Multi-Robot Systems with Decentralized Task Allocation

Read More

Multi-criteria Evolution of Neural Network Topologies for Autonomous Systems

Read More

Automated Selection of Surrogate Models or Supervised Learning Models (w/ continuous outputs)

Read More

Topology Optimization of Football Helmet Facemask for Concussion Mitigation

Read More

Swarm Robotics

Robotic systems, often working collaboratively as a team of multiple autonomous agents, are becoming valuable players in different real-world applications; these include search and…

Read More


In decision-support applications for autonomous systems, the architecture or topology of Artificial Neural Networks (ANN) is often user-prescribed, thereby leading to sub-optimal prediction models…

Read More

Transitioning UAVs

Multi-ability unmanned aerial vehicles have grown attention in the last decade. They also provide the advantage of vertical take-off and landing and forward flight…

Read More

To conceive, analyze and design complex systems, we investigate new approaches that are founded on a fundamental notion ofadaptation”. Adaptation is realized by bringing together nature inspired principles of computation, rigorous engineering design methods, and machine learning.

Fundamental areas of research in the ADAMS lab include:

  • Swarm Systems: swarm intelligence for distributed search, task allocation, optimization, and decentralized cyber-physical systems.
  • Evolutionary–Neural Algorithms: concurrent design of the morphological and intelligence architecture of autonomous systems; evolution of neural network topologies.
  • Physics-cognizant machine learning: physics-aware hybrid machine learning architectures for dynamic systems
  • Metamodeling and Multi-fidelity Optimization: automated selection and adaptive refinement of metamodels; multi-objective and mixed-integer optimization.


Major areas of application include:

  • Unmanned Aerial Vehicles (UAVs)
  • Swarm Robotics
  • Bio-inspired Flow Modulation 
  • Cyber Physical Systems 


      • Sep 2020: Payam Ghassemi, a PhD student at ADAMS Lab, successfully defended his PhD thesis.
      • Aug 2020: Payam Ghassemi received SEAS Dean’s Graduate Achievement Award from the University at Buffalo More
      • Jan 2020: Prof. Souma Chowdhury has been selected as Early Career Researcher of the Year Award 2019 at the University at Buffalo for his publications and significant research funding in swarm robotics, AI, and design optimization.

Chowdhury Early Career Researcher Award

        • Jan 2020: Our project of Human-augmented AI for Swarm robotics featured in Digital Trends
        • Aug 2019: NSF AI and Society funded our new research: “Cognitive-Behavior Model to Predict Human Reaction to Swarm AI Non-Compliance“. This research enables us to understand how human supervisors react to circumstantial or deliberate non-compliance by the swarms of robots, and how humans identify and attribute errors.
        • Aug 2019: Payam Ghassemi and Souma Chowdhury presented two research papers on swarm robotics in the 2nd IEEE MRS 2019.
        • Aug 2019: Payam Ghassemi received NSF travel awards to attend IEEE MRS 2019.

Payam MDO2019

    • June 2019: Payam Ghassemi won the best student paper award (3rd prize) in AIAA Aviation: Multidisciplinary Design Optimization 2019.
    • Mar 2019 Invited Talk by Souma Chowdhury, Spill Mapping with Drone Swarm, Remote Sensing and Field Data Collection session, Eighth Technology Workshop for Oil Spill Response in California, Feb 26 – March 1, 2019.

Most Recent Publications


ADAMS Lab is looking for exceptional graduate and undergraduate students who have the motivation to excel in the above areas of scholarly research. A successful student in these areas must have a solid background in mathematics, engineering, and computer programming. Good communication skills and previous research experience are a plus. For further information, click here, or contact Dr. Chowdhury: .