• Peer Observation Workshop

    Center for Excellence in Teaching, Room B502 227 West 27th Street, New York City, NY, United States

    Please join Brian Fallon, director of Faculty Development, and Meg Joseph, associate director for Student Learning Assessment, for this faculty workshop on conducting effective and meaningful peer observations. This event […]

  • AI, Teaching, and Learning Symposium

    Dubinsky Student Center, Eighth Floor Fashion Institute of Technology, New York City, NY, United States

    The symposium on AI, Teaching, and Learning at FIT will explore how emergent technologies are upending and changing how and what we teach in addition to how students learn. This […]

  • Emerging Technology Faculty Workshop: AI Prompt Engineering

    Faculty Research Space, Pomerantz Center, Room D524 Fashion Institute of Technology, 227 West 27th Street, New York City, NY, United States

    Step into a studio where a prompt, a doodle, or a quick photo can become a 3D object in hours. We’ll guide you through friendly, AI-assisted tools that generate multiple […]

  • FIT Curriculum Mini-treat

    Robert Lagary Board Room Marvin Feldman Center, Ninth Floor, Fashion Institute of Technology, New York City , NY, United States

    Join the offices of Curriculum and Faculty Development for a mini-retreat with presentations on: Curriculum Process and Registration Curriculum Development and Learning Assessment (Office of Faculty Development) Online and Blended Learning Collegewide Curriculum Committee Guidance A light breakfast and refreshments will be served. This event is for FIT faculty only. REGISTER FOR THE MINI-TREAT

  • Emerging Technology Faculty Workshop: 3D Scanning

    Faculty Research Space, Pomerantz Center, Room D524 Fashion Institute of Technology, 227 West 27th Street, New York City, NY, United States

    Capture the things you love—a shoe, a sculpture, a corner of a room—and place them in a small, navigable scene. We’ll teach a simple photo dance (how many shots, where to stand, what light to find) that produces clean results. You’ll see two flavors of capture—traditional meshes and newer “splat/NeRF” looks—and when each makes sense. […]