Resume - Perception Lead


The PDF version can be generated from this source with ./resume/generate-pdf.sh perception output.pdf.

Adwait Dongare

Palo Alto, CA email: FirstNameAbbreviated+n+LastName@gmail.com

**Perception Engineering Lead Sensor Fusion Spatial AI On-device ML**

Perception and sensor-fusion engineering lead with 5+ years shipping Apple spatial sensing systems to 1.5B+ devices. Experienced across vision, UWB/RF sensing, motion sensors, synthetic 3D data generation, TinyML, and real-time embedded deployment under power, latency, and privacy constraints. Led 5-10 engineers from ambiguous sensing problems to production perception systems. PhD in ECE from Carnegie Mellon; 3 granted US patents; best paper awards at IPSN and RTAS; DARPA SubT finalist.


Work Experience

Apple: Cupertino, CA

Senior Software Developer - 2023 - Present | Software Developer - 2020 - 2023

  • Led 5-10 engineers building multimodal perception systems from vision, UWB/RF, BLE/Wi-Fi, and motion sensors for production Apple spatial sensing features.
  • Architected synthetic 3D data pipeline generating millions of labeled physical scenarios for perception model training and sim-to-real evaluation.
  • Built on-device ML infrastructure for multi-model scheduling, memory optimization, and privacy-preserving execution under strict power and latency budgets.
  • Developed physics-informed RF perception models combining wireless propagation features with learned representations, enabling HomePod spatial sensing productization.
  • Led real-time UWB chip software stack across hardware interfaces, power states, resource allocation, and multi-device coordination for deployment across Apple platforms.

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 wireless applications.


Technical Skills

Perception & Sensor Fusion: Multimodal fusion, 3D spatial understanding, localization, proximity sensing, UWB/RF sensing, vision + wireless + motion pipelines

Machine Learning & Data: PyTorch, CoreML, TinyML, synthetic data generation, on-device inference, model optimization, privacy-preserving ML, human factors research

Systems & Deployment: Python, C/C++, Objective-C, Swift, embedded systems, real-time software, firmware, low-power optimization, hardware/software interfaces

Wireless Sensing: UWB, BLE, Wi-Fi, LoRa, time-of-flight, coherent combining, clock synchronization, ML for RF optimization

Simulation & 3D: MuJoCo, Blender, Unreal Engine, Fusion 360, FreeCAD, OpenSCAD, synthetic scene generation


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)

Research Experience: PhD research on distributed sensing and optimization at CMU WiSeLab; DARPA Subterranean Challenge finalist team (4th overall, 1st in tunnel circuit, runners-up in urban circuit)


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