, India
BTech in Engineering Physics with minor in Electrical Engineering - 2010-2014
Stanford University (Professional Education)
Reinforcement Learning - Completed post-PhD - Fall 2025
Research Highlights
Machine Learning Deployment: Led development of production ML systems on 1.5B+ devices including hybrid CNNs, gesture detection models, and synthesis-based training pipelines; grounded ML problem formulation in human factors studies conducted in partnership with research teams
Patents: 3 granted US patents in UWB synchronization, localization, and wireless networking (2020-2023)
Publications: 6 peer-reviewed conference papers including best paper award at IPSN 2018 for “Charm: Exploiting Geographical Diversity Through Coherent Combining in Low-Power Wide-Area Networks”
Awards:
- Best Paper Award - IPSN 2018, Porto, Portugal
- Best Presentation Award - RTAS 2017, Pittsburgh, Pennsylvania
- Hsu Chang Memorial Fellowship - Carnegie Mellon University (2016-2017)
Research Experience
WiSeLab, Carnegie Mellon University: Pittsburgh, Pennsylvania
PhD Candidate - Advisor: Prof Anthony Rowe - 2014 - 2020
Research on distributed signal processing, optimization, and coherent combining for low-power wide-area networks; developed Charm distributed reception system and Pulsar wireless synchronization framework.
DARPA Subterranean Challenge
Explorer Team Member - CMU-Oregon State - 2018 – 2020
Team placed 4th overall, won tunnel circuit and runners-up in urban circuit; contributed wireless communication systems for multi-robot coordination and localization in GPS-denied underground environments.
Detailed Publications
Patents
Techniques for synchronizing ultra-wideband communications
US Patent 17647822 - March 2023
Dongare, A., Brumley, R., Golshan, R.
Techniques for localizing an electronic device
US Patent 17397676 - October 2022
Dongare, A., Brumley, R., Golshan, R.
Methods, systems, and articles of manufacture for joint decoding of packets in wireless networks using chirp spread-spectrum modulation
US Patent 10735047 - August 2020
Dongare, A., Narayanan, R., Gadre, A., Luong, A., Balanuta, A., Kumar, S., Iannucci, B., Rowe, A.
Conferences and Workshops
Resilient and modular subterranean exploration with a team of roving and flying robots
Field Robotics - Volume 2, 2022
Scherer S. et al.
Sketchlib: Enabling efficient sketch-based monitoring on programmable switches
USENIX Symposium on Networked Systems Design and Implementation (NSDI) - 2022, Renton, Washington
Namkung, H. et al.
TagFi: Locating Ultra-Low Power WiFi Tags Using Unmodified WiFi Infrastructure
ACM Proceedings on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT/Ubicomp) - 2021
Soltanaghaei, E., Dongare, A., Prabhakara, A., Kumar, S., Rowe, A., Whitehouse, K.
All that GLITTERs: Low-Power Spoof-Resilient Optical Markers for Augmented Reality
ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) - 2020
Sharma, R., Dongare, A., Miller, J., Wilkerson, N., Cohen, D., Sekar, V., Dutta, P., Rowe, A.
Charm: Exploiting Geographical Diversity Through Coherent Combining for Low-Power Wide-Area Networks
ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) - 2018, Porto, Portugal
Dongare, A., Narayanan, R., Gadre, A., Luong, A., Balanuta, A., Kumar, S., Iannucci, B., Rowe, A.
Pulsar: Wireless Propagation-Aware Clock Synchronization
IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS) - 2017, Pittsburgh, Pennsylvania
Dongare, A., Lazik, P., Rajagopal, N., Rowe, A.
OpenChirp: A Low-Power Wide-Area Networking Architecture | Workshop paper
IEEE International Workshop on Smart Edge Computing and Networking (SmartEdge) - 2017, Big Island, Hawaii
Dongare, A., Hesling, C., Bhatia, K., Balanuta, A., Pereira, R. L., Iannucci, B., Rowe, A.
Timeline: An Operating System Abstraction for Time-Aware Applications
IEEE Real-Time Systems Symposium (RTSS) - 2016, Porto, Portugal
Anwar, F., D’souza, S., Symington, A., Dongare, A., Rajkumar, R., Rowe, A., Srivastava, M.
Demos
The Openchirp Low-Power Wide-Area Network and Ecosystem
ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), 2018, Porto, Portugal
Dongare, A., Luong, A., Balanuta, A., Hesling, C., Bhatia, K., Iannucci, B, Kumar, S., Rowe, A.
Propagation-Aware Time Synchronization for Indoor Applications
ACM Conference on Embedded Network Sensor Systems (SenSys), 2016, Stanford, California
Dongare, A., Rowe, A.