Two teams of faculty scientists affiliated with the Johns Hopkins Whiting School of Engineering have been awarded research grants through the Cohen Translational Engineering Fund.
The fund was made possible by a generous commitment from Sherry and Neil Cohen ’83, founder and chairman of venture capital firm Emerald Development Managers. It serves as a catalyst for translating cutting-edge research into practice by providing faculty with critical early funding. The grant is designed to help researchers further develop and characterize their technology with a focus on commercial application. These activities often include conducting key experiments to de-risk the innovation, collecting data that will bolster patent applications, working with contract research organizations to accomplish discrete deliverables, building prototypes, and more.
Grantees receive a maximum of $100,000 for a nine-month project. Since its inception a decade ago, the Cohen Fund has awarded more than $1.7 million to support 33 projects. Prior winning projects include a novel gene therapy that reprograms solid tumor cells via biodegradable polymers to trigger an anti-tumor immune response in the body, as well as a lens-free holographic device for imaging urine, which enables the early detection of urinary tract infections.
A panel of experienced researchers, engineers, startup entrepreneurs, and business executives reviewed presentations from a highly competitive pool of selected faculty finalists. The 2025 grantees and their innovative projects are detailed below.
REVEAL: Real-time Evaluation and Verification of External Adversarial Links
Principal investigator:
Alex Marder, PhD
Assistant Professor of Computer Science
The pitch: Identification of the manufacturers of radios on cell towers based on received radio frequency transmissions to classify benign versus potentially malicious base stations to secure safe cellular communications infrastructure and protect secure communications.
Nation-state adversaries can eavesdrop on sensitive cellular communications around the world through the cellular radio infrastructure housed on LTE and 5G cellular towers, also known as base stations. To counter that, Marder and his team created a classifier technology that identifies the manufacturers of radios on nearby cell towers by analyzing received radio frequency transmissions. This capability helps distinguish between base stations made by benign vendors and potentially malicious base stations. Enabling secure identification offers a communications advantage to the U.S. Department of Defense and the State Department. Currently, military members and diplomats are advised against using cell phones for sensitive communications, unfortunately limiting access to the high-bandwidth and low-latency communications of cellular networks.
Marder envisions two products resulting from this technology, the first being an app that notifies the user of the base stations their phone is connected to and automatically reconfigures the phone to connect to a safe base station if a malicious base station is identified. The second product is a database of station observation and classification data, annotated with geolocations and vendors based on what the phone app observes. This database would allow for analysis of which overseas cell carriers use safe base station infrastructure in specific areas of interest.
The team plans to use the funding to transition the existing prototypes to production-ready software. This will include improving the user interface of the database, increasing the reliability of the phone application, and hardening the security of both products against potential attack.
D-SENSE: Deep Learning-Powered Digital SERS for Rapid and Ultrasensitive Bioprocess Monitoring
Principal investigator:
Ishan Barman, PhD
Professor of Mechanical Engineering
The pitch: Low-cost, label-free, and highly robust bioanalytical method for monitoring biopharmaceutical manufacturing.
The production of biopharmaceuticals – complex biologic medicines like monoclonal antibodies, viral vectors, and cell therapies – represents a growing market as more of these therapeutics are approved and enter the market. Ensuring consistent quality of these materials is paramount to their safety and clinical success, but current monitoring methods are costly, require substantial analysis time, and can cause production delays. There is a need for real-time process analytical technologies that can monitor key cell culture parameters to reduce batch failure risk and improve manufacturing yields.
Barman and his team developed a real-time monitoring technology that can quickly and accurately check the health and quality of cells grown to produce biopharmaceuticals. The technology involves mixing a small sample of cell culture growth medium with colloidal gold nanoparticles and then using digital surface-enhanced Raman spectroscopy (SERS) coupled with deep learning to detect and quantify critical analytes and product quality characteristics. Requiring only minutes to analyze samples, this approach is much faster and more efficient than traditional process analytical technologies, and it can be easily integrated into existing manufacturing processes.
Barman said, “As a lab focused on translational research, JHTV has been an invaluable partner—helping us secure IP protection early and guiding us through the application process for the Cohen Translational Fund. Their support has enabled us to pursue commercialization pathways that would be difficult to navigate alone. With our recent efforts to advance real-time monitoring technologies for biomanufacturing, this support has been especially timely. We see real potential in the broader JHTV ecosystem, from access to incubator space to future partnering opportunities.”
The team plans to use the funding to support technical development of the D-SENSE analysis platform, perform pilot testing, and achieve system integration with a bioreactor for real-time, continuous monitoring of cell culture medium with validated sensitivity and stability.