Invention of the Year Awards

This approach leverages oscillating link strengths in artificial neural networks, mimicking the rhythmic biomechanical activity observed in neural synapses. By coordinating these oscillations, the network adapts to different contexts and rapidly identifies changes in data patterns. This method allows for unsupervised learning, enabling the network to predict complex system dynamics - even in unseen or non-stationary environments - without requiring predefined contextual tokens. The
algorithm's generalist nature could revolutionize cognitive AI models.

Inventors:

• Wolfgang Losert, College of Computer, Mathematical, and Natural Sciences - Physics and The Institute for Physical Science & Technology
• Hoony Kang, College of Computer, Mathematical, and Natural Sciences - Physics

Cellular Cloaking is a method that allows cellular anonymity by randomly changing the hardware and software IDs in real time at randomized intervals. This function allows a single mobile device to behave like multiple burner phones without the need to purchase ones from a store. The functions performed by the cellular and ID portions of the device are replaced and replicated using a dedicated chip. When these IDs are replaced randomly in firmware, they allow a mobile device to behave as if it was being updated with a new cellular number and device ID at random times. This method also allows the device to use multiple networks and cellular numbers simultaneously without dropping calls or data connections.

Inventors:

• Ray Boatwright, Applied Research Laboratory for Intelligence and Security

The method allows users to objectively measure possible bias in annotations. It uses a generative AI model to create deepfakes that adjust features such as skin color and hairstyle of people in images preserving original expressions. This changes the annotator's perception of sensitive traits such as race and gender of the person. If an annotation for the same person is different before and after the adjustment, it means that there may be bias. Experiments found that the method can
effectively measure bias in annotations, and improved individual fairness by 33%. In addition, using this method to correct the annotations and then retraining the model can also help reduce the bias of the model when making predictions. This methodology offers a framework for addressing biases in pain assessment, criminal justice, education, and employment.

Inventors:

• Siva Viswanathan, Robert H. Smith School of Business - Decision, Operations & Information Technologies
• Balaji Padmanabhan, Robert H. Smith School of Business - Decision, Operations & Information Technologies
• Yizhi Liu,  Robert H. Smith School of Business - Decision, Operations & Information Technologies

RNAnneal introduces a groundbreaking two-stage computational pipeline to predict optimized RNA ensembles. The first stage generates thousands of hypotheses about potential RNA tertiary structures using existing methods. The second stage employs a molecular dynamics-integrated generative artificial intelligence model that scores these hypotheses based on thermodynamics. This method is unique as it does not require pretraining on existing structures, ensuring higher accuracy and efficiency. RNAnneal addresses this challenge by introducing a novel two-stage computational pipeline, improving the precision of RNA structure prediction and enhancing the drug discovery process. RNAnneal was tested on three RNAs from the Critical Assessment of Structure Prediction (CASP15) competition. For each of the RNAs tested, the scoring stage of RNAnneal selected the optimal hypothesis showing 100% prediction accuracy.

Inventors:

• Pratyush Tiwary, College of Computer, Mathematical, and Natural Sciences - Institute for Health Computing
• Lukas Herrong, College of Computer, Mathematical, and Natural Sciences - Institute for Health Computing

It is known that focal weakening of the cornea is the main driver of keratoconus progression and occurs before any shape changes occur in the cornea (i.e. before any clinical symptoms of degraded vision). This invention features motion tracking Brillouin microscopy (MTB), a Brillouin
microscope that measures mechanical properties guided by rapid 3D structural imaging OCT to avoid motion artifacts. It can take biomechanical measurements of the focal area and can diagnose
subclinical keratoconus unlike any previous technology. MTB enabled the capture of high-quality mechanical mapping in vivo even while the subject was breathing normally.

Inventors:

• Giuliano Scarcelli, A. James Clark School of Engineering - Fischell Department of Bioengineering
• James Randleman, The Cleveland Clinic Foundation

The invention is an anti-fungal hydrogel composition comprising a polymer, a carrier, and an effective amount of an anti-fungal agent that can be delivered intranasally It provides a treatment that is both effective and easy to manage. The hydrogel can be applied to the nasal cavity using a syringe at room temperature. It works at just below body temperature (28°C) and can be removed by the body through coughing or nasal discharge. The hydrogel is made using Pluronic F127 mixed in a salt-based solution like saline or water and combined with Amphotericin B – an antifungal drug – in a range of concentrations. Amphotericin B can also be combined with the hydrogel in a different form (e.g. encased in liposomes) to improve its delivery. The hydrogel can also be used with hyaluronic acid, which that helps things stick to surfaces, without interfering with the hydrogel's properties.

