Semiha Ergan
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Ph.D.
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Associate Department Chair, Civil and Urban Engineering
I am a faculty at NYU Tandon School of Engineering, Department of Civil and Urban Engineering with a courtesy appointment at the Department of Computer Science and Engineering. I am also an associated faculty member at Center for Urban Science and Progress (CUSP). Prior to joining NYU, I was a research faculty at Carnegie Mellon University. I received my Ph.D. at Carnegie Mellon University.
Experience
Carnegie Mellon University
Visiting Assistant Professor
From: October 2010 to July 2012
Carnegie Mellon University
Assistant Research Professor
From: July 2012 to August 2014
Affiliations
Assistant Professor, Computer Science and Engineering, NYU (courtesy)
Assistant Professor, Center for Science and Progress, NYU (associated)
Adjunct Professor, Carnegie Mellon University, Civil and Urban Engineering
Associate Professor of Civil Engineering, Turkey, Higher Education Council.
Awards
DARPA Young Faculty Award (2015)
Berkman Faculty Award, Carnegie Mellon University (2013)
Outstanding Teaching Assistant Award, Carnegie Mellon University (2007)
Winner of Association for Advancement of Cost Engineering (AACE) Education
Board Scholarship Competition (2006)
Higher Education Council Doctoral Student Scholarship (2003-2008)
Dean’s Successful Student List- High Honor Student (1998-2000)
Patents
System and method for integrated model-based histories, (Full Patent Application)
Semiha Ergan, Burcu Akinci
A formal approach to provide information support for troubleshoot, (Provisional)
Xue Yang and Semiha Ergan
Information for Mentees
About Me: Prefer chatting informally. Joined NYU in 2015, tenured in 2020, was a research faculty at CMU before. A proud PelotonMom.
Research News
NYU Tandon team help develop bio-inspired robotics for disaster response and construction, in new NSF-funded project
The United States recorded 28 natural disasters causing at least $1 billion in damages each in 2023, the highest number in the nation's history. Now researchers at NYU Tandon are helping develop a robotic system that could significantly reduce disaster recovery times while improving efficiency for contractors working in confined spaces.
Along with colleagues from New Jersey Institute of Technology, who led the project, and a researcher from The University of Scranton, the Tandon team led by Maurizio Porfiri and Semiha Ergan is part of a three-year, $5 million U.S. National Science Foundation (NSF)-funded project to create the Kastor robotic system. The funding comes from the NSF Directorate for Technology, Innovation and Partnerships, which supports research that brings together multiple disciplines and sectors to solve complex societal and operational challenges.
This Phase 2 award follows a previous $650,000 Phase 1 grant that developed a prototype robot and algorithms.
The Kastor robotic system uses swarms of self-assembling robots to transport equipment and clear debris in disaster zones, addressing a persistent challenge in disaster response: much of the workforce effort goes toward moving supplies and removing debris rather than critical tasks like searching for survivors.
The technology takes its design cues from fire ants and slime molds. Fire ants can link their bodies to form bridges over difficult terrain, while slime molds create efficient transport networks across varied surfaces. The Kastor system applies these biological strategies to create networks of flat metal robotic tiles that can autonomously reconfigure themselves as conditions change.
The tiles move themselves into position and use wheels and treads to transport pallets across disaster sites without human intervention. Algorithms developed by the research team guide their assembly and movement patterns.
Porfiri — who directs NYU's Center for Urban Science + Progress (CUSP) and is Institute Professor in the departments of Mechanical and Aerospace Engineering, Biomedical Engineering, and Civil and Urban Engineering (CUE) — brings expertise in urban science and virtual reality to the project. His role focuses on ensuring the technology integrates with existing disaster response workflows in urban environments.
Ergan — an associate professor in CUE, and on the faculty of CUSP, Institute of Design and Construction (IDC) Innovation Hub, and C2SMARTER transportation center — is leading virtual and on-site pilot studies that will test the system in realistic construction and recovery scenarios.
"Each community faces different challenges when disasters strike, and current response methods often require inefficient manual labor for debris removal and supply transport," Porfiri said. The project team has consulted with police officers, emergency responders, contractors and construction companies to understand operational requirements.
"We want to bring the high-tech automation of distribution facilities and smart warehouses to messy, unstructured outdoor environments," said Petras Swissler, an assistant professor of mechanical and industrial engineering at NJIT and the project's principal investigator.
Beyond disaster response, the researchers found the same challenges exist in construction projects, where efficiency improvements have lagged behind other industries.
"This technology will also assist at construction sites where space is tight and the ability to navigate in multiple directions while carrying dirt and construction materials is limited," Ergan said.
The project will develop a production-ready robotic system, create interfaces for operators to control the robot swarms, and conduct pilot studies in both disaster response and construction settings. Along with Porfiri and Ergan, the other co-principal investigators are Simon Garnier, a biology professor at NJIT, and Jason Graham, a mathematics professor at The University of Scranton.
AI-powered and Robot-assisted Manufacturing for Modular Construction
Semiha Ergan, assistant professor in the Departments of Civil and Urban Engineering, and Computer Science and Engineering and Chen Feng, assistant professor in the departments of Civil and Urban and Mechanical and Aerospace Engineering will lead this project.
Modular construction, with an established record of accelerating projects and reducing costs, is a revolutionary way to transform the construction industry. However, new construction capabilities are needed to perform modular construction at scale, where, as is the case in factories, the industry suffers from the dependency on skilled labor. Among the challenges this project aims to address:
- Every project is unique and requires efficiency and accuracy in recognition and handling workpieces
- Design and production-line changes are common, and require design standardization and optimization of modules, and
- Production lines are complex in space and time, and necessitate the guidance of workers while processing design and installation information accurately
To focus on these challenges while exploring modular construction within the context of Future Manufacturing (FM), this project exploits opportunities at the intersection of AI/robotics/building information modeling and manufacturing, with the potential to increase the scalability of modular construction.
The research will pioneer initial formulations to enable (a) high throughput in manufacturing through the definition and evaluation of processes that embrace real-time workpiece semantic grounding and in-situ AR-robotic assistance, (b) feasibility studies of optimizing and standardizing the design of modules, and utilization of a cyber-infrastructure for their standardization, (c) prototyping cyber-infrastructures as both novel ways of forming academia and industry partnerships, and data infrastructures to accelerate data-driven adaption in FM for modular construction, and (d) synergistic activities with a two-year institution to train and educate FM workforce for the potential of FM and technologies evaluated.
The team argues that, while the evaluations of technologies will focus on the modular construction, the proposed technologies could make manufacturing industries more competitive, particularly heavy manufacturing industries that share similar challenges such as agricultural, mining, and ship building. The project will therefore enhance U.S. competitiveness in production, bolster economic growth, educate students, and influence workforce behavior towards efficiency and accuracy with the skills required for leadership in FM.