Aashis Luitel contact →
Aurora, Colorado

Aashis
Luitel

Associate Professor of Artificial Intelligence, University of the Cumberlands. Lead Technical Program Manager, N-able Technologies. Product and program leadership on Microsoft Security Copilot, the industry’s first generative AI security platform.

Trustworthy AI is not a principle an organization publishes. It is a property someone outside the room can verify. My work sits where ethical commitments become architecture decisions, and where those decisions become evidence.

Current scope 2026
focus
AI ethics, trust, and assurance engineering
teaching
PhD and Executive Master’s in Artificial Intelligence
practice
Public sector security and AI governance programs
built
Responsible AI, privacy, and compliance foundations for Security Copilot
service
U.S. Navy, active duty, deployed overseas
AT

Teaching

Faculty in the PhD and Executive Master’s programs in Artificial Intelligence at the University of the Cumberlands, where I designed the doctoral curriculum in AI ethics and responsible AI and advise dissertation work in AI governance. I also teach in the School of Professional Studies at Wake Forest University.

Students in these courses do not study ethics as a reading list. They argue real deployments: model bias with a deadline attached, transparency traded against privacy, automated decisions nobody wants to own. The same arguments I sat in at Microsoft.

Fall 2026
PhDAI 832 Ethics in Responsible AI doctoral
Also taught
—Ethics in AI
—Introduction to Responsible AI
—Transforming Business with AI
PM

Practice

Microsoft Security Copilot

Product and program leadership · Responsible AI, privacy, compliance, sovereign cloud

Security Copilot was the first generative AI security product to reach market, which meant no precedent existed for how trust, safety, and ethics should be built into one. I worked across engineering, legal, and policy to turn Responsible AI principles into practices an auditor could examine, and aligned the platform to SOC 2, HIPAA, ISO 42001, and FedRAMP controls.

The durable lesson was treating regulatory expectation as a design input rather than a gate at the end. That reordering changed the architecture, not just the paperwork.

N-able Technologies

Lead Technical Program Manager, Public Sector Security

Leads security and compliance programs for public-sector and defense-adjacent platforms, including FedRAMP Moderate and CMMC 2.0 Level 2, from control implementation through assessment readiness.

AU

Recent commentary

Clock is ticking on Colorado’s new AI rules Colorado Politics · Jul 29, 2026 Why AI-built tools are threatening SaaS vendor renewals InformationWeek · Jul 2026 Bridging AI and ethics: a vision for trustworthy innovation University of the Cumberlands · Jun 4, 2026 Addressing the CMMC evidence gap Federal News Network · May 2026 Colorado’s small defense suppliers are about to disappear The Colorado Sun · May 14, 2026 Between Systems essays · ongoing
CA

Credentials

  • Doctor of Engineering, The George Washington University. Dissertation: a framework for modeling data breach risk using machine learning models for high-dimensional panel data.
  • Master of Public Administration, Harvard Kennedy School.
  • CMMC Registered Practitioner, Cyber AB.
PS

Before this

U.S. Navy veteran. Active duty operations, deployed overseas, in assignments where documentation and verification were the condition for anything being trusted to run.

Earlier, a career in Nepali broadcast and print journalism at Nepal Television and Kantipur Daily. Those two are less unrelated than they look. Both teach the same discipline from opposite directions: a claim is worth whatever you can show behind it.