David Mendonça
	Email: mendod@rpi.edu Phone: (518) 276-4222 Fax: (518) 276-8227 Postal Address:     Industrial and Systems Engineering     Rensselaer Polytechnic Institute     CII 5111     110 8th St.     Troy, NY 12180 Fall 2010 Office Hours: TBD

Curriculum vitae (reasonably current as of March 2013). Email me for copies of papers: mendod@rpi.edu.

Openings for PhD Students
I am currently looking for PhD students, particularly those with undergraduate- and/or master's-level training in cognitive science/cognitive engineering, computer science (including HCI), or industrial engineering.

Current Student Researchers
Doctoral: James Brooks
Undergraduate: Jane Braun, Gabriele Cruz, Caroline Hsia, Maira Kagohara, Christian Pedrosa, Zal Mirza (SUNY)

Current Projects
Network improvisation in post-disaster debris removal operations (NSF CMMI 1313589). This work is investigating the relationship between improvisation and performance for the post-Sandy debris removal mission in New York State.

Improvisation in response to extreme events (NSF CAREER CMS 0449582). This work examines team decision processes in highly non-routine situations, based mainly on observational studies with emergency response personnel.

Synthetic environments for examing organizational resilience. This work employs advanced information technologies for observing and supporting teams undertaking post-disaster infrastructure restoration in a simulated setting. This is work being done at RPI's EMPAC facility with Barb Cutler (RPI CS Dept.) and Al Wallace (RPI ISE Dept.)

Cognition in Jazz Improvisation (with Mark Pfaff of IUPUI). Building on prior work, we are taking an in-depth look at planning and idea generation processes in small jazz groups.

Research Interests
My research centers on the study of the cognitive processes that underlie human decision making in the management of critical infrastructure systems with a focus on understanding and supporting decision making in high consequence, non-routine, time-pressured situations. I use laboratory and field-based methods to collect data on the physical state of systems in the built environment, and the psychological state of humans operating in relation to those systems. This work has led to the development of statistical and computational models to explain decision maker behavior in the field, and has translated these results into implications for practice and policy. I have pioneered new technologies providing cognitive support in solving sequential multi-criteria decisions for these constituents and developed novel statistical models that have explained variability in cognition, behavior and communication among individuals and collectives in the hours following disruptive events.

Teaching
Course Offering: Fall (annually)
Human Performance Modeling and Support: Applications in Competitive Sports (ISYE-4961)
This course introduces methods, tools and technologies for describing human performance via various types of models, and supporting this performance via tools and advanced technologies. The course is hands-on, involving student projects that investigate human performance in challenging domains (e.g., competitive sports), as well as direct engagement with technology. A short promo on the course is here.