What Does an Unconventional Engineer Look Like? | NYU Tandon School of Engineering

What Does an Unconventional Engineer Look Like?

Great engineering can come from (and lead to) unexpected places.

As Tandon faculty members prove, not all civil engineers design bridges, and not all computer engineers are tackling the problems of operating systems. Tandon engineers are involved in every sector, and in sometimes surprising ways.


4 faculty headshots spliced together

Carla Gannis

Industry Professor of Integrated Digital Media

Carla Gannis

Carla Gannis’s work sits squarely on the crossroads of art and technology, whether it takes the form of animated GIFs, large-scale illustrations, 3D-printed sculptures, or augmented reality experiences. Taking her inspiration from networked communication, art and literary history, emerging technologies, and speculative fiction, she explains that her pieces draw upon the incredible amount of media we now take in, while also critiquing that phenomenon.

Her latest work, Wwwunderkammer, plays on the concept of “cabinets of curiosities,” antique collections of natural specimens, diagrams, and other interesting or exotic objects that often had elements of both science and speculation or superstition.

An interactive environment that viewers can access in Social VR, Wwwunderkammer invites viewers to choose an avatar and explore a vast and richly detailed virtual dreamscape. Those familiar with Gannis’s body of work will find familiar objects and themes throughout: pieces reminiscent of the fantastical paintings of Arcimboldo; her own avatar, C.A.R.L.A. G.A.N. (Crossplatform Avatar for Recursive Life Action Generative Adversarial Network); and plenty of emojis, among them. While she examines how digital media influences the way we experience the real world, Gannis ultimately wants her audience to realize that, technology aside, we interact with the virtual every day, in the form of culture, dreams, fantasy, and ideologies.


Beth Simone Noveck

Director of Tandon's Governance Lab (GOVLAB)

''Noveck is committed to studying the impact of technology on governing, and under her leadership, The GovLab helps public institutions design, implement, and assess innovative ways of using tech to help institutions and people work more transparently and collaboratively.

Among the Lab’s most recent work: exploring how policymakers can responsibly re-use the public’s personal data for crisis management in an age of COVID-19 and for more effective, inclusive policymaking after the pandemic, and partnering with the Inter-American Development Bank to advise governments worldwide on ways to most efficiently and effectively address the challenges of COVID-19.


Darryl Reeves

Industry Assistant Professor of Computer Science and Engineering

Darryl ReevesWith billions of nucleotides in the human genome, there are way too many to look at individually, so an automated approach is required. That’s where computational biologists like Reeves come in. Because he has domain expertise in biology along with mathematical and computer science skills, he can develop efficient computer-enabled methods for comparing and analyzing genomes of any size — a process that’s made the modern study of genomics possible.

Reeves has also explored communities of organisms such as the human microbiome, which plays host to trillions of bacterial cells in addition to our own human cells. Some are beneficial, and some can be harmful, but, again, it would be impossible to process, manage, and analyze the entirety of the DNA present in these communities without the help of computers and sophisticated algorithms. In the past, he says, you might not have been taught to think of biology as a hardcore quantifiable science, but technology has changed that forever.


Julia Stoyanovich

Assistant Professor of Computer Science and Engineering and the NYU Center for Data Science

Julia StoyanovichAt a time when artificially intelligent automated decision systems (ADS) are being used by banks to determine who gets loans, by landlords to determine who gets to rent an apartment, by employers to decide whom to invite for job interviews, and by court systems to decide who gets offered bail or parole, it’s disturbing to realize that those systems can be inherently biased. Stoyanovich cautions that while it is customary to think that the complexity and opacity of the algorithms involved are to blame for some of these “bias bugs,” the data being used to train the systems is the main culprit. Accountability for the decisions being made by an ADS, however, always rests with a human being.

She feels a deep responsibility to teach students about the social implications of the technology they build. A typical student, she says, has an engineer’s desire to build useful artifacts, such as a classification algorithm with low error rates, but may not have the awareness of historical discrimination, or the motivation to ask hard questions about the choice of a model or of a metric. But that student, as she explains, will soon become a practicing data scientist, influencing how technology companies impact society.

Among the unconventional teaching tools now at her disposal is the “Data, Responsibly” comic series, which she created in collaboration with graduate student Falaah Arif Khan.