By Dave DeFusco
At the Katz School鈥檚 2026 Symposium on Science, Technology and Health, graduate students presented research projects united by a common goal: solving real-world problems through practical innovation. Held May 19 at the 糖心破解版 Museum, the symposium showcased how students across disciplines are applying advanced research to challenges in healthcare, education, business, agriculture, communication and public policy.
In his address to the students, 糖心破解版 President Ari Berman emphasized that as science and society evolve rapidly, maintaining a focus on human dignity is essential. Linking the moment to the Jewish holiday of Shavuot, which commemorates the giving of the Ten Commandments at Mount Sinai, he highlighted the foundational idea that every person is created in the image of God. That belief, he said, underpins both education and innovation at the Katz School, where research is driven by a responsibility to serve people first.
鈥淭he only reason we鈥檙e here is because we believe in each of you,鈥 he said. 鈥淚t鈥檚 why the Katz School is such a great brand, because you're putting human dignity at the center of your work.鈥
In addition to honoring the 32 research teams whose posters were on display, the faculty also recognized four projects for their exceptional scholarship and impact on clinical practice and industry, with awards for:
- Outstanding Original Research in Science and Tech: Chengyi Liu and Lei Zhang (M.S. in Artificial Intelligence)
- Outstanding Original Research in Health Sciences: Vanessa Murad (Occupational Therapy Doctorate)
- Outstanding Impact in Health Sciences: Jennifer Schneider (M.S. in Speech-Language Pathology)
- Outstanding Impact in Science and Tech: Emmanuel Kasigazi (M.S. in Data Analytics and Visualization)
Attendees also had the opportunity to vote for the People鈥檚 Choice Award, which recognized a project that resonated most strongly across disciplines. This award went to Arunima Chandra and Mrinal Chaman (M.S. in Digital Marketing and Media).
Science and Technology Research
Honggang Wang, chair of the Department of Graduate Computer Science and Engineering, said that students didn鈥檛 simply build theoretical models. 鈥淭hey are designing technologies and analytical systems that directly address practical human needs鈥攆rom medical imaging and cybersecurity to education access and sustainable agriculture,鈥 he said. 鈥淭he interdisciplinary nature of the work reflects how modern science increasingly depends on collaboration across fields.鈥
Among the projects drawing attention was research by Jialu Li, a student in the M.S. in Artificial Intelligence, who developed PAFL, a system that allows veterinary hospitals to collaborate in training artificial intelligence programs without sharing sensitive patient data. The project focused on helping computers analyze dog chest X-rays to detect enlarged hearts and estimate heart size more accurately. Instead of transferring private medical images to one central database, the system allows hospitals to keep information locally while still contributing to the AI training process.
Artificial intelligence students Lei Zhang and Chengyi Liu presented a robotic health-monitoring system that measures heart rates using millimeter-wave radar instead of wearable devices or cameras. Their system protects privacy and functions even in low-light conditions. The students discovered that radar measurements became much less accurate when devices were placed at poor angles, so they created a robot capable of repositioning itself automatically to improve readings. By combining robotic navigation, body-position tracking and signal analysis, the system more than doubled heart-rate accuracy compared to fixed radar systems, potentially opening new possibilities for hospitals and elder-care facilities.
Artificial intelligence student Tirth Joshi explored the growing dangers of digital privacy loss in an era of interconnected public data. His project introduced the Re-Identification Pressure Index, or RPI, a system designed to measure how easily supposedly anonymous people can be identified when multiple datasets are combined. By studying public information such as housing records, transportation data and work locations, Joshi demonstrated how small pieces of information can gradually reveal personal identities over time.
Agriculture and sustainability were another major focus. Sapna Rani, Angel White and Sree Harshini, students in the M.S. in Biotechnology Management and Entrepreneurship, created FieldFit, an AI-powered farming application designed to help farmers manage crops under difficult conditions. The app provides recommendations on irrigation, pest management, crop care and safe use of agricultural supplies based on local conditions. By keeping FieldFit affordable and easy to use, the students aimed to create practical decision-making support for farmers facing drought, rising costs and unpredictable growing conditions.
Computer science doctoral student Dengyi Liu developed an artificial intelligence system capable of evaluating caregiver-child interactions through short private videos. Traditionally, specialists manually review such interactions, a process that can be costly and time-consuming. Liu instead used existing AI models to identify important visual and audio patterns from relatively small datasets. By combining speech, movement and behavioral cues, the system predicted interaction quality more accurately than methods relying on only one type of information.
Cybersecurity student Srujan Dasari demonstrated an intelligent AI assistant designed to automate many of the repetitive tasks performed by human security analysts. Built using the Model Context Protocol, the system safely allowed large language models to interact with cybersecurity tools while maintaining audit trails and permission controls. In testing, the platform reduced some security analysis tasks from nearly an hour to just minutes, offering a potential solution for increasingly overwhelmed cybersecurity teams.
Mayukh Paul鈥檚 cybersecurity work tackled one of the most persistent problems in digital security: human error. Paul highlighted that most cyberattacks succeed not because of technical system failures, but because people accidentally click phishing links, reuse passwords or fall victim to social engineering scams. VISHWAR is a simulation-based platform that places users in realistic cyberattack scenarios, tracks how they respond and provides feedback through what he calls a Human Vulnerability Management Lifecycle, which includes identifying risk behaviors, testing responses, improving performance, and monitoring change over time.
Education access stood at the center of Data analytics student Emmanuel Olim Kasigazi鈥檚 project, AXAM, an offline artificial intelligence learning platform designed for students without reliable internet access. Built using thousands of lecture transcripts from Massachusetts Institute of Technology OpenCourseWare, the system can answer educational questions in more than 100 languages while running entirely on local devices such as laptops or USB drives. Tests showed that AXAM correctly retrieved educational content roughly 99% of the time in English while also performing strongly in several other languages.