Inventors:

• Katharina Maisel, A. James Clark School of Engineering - Fischell Department of Bioengineering
• Kaitlyn Sadtler, National Institutes of Health
• Devon Hartigan, National Institutes of Health

NILE is an innovative technology that integrates near-critical CO2 for the liquefaction and extraction of biomass and municipal organic waste. The process dewaters the biomass using supercritical CO2 and then liquefies and extracts biocrude with significantly reduced oxygen and metal
content. This method produces biocrude that is highly compatible with existing petroleum refining infrastructure, specifically for hydrotreating, while maintaining low acidity, stable viscosity, and improved fuel quality.

Inventors:

• Ashwani Gupta, A. James Clark School of Engineering - Mechanical Engineering
• Kiran Raj Gouad Burra, A. James Clark School of Engineering - Mechanical Engineering

The invention combines micro-encapsulated phase change material (MEPCM) slurries with specialized microchannel geometries, such as helical or herringbone structures, to enhance cooling performance. MEPCM slurries exhibit over three times the thermal capacity within their melting range, enabling effective heat flux management. Using liquid metals like Galinstan or dielectric coolants as base fluids, the structured channels promote 3D transverse mixing, optimizing the cooling potential of MEPCM particles. This results in a compact, stable, and high-capacity thermal management system. Additionally, by implementing dielectric-based cooling, this technology has tremendous potential with heterogeneously integrated 3D chips.

Inventors:

• Damena Agonafer, A. James Clark School of Engineering - Mechanical Engineering
• Vivek Manepalli, A. James Clark School of Engineering - Mechanical Engineering

The invention combines an electron beam source with a remote plasma source. By using reactive oxygen and chlorine-based neutrals, low-damage and selective Ruthenium (Ru) etching can be enabled and controlled by an electron beam. The etching behavior and selectivity to other materials can be precisely tuned using the electron beam and remote plasma source parameters (e.g. high selectivity over tantalum). This method establishes line-of-sight ion-bombardment free processing
for Ru etching, which outperforms conventional plasma etching in both efficiency, spatial control and substrate preservation.

Inventors:

• Gottlieb Oehrlein, A. James Clark School of Engineering - Materials Science & Engineering, Institute for Research in Electronics and Applied Physics
• Yudong Li, A. James Clark School of Engineering - Materials Science & Engineering

DIY is an 8-week classroom program for 3rd, 4th, and 5th grade students that has two components. The first is an individualized guided reflection via an online tool that depicts characters making difficult decisions about inclusion and exclusion in everyday settings like the school, park, or
playground. The decisions are related to things such as gender, race, ethnicity, immigrant status, and wealth status. The second part of the program is facilitated group discussions with all students sitting in a circle, led by a trained teacher. The group discusses the online peer scenarios in terms of students' evaluations, reflections, and interpretations, in addition to discussing personal experiences of social exclusion and solutions. DIY stands out from its social emotional learning (SEL)
competitors by focusing on inclusivity and bias reduction, and addressing factors like exclusion, victimization, and harassment that contribute to the academic achievement gap and stress and anxiety for many students.

Inventors:

• Melanie Killen, College of Education - Human Development and Quantitative Methodology
• Lauren Elenbaas, College of Education - Human Development and Quantitative Methodology
• Michael T. Rizzo, College of Education - Human Development and Quantitative Methodology

Through machine learning and generative AI, users are transported into
virtual galleries and art spaces. Users can walk through a virtual painting,
watch a sculpture take shape in real-time, or even interact with digital art
in ways that were previously unimaginable. By focusing on the digitization
of works from underrepresented artists and artist communities, and
targeting university-based museum collections to digitize, Myseum
presents a solution to distinct yet related challenges. Finally, Mysuem is
an opportunity to resolve the issues related to secondary and tertiary
markets for art, creating new revenue streams from artists from all walks
of life.

Inventors:

• Jordana Moore Saggese, College of Arts and Humanities - Art History & Archaeology; The Driskell Center

An online educational module designed to teach students in any discipline about AI and information literacy. Integrated directly into existing course spaces, it offers an engaging and structured learning experience by including interactive content such as videos, quizzes, and practical exercises to give learners the chance to practice these skills for themselves. The module explains the mechanics and world impacts of generative AI and provides a cognitive framework for evaluating and fact-checking AI outputs using lateral reading skills. The module also provides guidance on citing AI-generated work and using AI tools effectively and creatively. With a focus on academic integrity and critical thinking, it equips students with the knowledge to responsibly navigate AI information ecosystems.

