Resume - Robotics
The PDF version can be generated from this source with
./resume/generate-pdf.sh robotics output.pdf.
Adwait Dongare
| Palo Alto, CA | email: FirstNameAbbreviated+n+LastName@gmail.com |
| **Robotics Perception & Sensor Fusion Lead | Spatial AI | Real-time Embedded ML** |
Engineering lead building perception and spatial sensing systems that connect sensors, ML, and real-time hardware. Shipped Apple multimodal sensing systems across vision, UWB/RF, wireless, and motion inputs to 1.5B+ devices; led teams building synthetic 3D data generation, on-device ML deployment, and low-power real-time sensor fusion. PhD in ECE from Carnegie Mellon with research in distributed sensing, wireless coordination, and real-time systems. DARPA Subterranean Challenge finalist team member with experience in GPS-denied autonomous robotics.
Work Experience
Apple: Cupertino, CA
Senior Software Developer - 2023 - Present | Software Developer - 2020 - 2023
- Led 5-10 engineers building multimodal spatial perception from vision, UWB/RF, BLE/Wi-Fi, and motion sensors for production Apple proximity and localization systems.
- Architected synthetic environment pipeline generating millions of physical scenarios for training and evaluating spatial perception models under controlled ground truth.
- Built edge ML infrastructure for multi-model scheduling, memory optimization, and privacy-preserving execution under strict power and latency constraints.
- Developed physics-informed RF sensing models that combine wireless propagation structure with learned representations for robust spatial understanding.
- Led real-time UWB chip software stack from hardware interfaces and power states to multi-device coordination, resource allocation, and cross-platform deployment.
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.
Carnegie Mellon University / DARPA Subterranean Challenge
Research Team Member - 2018 - 2020
- Contributed wireless communication and localization systems for a multi-robot team operating in GPS-denied underground environments.
- Member of CMU-Oregon State Explorer team that placed 4th overall, won the tunnel circuit, and finished runner-up in the urban circuit.
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 wireless applications.
Technical Skills
Robotics Perception: Multimodal sensor fusion, 3D spatial understanding, proximity sensing, localization, RF/UWB sensing, GPS-denied sensing systems
Machine Learning & Simulation: PyTorch, CoreML, TinyML, synthetic data generation, on-device inference, model optimization, MuJoCo, Blender, Unreal Engine
Real-time Systems: Python, C/C++, Objective-C, Swift, embedded systems, firmware, low-power software, hardware/software interfaces, latency-constrained deployment
Wireless & Distributed Sensing: UWB, BLE, Wi-Fi, LoRa, time-of-flight, coherent combining, clock synchronization, multi-device coordination
Hardware & 3D Tools: Fusion 360, FreeCAD, OpenSCAD, KiCad, EAGLE, CAD-to-simulation workflows
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 (Google Scholar)
Select Awards: Best Paper (IPSN 2018), Best Presentation (RTAS 2017), Hsu Chang Memorial Fellowship (CMU 2016-2017)
PhD Research: Distributed signal processing and optimization for wireless sensor networks, including multi-node coordination, real-time systems, and physical-layer algorithms.
Education
Carnegie Mellon University: Pittsburgh, PA - PhD in Electrical and Computer Engineering, 2014-2020
Thesis: Distributed signal processing and optimization for wireless sensor networks.
Advisor: Prof. Anthony Rowe
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