Departmental Unit № 1
Department of Civil and Environmental Engineering
PhD in Civil and Environmental Engineering
100% Full Funding Guaranteed (5 Years)
Funding Package: Full tuition waiver + 12-month living stipend (~$38,000–$42,000/yr) + health insurance guaranteed through College of Engineering Fellowships and research assistantships.
Fall Priority Deadline: December 15 (Priority)
GRE Policy: Not required / Waived
English Minimums: TOEFL iBT 90 minimum or IELTS 7.0 minimum
MS in Environmental Engineering
Mostly Self-Funded (Target PhD)
Funding Reality: Direct PhD application provides guaranteed 100% full funding.
Application Deadline: January 15
Admissions Advisory: If full funding is required and MS is self-funded, students are strongly advised to apply directly to the PhD track.
Vetted Matched Scholars (1 Profiles)
Prof. Auroop R. Ganguly
Professor of Civil and Environmental Engineering; Director, AI for Climate and Sustainability (AI4CaS)
In Plain Terms · What This Scholar Does:
He uses artificial intelligence and network mathematics to predict when freak monster storms and flash floods will overwhelm city drainage systems and cause blackouts.
Core Research Topics: GeoAI, machine learning for hydroclimatic extremes, flood risk resilience, nonlinear environmental data science, climate adaptation.
Recent 2024–2026 Works & Grants: Directs the Sustainability and Data Sciences Laboratory (SDS Lab) and AI4CaS. Uses machine learning, network science, and extreme value theory to predict catastrophic flash floods, atmospheric rivers, and urban infrastructure failure.
Laboratory Instruments & Methods: Deep learning (physics-guided neural networks), extreme value statistics, complex network analysis, spatial GIS flood mapping, Python.
Recruiting Context: Director of major environmental data science laboratory with substantial defense and NSF grants.
Candidate Match:
GeoAIFlood ModelingHydrologyGISPython
Tailored Cold-Email Opening Hook:
"Discussing your background in GIS, spatial analysis, and Python programming applied to GeoAI and hydroclimatic extreme flood modeling in the SDS Lab."