Inventors:

• Mona Thompson, Teaching & Learning Transformation Center; College of Education - Teaching and Learning, Policy and Leadership
• Benjamin Shaw,  University Libraries
• Daria Yocco, University Libraries
• Katie Shilton, College of Information
• Hal Daumé, College of Computer, Mathematical, and Natural Sciences - Computer Science, Institute for Advanced Computer Studies; College of Arts and Humanities - Language Science Center

Inventions of the Year Awardees:

• In Information Sciences/Overall Winner: Brain-inspired Method of Machine Learning
  Bridging the gap between neuroscience and artificial intelligence, Losert and Kang have developed a radical new way for machines to learn. Inspired by the human brain, their system mimics the rhythmic communication between neurons and glial cells, allowing machines to detect patterns and shifts in data with striking speed and accuracy. The result is an adaptable, efficient learning model that could one day predict financial crashes, natural disasters or cancer mutations, all with a fraction of the information that today’s AI systems require.
• In Life Sciences: RNAnneal: Prediction of RNA Tertiary Structure and Thermodynamics With Generative AI
  RNAnneal, developed by Millard and Lee Alexander Professor in chemical physics Pratyush Tiwary and doctoral student Lukas Herron, is a breakthrough in computational biology that could reshape how we design drugs targeting RNA—a fast-emerging frontier in medicine. This two-stage, AI-driven pipeline first generates thousands of potential RNA structures, then applies a novel thermodynamics-based model to identify the most stable configurations. It does so without relying on existing RNA data, setting a new bar with 100% prediction accuracy in benchmark tests. By dramatically improving the speed and precision of RNA-targeted drug development, RNAnneal offers new hope for treating cancer, neurological disorders, genetic conditions, infectious diseases and more.
• In Physical Sciences: Efficient Microchannel Cooling for High-powered Electronics
  As the race to build faster, smaller and more powerful electronics heats up—literally—Associate Professor of mechanical engineering Damena Agonafer and doctoral student Vivek Manepalli have cracked one of the industry’s most stubborn challenges. Their inventive cooling system, which blends tiny heat-absorbing capsules with specially designed microchannels, offers a smarter and more energy-efficient way to keep high-powered devices from frying themselves. The system has the potential to make the future of supercomputing possible by keeping it cool.
• In Social Innovation: AI and Information Literacy Module
  As artificial intelligence becomes a regular part of daily life, an interdisciplinary team of researchers, led by Mona Thompson of the Teaching and Learning Transformation Center and Benjamin Shaw of University Libraries, with researchers Hal Daumé III, Katie Shilton and Daria Yocco, want to make sure students aren’t just using AI—they’re thinking critically about it. Their new online module is a crash course on how to understand, evaluate and responsibly use AI tools, offering everything from bite-sized videos to hands-on exercises. The module aims to build digital citizens who can navigate misinformation, cite AI-generated content ethically and maintain academic integrity.

Read the full list of finalists in every category.

In addition to the Invention of the Year Awards, three special recognition awards were presented to honor recipients for their exceptional contributions to UMD’s innovation ecosystem and their lasting impact both in the region and beyond.

• Startup of the Year: ION Storage Systems, founded by Distinguished University Professor of materials science and engineering Eric Wachsman, was recognized as Startup of the Year for their pioneering work to develop safer, more powerful and fully recyclable solid-state batteries.
• Entrepreneur of the Year: Kan Cao, professor of cell biology and molecular genetics, was named Entrepreneur of the Year for launching Bluelene; the skin care line from her company, MBlue Labs, is the first to harness the anti-aging properties of the antioxidant methylene blue.
• Lifetime Inventor Award: Reinhard Radermacher (1952-2025), former director of the Center for Environmental Energy Engineering and Minta Martin Professor of Mechanical Engineering, was honored posthumously for his unparalleled career at UMD as an inventor. He holds the record for most inventions disclosed with a cumulative total of 150 since 1984, was himself an Invention of the Year winner in 2010 and finalist three other times. Six companies further developed and commercialized Radermacher’s technologies over his career at UMD, demonstrating his lasting, real-world impact.

Read more about 2025 Innovate Maryland in Maryland Today.

Groundbreaking Plasma Innovation Shines as Top Invention of the Year

Innovate Maryland Also Celebrates Research on AI Detection, Cancer Treatment, Quantum Computing

Here are the 2024 Invention of the Year Award winners across all categories:

Physical Sciences Invention of the Year/Overall Winner: Stable Plasma for Extreme Materials
Department of Materials Science and Engineering researchers Liangbing Hu, Hua Xie, Qian Zhang and Ji-Cheng Zhao and Princeton University researcher Yiguang Ju have developed a new method for creating stable plasma that can be used in extreme materials. The protocol works by applying a voltage between two blocks made of thin carbon fibers. The fibers act as a tip through which electrons can flow, resulting in all the gas between the blocks being turned into a highly stable and ultra high-temperature plasma. The process is simple, scalable and powered by renewable energy, allowing for reduced cost and a lower carbon footprint to make extreme materials.

Information Sciences Invention of the Year: Binoculars: A Method for Detecting Text Generated by Large Language Models
Two years ago, the launch of ChatGPT kicked off an AI boom that has been making headlines ever since. The growth of AI—specifically of large language models (LLMs) like ChatGPT—has been felt across all industries, but raises concerns about plagiarism, fraud and disinformation. Recent attempts to detect LLM-generated content have been consistently found unreliable, but College of Computer, Mathematical, and Natural Sciences researchers Tom Goldstein, a Volpi-Cupal Family Endowed Professor in the Department of Computer Science, and Abhimanyu Hans ’25, as well as Avi Schwarzschild Ph.D. ’23, now of Carnegie Mellon University, have developed an accurate method for distinguishing human-generated content.

The method, dubbed “Binoculars,” does not require any training data and does not need to modify the LLM to detect AI-generated text. It is also more reliable than many of its predecessors, with an accuracy rate of 90% and a false positive rate of 0.01%.

Life Sciences Invention of the Year: Combination Therapy and Diagnostic Tool for Aggressive Prostate Cancer
Each year, about 300,000 new cases of prostate cancer are diagnosed in the United States, affecting one in eight men during their lifetimes; one in 44 will eventually succumb to the disease. This grim reality is amplified among African American men, who experience an incidence rate 2.3 times higher and mortality rate 1.7 times higher than their white counterparts. Research has attributed this disparity to a blend of socioeconomic factors and biological vulnerabilities, underscoring the urgent need for targeted interventions.

Associate Professor Bi-Dar “Peter” Wang and Visiting Scientist Mohammad Waseem from the University of Maryland Eastern Shore have identified a precision prognostic biomarker and therapeutic tool, specifically for African American men. The novel treatment method combines gene therapy, introducing a tumor-suppressing mimic gene, with androgen receptor antagonists, drugs that stop the growth and spread of cancer cells. The method shows promise in treating prostate cancer that has become resistant to other types of therapy, and could potentially be used to treat all forms of advanced prostate cancer.

Quantum Invention of the Year: Quantum Non-Demolition Photon Counter
The rise of quantum computing presents unprecedented opportunities, leveraging the laws of quantum mechanics to tackle challenges beyond classical computers’ reach. Challenges to quantum computing have led researchers around the world to turn to the use of photons, or tiny particles of light, that can carry information from one place to another. With this development, photon counting has become a vital part of the field.

Traditional methods of photon counting destroy the particles’ quantum states, and existing attempts to circumvent this have a number of limitations. Researchers in the Department of Physics and the National Institute of Standards and Technology—NIST physicist and Adjunct Professor Alexey Gorshkov, NIST physicist and Adjunct Assistant Professor Michael Gullans, NIST Research Scientist James “Trey” V. Porto, graduate student Christopher Fechisin, current IBM Research Scientist Kunal Sharma, current Amazon Web Services Research Scientist Przemyslaw Bienias and Department of Physics Chair Steven Rolston have developed a new protocol that eliminates these limitations. Unlike previous methods, the researchers’ protocol has no fundamental limitation on the number of photons being counted and has the ability to count itinerant—or moving—photons. Their work has potential applications in light detection and ranging (LIDAR), fiber optic communication, quantum information processing, quantum encryption and cybersecurity, medical imaging, DNA sequencing and astrophysics.

Read the full list of finalists in every category.

In addition to the Invention of the Year awards, two faculty innovators received special recognition awards for their significant contributions to UMD’s innovation ecosystem and for making a lasting impact in the region and beyond:

• President Darryll J. Pines presented a special recognition award to Hu, a professor in the Department of Materials Science and Engineering. Hu has submitted 134 invention disclosures, making him the second-most prolific inventor in the university’s history—a feat he accomplished in only 11 years. He also co-founded the highest number of university IP-based startups, with a record four this fiscal year alone.
• Senior Vice President and Provost Jennifer King Rice presented a special recognition award to James Fey, a professor emeritus in the College of Education’s Center for Math Education. Fey co-authored a series of children’s mathematics workbooks and curricula that have generated $4.1 million in revenue for UMD since 1991. Fey donated his share of the royalties back to the department to fund over a dozen PhD students in the Fey-Graeber Fellowship program.

Read more about Innovate Maryland 2024 in Maryland Today.