Mehran Rostamnia

PhD Candidate · Robotics Software Engineering

Building adaptive robotic systems for a changing world.

I study how robots and their digital counterparts can remain effective when missions, environments, and design-time assumptions change.

Explore my research Get in touch
GSSI L'Aquila, Italy
2023—Now PhD in Computer Science
Focus Adaptive robotics
Portrait of Mehran Rostamnia
Researching at Gran Sasso Science Institute
Behavior Trees
Digital Twins
Self-adaptation
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01 · About

Software engineering for robots that must outlive their assumptions.

I am a PhD candidate in Computer Science at the Gran Sasso Science Institute, working at the intersection of robotics and software engineering.

My research asks a practical question: how can long-living robots keep their behavior, knowledge, and digital representations aligned as the world changes? I investigate adaptive behavior architectures—especially Behavior Trees—and evolving Digital Twins, with an emphasis on uncertainty, runtime change, traceability, and assurance.

I work with Prof. Patrizio Pelliccione and collaborate with researchers across robotics and software engineering.

Robotics Behavior Trees Digital Twins Self-Adaptive Systems Mission Specification

02 · Research

Three connected research directions.

From runtime behavior to system-level evolution.

01

Adaptive robot behavior

Understanding when classical Behavior Trees are sufficient, where they reach their boundary, and how generation, extension, evolution, and refinement mechanisms can help.

  • Behavior Trees
  • Runtime adaptation
  • Uncertainty
02

Evolving Digital Twins

Engineering Digital Twins that co-evolve with physical systems, manage semantic drift, and preserve consistency across models, metamodels, ontologies, and ecosystems.

  • Semantic drift
  • Co-evolution
  • Smart systems
03

Engineering autonomy

Applying software architecture, requirements engineering, and self-adaptive-systems principles to make autonomous robots understandable, resilient, and safe to evolve.

  • Architecture
  • Mission specification
  • Assurance

A recurring research question

Where should adaptation live?

  1. 1DetectWhat changed?
  2. 2DecideWho responds?
  3. 3ChangeWhat may evolve?
  4. 4AssureWhat evidence is enough?

Current work

Adaptation Needs in Robotic Systems

A study assessing what robotic adaptation requires, where classical Behavior Trees help or fall short, and how enhanced BT approaches address the remaining needs.

6 adaptation-need families 4 BT technique families Literature + practitioner evidence

03 · Publications

Selected publications.

View Google Scholar
2026 Journal article

Digital Twin Models for Space Robotics: Objectives, Applications, and Challenges

Array · Elsevier

2025 Workshop paper

Towards Adaptable and Uncertainty-Aware Behavior Trees

IEEE/ACM International Workshop on Robotics Software Engineering

2021 Journal article

An Efficient Path-Based Approach for Influence Maximization in Social Networks

Expert Systems with Applications · Elsevier

2019 Conference paper

Vertex Cover Preprocessing for Influence Maximization Algorithms

Conference on Knowledge Based Engineering and Innovation

04 · Journey

An academic path shaped by software, systems, and people.

  1. Nov 2023—Now

    Doctoral research

    PhD Candidate in Computer Science

    Gran Sasso Science Institute · L'Aquila, Italy

    Robotics software engineering, adaptive systems, Digital Twins, and mission specification.

  2. 2020—2022

    Professional experience

    Information & Communication Technology Teacher

    Ministry of Education · Iran

  3. 2019

    Education

    MSc in Computer Science

    Shahid Rajaee Teacher Training University

05 · Contact

Let’s discuss adaptive robotics.

I am always glad to exchange ideas about Behavior Trees, evolving Digital Twins, self-adaptive systems, and research collaborations.

Google ScholarPublications & citations ORCID0009-0002-3278-0200 GitHub@mehranrostamnia LinkedInConnect professionally ResearchGateResearch profile