What you should expect
What we work on
Our mission is to help people make sense of complex data. We combine methods from AI, data science, and human-computer interaction to develop interactive systems for data visualization and analysis.
- Visualizations for Traceable and Defensible Human-AI Collaborationgoal tracking · bi-directional communication · interactive reasoning · uncertainty
- Making AI Trustworthy in Education Through Interactive Visualizationmeasuring trustworthiness · responsive pedagogy · personal data tracking · self-reflection
- Visual Analytics for Expert-Driven Scientific Discoverymultidimensional visualization · spatial and 3D data · automated hypothesis testing
- Bias-Aware Visual Analytics Using Interaction Tracesinteraction traces · analytic provenance · cognitive bias · mixed-initiative guidance
Browse all of our papers to see the kinds of systems, studies, and guidelines we produce.
Who we're looking for
We're looking for self-motivated students who want to build visual analytics, human-centered AI, and data science tools to solve pressing human-centered, data-driven problems. Nobody arrives knowing everything; these are the skills we use and teach along the way:
- Data visualization: temporal, networks, tabular, text, geospatial, 3D
- Data mining and analysis: regression, clustering, dimensionality reduction, aligning with domain needs, reporting, dashboards
- AI and machine learning: training, fine-tuning, evaluating, prompt engineering
- Human subjects research: think-aloud, interviewing, mixed methods, thematic analysis
- UI/UX: design, interaction, prototyping, implementation, evaluation
In your application, tell us what you're curious about and why. Be yourself rather than writing what you think we want to hear.
How we do research: a typical expedition
- Meet a domain expert with a data problem. Someone is sitting down to look at data and make a decision, and the tools they have aren't enough.
- Map the terrain. Building tools requires three things: the task (what do we need to make sense of?), the data (where will answers come from?), and the users (who is interpreting the results?).
- Build the tool. Systems, interfaces, algorithms, and libraries for doing data science, for experts and novices alike, co-designed with the people who will use them.
- Study it in the field. We study how people use our tools to interpret data and how interaction and visualization impact decision-making, through mixed methods, human-subjects studies with domain experts, and longitudinal deployments.
- Share what we learned. Open-source software, empirical studies, and design guidelines for the community.
Lab culture
Research is an adventure
"It's a dangerous business, Frodo, going out of your door. You step into the Road, and if you don't keep your feet, there is no knowing where you might be swept off to!"
I see research as an adventure. You have a vague idea of a goal, a destination, something tangible, but you're not sure how you'll get there, and what challenges you'll face along the way. But you'll only get where you're going by taking that first step out the door.
Staying the course
"All we have to decide is what to do with the time that is given us."
You have to trust in yourself and let go of what you cannot control. Comparison is the thief of joy. Making progress can mean a lot of things in research, from reading to writing to experimenting to thinking. Trust you are on the right path.
New students start on a scoped first project with more hands-on support, then shape later projects around their own goals.
Being a part of the fellowship
"I'm glad to be with you, Samwise Gamgee... here at the end of all things."
Research is a very social endeavor. Your best ideas will come from hanging out with interesting people. And when times are tough, it's your colleagues, peers, and friends who will stick by you, lift you up, and give you the strength to carry on.
Group meetings
We meet as a group to discuss papers, give feedback on drafts and proposals, and practice talks before conferences.
Outside the lab
Lab outings, conference trips, and the occasional hike.
Resources for the journey
Why Stevens?
Stevens Institute of Technology sits on Castle Point in Hoboken, New Jersey, directly across the Hudson River from Manhattan. Students are a short trip from New York City's technology, finance, media, and healthcare communities.
Funding
Ph.D. students in the Ph.D. in Computer Science and Ph.D. in Data Science programs receive fully funded doctoral study. For Stevens master's and undergraduate students, research credit, independent studies, and paid positions may be available depending on the term.
Partner labs
On campus, we work alongside:
- Hanlon Financial Systems CenterIndustry-grade financial technology labs that replicate the tools used at finance companies.
- Stevens XR LabExtended-reality spaces and equipment for immersive visualization and interaction.
Internships
Summer research internships in industry and at national labs are a great way to grow as a researcher. Adam interned at NASA JPL, Adobe Research, and MIT Lincoln Laboratory during his Ph.D. and is happy to talk through internship options with lab members.
How to apply
If you made it this far and liked what you saw, then give us a shout :)
Prospective Ph.D. students
Apply through one of these Stevens programs and name Adam Coscia as a potential advisor in your statement:
- Ph.D. in Computer ScienceFully funded doctoral study in AI/ML, algorithms, and human-centered computing.
- Ph.D. in Data ScienceFully funded doctoral study in AI/ML, big data, and statistical methods.
Current Stevens master's and undergraduate students
You don't need prior research experience. If a project here sparks your curiosity, email Adam with a few sentences on what interests you, your CV, and a link to anything you've built (a class project counts!). Research credit, independent studies, and paid positions may be available depending on the term.
- M.S. in Human-Centered AITraining to design user-focused AI systems, and a natural path into lab projects.
Visiting research scholars and interns
Visiting students, scholars, and summer interns are welcome to join the expedition too. Email Adam with a few sentences on what you'd like to work on, your CV, and when and for how long you'd like to visit.