Eight NYU research teams and their business student counterparts, make up the Fall 2026 cohort of Tech Venture TeamUp (TVT). Their work ranges from a wildfire-resistant roof coating to an AI co-scientist for rare disease drug discovery and a stethoscope app that can hear a swallowing disorder. The teams come from labs across Grossman, Dentistry and Tandon.
What they share is a set of open questions that the lab can't answer: who buys, at what price, through which channel, and under which regulatory pathway. Each team is now working on answering those questions with their new business-focused teammates, who they met through TVT in October.
About Tech Venture TeamUp
Tech Venture TeamUp (TVT) pairs NYU researcher teams with NYU Stern MBA and other Masters students who bring business experience, to accelerate the commercialization of early-stage deep tech and life science innovations from NYU research labs.
At the kickoff on Oct 8, research teams pitched their projects, students introduced themselves, and both groups met over food and structured networking. Matches were made only where researchers and students agreed to work together. Through Dec 10, the new teams are developing their business models with:
- Venture coaching from the Leslie Entrepreneurial Institute
- Workshops on customer discovery, go-to-market, regulatory strategy, and pitch prep
- $1,000 per team in reimbursable customer discovery expenses
- Finale pitch to NYC investors, vying for a chance to win a $2500 prize
The incubation period works as a trial for each new team. After the finale, researchers and students decide whether to keep working together and, potentially, co-found a company built on NYU research.
Meet the Fall '26 TVT Cohort
BioPress
A benchtop platform that mechanically compresses cancer cells to recreate the physical pressure inside a solid tumor, giving researchers a more realistic model for testing therapies than a standard lab dish. Drug results that look promising in the lab often fail to hold up in patients, in part because conventional cell models miss these physical forces.
Team:
- Liam Holt, PhD (Faculty, Grossman)
- Shivanjali Saxena, PhD (Postdoc, Grossman)
- David Duran, PhD (Postdoc, Grossman)
- Cynthia Wang, PhD
- In collaboration with: Veronica Uribe-Echevarria Zubizarreta, PhD, MBA (Postdoc, Grossman)
CLXY
A suite of physical and digital tools that guide dental and surgical implant procedures while capturing structured procedural data, the foundation a future AI surgical assistant would need. Surgeons planning complex implants currently lack standardized digital tools to guide execution and record what happens. Starting in dentistry, the team has developed and tested AI-assisted implant planning concepts, received $20K in NYU innovation grants, and has patent activity underway.
Team:
- Young K. Kim, DMD, DMSc (Faculty, Dentistry)
- In collaboration with: Leonardo Clo (Stern '27)
Cognitive Empathy Academy
A self-paced digital platform where physicians practice conversations with AI-simulated virtual patients and receive personalized feedback on empathic communication, a few minutes at a time. Poor doctor-patient communication lowers patient experience scores and contributes to staff turnover, yet physicians have little time for in-person training. The team has completed 30+ customer discovery interviews, built a working virtual patient and AI coach prototype, secured $226K in grants and funding, and established active partnerships with NYU Langone Health.
Team:
- Cristina Gonzalez, MD (Faculty, Grossman)
- Heidi Meyer, PhD (Postdoc, Grossman)
- Neysha Arcelay
- In collaboration with: Sophia Sabharwal (Stern '28)
DigDis
An AI system that analyzes swallowing sounds recorded on an inexpensive digital stethoscope to diagnose and stage oropharyngeal dysphagia in real time, with no radiation. About 15 million US adults live with this swallowing disorder, but the gold-standard diagnostic test is costly, uses radiation, and isn't available in most primary care or telehealth settings. In testing on 408 patients, the team reports about 90% accuracy against the gold standard.
Team:
- Fernando Hugo, DDS, MSc, PhD (Faculty/Chair, Dentistry)
- Rafaela Rech, PhD
- In collaboration with: Craig Binder (Stern '27) & Manjiri Nadkarni, MD (Stern '28)
Eure
An agentic AI co-scientist that combines frontier language models with specialized genomic foundation models to identify disease targets and matching therapies, including for rare diseases where target discovery has traditionally been too costly to pursue. Imprecise biological targets are a major reason clinical trials fail. With an operational prototype, the team has demonstrated new discoveries, and has three papers published or in review (including in Nature).
Team:
- Jimin Tan, PhD (Faculty, Grossman)
- Bo Xia, PhD (Grossman '22)
- Xi Fu, PhD
- Huiyuan Zhang, PhD
- In collaboration with: Benjamin Newman (Stern '27) & Paul Leon (Stern '27)
GeoShield Roof
A thin-layer geopolymer coating and interlayer strip that retrofits an existing roof with a fire-resistant thermal barrier, reducing heat transfer and delaying ignition. During wildfires, homes ignite when embers and heat reach the wood roof deck beneath standard asphalt shingles, and full roof replacement is out of reach for most homeowners in fire-prone areas.
Team:
- Augustin Guibaud, PhD (Faculty, Tandon)
- Charudatta Mhasde, PhD (Postdoc, Tandon)
- In collaboration with: Duncan MacDougall (Stern '28)
OncoVera
A clinician-designed AI platform that brings a cancer patient's pathology slides, MRI scans, lab results, and treatment history together into one interpretable risk score, starting with prostate cancer. Today that information sits across separate systems, and physicians piece it together by hand. The team has built an initial AI prototype on real prostate biopsy images.
Team:
- Fang-Ming Deng, MD, PhD (Faculty, Grossman)
- Jinrong Cheng, MD (Faculty, Grossman)
- Ananya Madhavaram (Stern '26)
- Irene Li (Gallatin '28)
- In collaboration with: Chee Kim (Stern '28)
PolySynk
A digital lab notebook that records polymer materials in a machine-readable format, capturing the characteristics AI tools need to speed up materials discovery. As new regulations tighten the supply of fluoropolymers, specialty materials companies are under pressure to find alternatives faster, but poorly organized in-house data blocks the AI tools that could help. The platform has been validated in a relevant environment with active industry research collaborators including BASF and Apple.
Team:
- Juan de Pablo, PhD (Executive Dean & Faculty, Tandon, VP for Global Science and Technology, President's Office)
- Gervasio Zaldivar, PhD (Postdoc, Tandon)
- Yuan Tian, PhD (Postdoc, Tandon)
- Ge Sun, PhD (Postdoc, Tandon)
- In collaboration with: Rafi Sarkar (Stern '27)
What Comes Next
The teams will present at the Finale Pitch Fest on Dec 10 to a panel of investor judges and an audience of mentors and peers. Two winning teams will receive an additional $2,500 in reimbursable expenses for customer development.
After the program, teams that choose to keep working together will receive support from the Institute to pursue NSF I-Corps, the NYU Entrepreneurs Challenge, Small Business Innovation Research and Small Business Technology Transfer (SBIR/STTR) grants, and/or other follow-on programs.
Join the next TeamUp
If you're an NYU PhD student, researcher or research faculty member and are interested participating in the next Tech Venture TeamUp to be matched with a business student, email Rebecca Silver, Director of the Leslie Entrepreneurial Institute ([email protected]).
Researchers who want to test the commercial potential of their work can also start with the Tech Venture Workshop.
To meet more NYU researcher teams, check out our Blog:
