ワ タ ナ ベ 研 究 チ ー ム @ NEW YORK TECH
NEWS:
» PI Watanabe awarded 5-year NSF CAREER grant (NYIT article).
» Post-doc Todd Green's new paper & journal cover here.
» Post-doc Todd Green awarded 2021 Early-Career Anatomist Publication Award.
As a lab studying biological diversity, we firmly believe that innovations spring from diversity across members. In line with this belief, our lab is committed to fostering a diverse, inclusive, and supportive environment for everyone looking to do, make, innovate, and reinvent the future.
Current Members
Aki Watanabe
Principal Investigator
Links: CV | Google Scholar | Twitter
Interests: classical music, violin, film, cooking, tennis, running
Sylvia Marshall
Academic Medicine Scholar
Project: 3-D imaging of human cadaveric eyes; brain shape differences across chicken breeds
Jeff Ng
Medical Student
Project: Cassowary cranial pneumaticity
Izza Arqam
Undergraduate Student
Project: brain-skull integration in developing chickens
Meghan Forcellati
Undergraduate Student (Columbia)
Project: Ratite brain development
Meredith Taylor
Lab Technician
Email:
???
Post-doctoral Researcher
New NSF-funded position anticipated to begin Summer/Fall 2022. More info will be provided in Fall 2021. Contact PI for inquiries.
Scott Landman
Medical Student
Project: brain-skull integration in developing chickens
Shebin Tharakan
Undergraduate Student
Project: cranial integration in snakes and lizards
Siem Satti
Undergraduate Student
Project: brain-skull integration in developing chickens
Past Members
Mariel Bedell
Medical Student
Project: Brain-skull integration in developing alligators and chickens
Alexis Morin
Medical Student
Project: Effect of cranial muscles on developing skull morphology
Marichelle Pita
Medical Student
Project: New education app for learning human anatomy
Chun Maung
Medical Student
Project: New education app for learning human anatomy
Kat Okouneva
Medical Student
Project: brain-skull integration in developing chickens
John Thomas
Undergraduate Student
Project: Musical transformation of scientific data