About Me

I hold a Ph.D. in Electrical Engineering with a focus on AI and Machine Learning from UC Santa Cruz and a B.S. in Electrical Engineering and Computer Science from UC Berkeley. My career began at Intel as a Design Automation Engineer, where I specialized in transistor-level optimization and automation tools. This experience led me to become one of Intel's early data scientists.

At UC Santa Cruz, I founded SEADS (Smart Energy Disaggregation System) and led a community of developers to advance AI algorithms for energy monitoring. My work earned NSF funding and I mentored over 200 students as a faculty-researcher.

As a Senior Manager at Accenture, I delivered high-impact projects, including a healthcare robotic platform and a cloud-based IoT asset tracking system, achieving a 25% cost reduction for clients and earning the Accenture Global Innovation Award. I managed cross-functional teams and drove significant revenue growth.

Currently, as CTO at AI2X, I focus on integrating General AI into business operations, increasing operational efficiency by 30% and reducing manual workloads by 40%. My expertise spans AI, ML, cloud technologies, and leadership.

I am passionate about continuous learning and innovation, always ready to embrace new challenges in the ever-evolving tech landscape.

Highlights:

  • Ph.D. in Electrical Engineering, AI, and Machine Learning from UC Santa Cruz
  • B.S. in Electrical Engineering and Computer Science from UC Berkeley
  • Ranked 1st out of 1000 hackers in TechCrunch
  • Accenture Global Innovation Award for the Autonomous Trace Project
  • Certified Scrum Master, Technology Architect Certificate, Data Science, and ML Certificates from Stanford

Professional Experience:

SEADS (Intelligent IoT for Energy Monitoring)


SEADS BlockChain Integration


SEADS GitHub



  • Status and challenges of residential and industrial non-intrusive load monitoring
    A Adabi, P Mantey, E Holmegaard, MB Kjaergaard
  • SEADS: A modifiable platform for real time monitoring of residential appliance energy consumption
    A Adabi, P Manovi, P Mantey
  • PhD Dissertation: Economical Real-Time Energy Management For Microgrids Via Nilm And With User Decision Support
    A Adabi
  • M.S. Thesis Toward a Social Graph Recommendation Algorithm: Do We Trust Our Friends in Movie Recommendations?
    A Adabi, L de Alfaro
  • ElbowQuad: Thrust Vectoring Quadcopter
    Trieste Devlin, Ryan Dickerhoff, Kevin Durney, Aidan Forrest, Pattawong Pansodtee, Ali Adabi, Mircea Teodorescu
  • Cost-effective instrumentation via NILM to support a residential energy management system
    A Adabi, P Manovi, P Mantey
Date Talk Location
Winter 2018 Deep Learning AI applications in IoT and Grid Optimization Course UCSC
Spring 2018 IoT Case Studies in Power System Advanced topics in Controls UCSC
Fall 2017 SEADS Cross Sympossium UCSC
Fall 2014 Grid Operating system California Public Utility Commission
Autonomous Trace Platform
TechCrunch Disrupt Award
UCSC Competition Award

NSF iCorps Award