Current Research

Feedback Control of Music and Light, Virtual Reality, for Mental Health:

1. Challenges: Stress reduction, mood disorders (depression, bipolar illness), attention (ADHD).
2. Mathematics/computational: Mathematical modeling of mood disorders, mindfulness, attention; computational analysis, model validation. Feedback control and optimization methods. Stability analysis.
3. Sensors: EEG, PPG/ECG, and heart rate, heart rate variability (HRV), HR, and acceleration signals.
4. Actuators: Auto-generation of music and video.
5. Technology goals: Apps/web sites and bio-signal driven virtual reality and psychoeducation treatments, integration with social supports network.

Humanitarian Engineering:

Other research problems, given in the Humanitarian Engineering book. Three samples are:

1. Community participation: Models and analysis, cooperation perspective.
2. Cooperative Management of Community Technology: control and optimization approaches, network, implementation.
3. Sustainable Cooperative Community Development: Models, measures of development, computational analysis of the impact of technology on development over a network.

Stable Optimal Cooperation on a Network:

The theme for how we approach problems is via social/cooperative principles: Coordinated motion for animal and robot swarms over networks (agents), optimal social foraging (honeybees, group search), social/group choice (speed-accuracy tradeoff in honeybees; swarm cognition; and performance in choice discrimination, distractor avoidance, and individual-level irrationality filtering to achieve better swarm-level performance), cooperative allocation over networks (social foraging with optimal distributions, fast/accurate redistributions, and open-monitoring vs. focus/exploit trade-offs; computer networks; group/agent distributions for tasks; and sensing, search, patrol, and surveilance; distributed temperature and smart lights regulation), distributed synchronization (fire flies, sychronized swarms), cooperative task scheduling and sharing, coordinated attention (stable focus/re-focus), decentralized learning (inter-agent space regulation for autonomous agent groups), cooperative point pursuit in an electromechanical arcade, distributed assignment/concensus over a network (coordinated decisions on who does what and when), social dilemmas on task completion (participate or not on a community development project), collective optimization (bacterial foraging) and its use in learning, immunity-based learning, distributed evolution of decision-makers (robust controller design over the internet of things), network topology evolution from optimal allocations, and intelligent/autonomous control functional architectures. Principles for these, such as (i) kin (family), mutualism, direct reciprocity, indirect reciprocity, spatial, multilevel, etc.; and (ii) social cognition incorporating interaction rules, planning, attention, learning, evolution, and foraging (see biomimicry book). Courses taught include those listed at the above link, and ECE 7858 Intelligent Control. Fieldwork has been done in biology (e.g., the honey bee social choice problem), via collaborators, and in engineering in our Distributed Dynamical Systems Laboratory. See publications, books, and directions.

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