Resume
Adwait Dongare
| Palo Alto, CA | email: FirstNameAbbreviated+n+LastName@gmail.com |
Multi-modal sensing systems engineer — vision, wireless, and motion sensing for spatial computing running on 1.5B+ devices. PhD in ECE from CMU, 3 patents. Interested in physical AI where spatial sensing grounds models in the real world.
Education
Carnegie Mellon University: Pittsburgh, PA - PhD in Electrical and Computer Engineering, 2014-2020
Thesis: Distributed reception architecture for low-power wide-area networking
Advisor: Prof. Anthony Rowe
Research focused on multi-node coordination, real-time systems, and physical layer algorithms.
Indian Institute of Technology Bombay: Mumbai, India - BTech in Engineering Physics with minor in Electrical Engineering, 2010-2014
Stanford University (Professional Education) - Reinforcement Learning, Fall 2025
Work Experience
Apple: Cupertino, CA
Senior Software Developer - 2023 - Present | Software Developer - 2020 - 2023
- Architected real-time software stack for ultra-wideband spatial sensing chip, managing hardware interfaces, power optimization, and multi-device coordination. Running on 1.5B+ Apple devices
- Built production ML infrastructure for edge deployment with focus on multi-model scheduling, memory optimization, and privacy-preserving execution under strict power/latency constraints
- Led a team of 8 engineers to build a 3D spatial understanding feature using vision + wireless + motion sensors; built a physics-based synthetic data pipeline to generate training data at scale
- Developed physics-informed ML models for ultra-wideband sensing, combining learned representations with wireless signal propagation models. Essential work that enabled productization and launch of the Apple HomePods.
Software Engineering Internship - Summer 2019
Prototyped distributed UWB localization algorithms that evolved into production wireless sensing systems and one granted patent.
Software Engineering Internship - Summer 2015
Developed system firmware for low-power always-on processors on iOS and watchOS devices.
Texas Instruments: Dallas, TX
Design Engineering Internship - Summer 2017
Benchmarked new oscillator technology for microcontrollers with integrated radios; identified novel use-cases and productization strategies for emerging embedded wireless applications.
Technical Skills
Systems Programming & Real-time Development: Languages (Python, C/C++, Objective-C, Swift), Specializations (Embedded, Firmware, iOS/macOS, Low-power, Real-time, Secure ML deployment)
Wireless Sensing & Spatial Intelligence: Radio technologies (UWB, BLE, WiFi, LoRa), Signal processing techniques (Coherent Combining, Clock Synchronization), ML for RF optimization
Machine Learning & Multi-Modal Perception: Reinforcement Learning, TinyML, Synthetic data generation and training pipelines, On-device ML deployment, Privacy-preserving ML systems, Multi-modal sensor fusion, RLHF, Human factors research
ML Frameworks & Tools: PyTorch, CoreML, LLM APIs and agents
Simulation & 3D Tools: Physics simulation (MuJoCo), CAD (Fusion 360, FreeCAD, OpenSCAD), 3D rendering (Blender, Unreal Engine)
Research & Awards
Patents: 3 granted US patents in spatial sensing, multi-device localization, and wireless coordination systems (2020-2023)
Publications: 7 peer-reviewed papers in real-time systems, embedded sensing, and wireless networks https://scholar.google.com/citations?user=Bzc429AAAAAJ
Select Awards: Best Paper (IPSN 2018), Best Presentation (RTAS 2017), Hsu Chang Memorial Fellowship (CMU 2016-2017)
Competitions: DARPA Subterranean Challenge (autonomous robotics competition: 4th overall, 1st in tunnel circuit, runners-up in urban circuit)