Another data analytics student Benjamin Morris introduced a new approach to analyzing music streaming success through what he described as 鈥渕usical DNA.鈥 Rather than relying only on simple metrics such as tempo or energy, Morris examined lyrics, song structure, production details and listening context to predict streaming performance. His deeper analytical model produced more consistent and accurate predictions over time than many existing industry methods, suggesting that richer data analysis could help music companies make better decisions about playlist placement, artist promotion and release strategies.
Business-focused research also featured prominently in the work of students in the M.S. in Digital Marketing and Media. Aditya Bhandari, Hangmu Mabuhang, Sebika Bomjan Shahi and Thulani Nsingo studied why pharmaceutical research companies are increasingly reluctant to renew costly data-analysis services. Focusing on the company Cytel, the team found that many clients struggle to clearly understand the financial value of the services they receive, especially as lower-cost AI tools and open-source software become more common. Their proposed solution combined clearer return-on-investment reporting with flexible service packages tailored to smaller biotechnology firms.
Digital marketing students Chipo Prudence Pasi and Tiyese Phiri examined how 鈥渁gentic AI鈥 systems capable of adapting messages in real time could improve digital marketing for faith-based audiences. Their research emphasized the importance of trust, cultural values and religious identity in shaping audience responses. The students argued that AI-generated marketing becomes more effective when it reflects values such as integrity, community and purpose instead of relying on generic advertising language.
Several other digital marketing students focused on how technology and communication intersect in industries ranging from mortgages to tourism. Swaraj Acharekar studied why mortgage loan officers often hesitate to adopt new customer-management software in his project on the platform Lendware. He found that concerns about brand trust, productivity loss and difficult data migration discourage adoption.
Gayathri Rajesh Kumar and Joyanta Mallick explored how speech-language pathology graduate programs can improve student recruitment through data-driven digital marketing. By analyzing online search behavior and competing academic programs, they found growing interest in specialized medical training and online learning opportunities.
Housing access was the focus of Fildah Tsuro鈥檚 research on newcomers to the United States. Her project proposed replacing traditional credit-score requirements with a 鈥淢ulti-Factor Reliability Index鈥 that considers school enrollment, employment contracts, international banking records and identity verification. Tsuro argued that the system could reduce fraud while helping immigrants and international workers gain fairer access to rental housing in New Jersey and New York.
Arunima Chandra and Mrinal Chaman developed a low-cost marketing research pipeline for small businesses using artificial intelligence. Working with Sweet Vegan NYC, an allergen-free chocolate company, they analyzed more than 1,200 customer reviews to identify emotional patterns influencing purchasing behavior. Their Emotional Resonance Model found that emotional themes such as celebration, inclusion and gift-giving produced stronger sales than purely functional advertising focused on safety or ingredients.
Denelsen Dandi compared challenges facing cattle farmers in Zimbabwe and the United States. While producers in both countries struggled with disease, drought and market pressures, the problems differed substantially by region. Zimbabwean farmers often faced shortages of veterinary services and reliable information, while U.S. farmers focused more heavily on monitoring large herds and detecting disease early.
Monalissa Zibwowa examined how tourism could create employment opportunities for young people in Zimbabwe. Although many Americans recognize Victoria Falls, her research found limited awareness of the country鈥檚 broader attractions. Zibwowa recommended stronger digital marketing, simplified visa systems and targeted online outreach to increase tourism and create jobs in hospitality, transportation and cultural services.
Biotechnology student Dharani Vedula explored how new brain-repair technologies can move from the laboratory into real medical use in her project, 鈥淣EURADAPTIVE: Market and Investor Strategy for an AI-Native Brain Repair Platform.鈥 Her research focused on Neuradaptive, a startup developing technology that combines artificial intelligence, brain-computer interfaces and targeted brain stimulation to help restore function in people with serious neurological conditions.
Mathematics research at the symposium ranged from economics and speech technology to astronomy and renewable energy. Ian Phiri Chigada, a student in the M.A. in Mathematics, studied whether the language used in Federal Reserve meeting notes could help predict future interest-rate decisions. Comparing traditional word-count methods with AI-generated sentiment analysis, he found that more inflation-focused language often appeared before rate hikes, though the predictive signal remained modest.
Mathematics Ph.D. students Sahil Kumar and Namrataben Patel presented MambaVoiceCloning, a text-to-speech system designed to generate realistic speech more efficiently than many current technologies. Their system maintained stable tone, rhythm and emotional expression during long passages while requiring less computing power, making it promising for voice assistants, accessibility tools and multilingual speech applications.
Arya Dutta, a student in the mathematics Ph.D., investigated the orbital behavior of comet 39P/Oterma using advanced mathematical models describing the gravitational interactions among the Sun, Jupiter and the comet itself. His work identified additional orbital resonance patterns that may explain why the comet sometimes drifts toward Saturn after close encounters with Jupiter.
Penghui Han explored how carefully controlled 鈥渘oise,鈥 or small irregular vibrations, could improve the performance of renewable energy systems that convert movement into electricity. By introducing low-level disturbances, Han uncovered hidden performance patterns and improved optimization methods without reducing efficiency.
Ruslan Gokhman challenged assumptions about modern forecasting systems by comparing complex transformer-based AI models with simpler linear mathematical approaches for long-range temperature prediction. Surprisingly, the simpler models consistently outperformed the more advanced AI systems in accuracy and stability, demonstrating that straightforward methods can still provide the strongest scientific results in certain applications.
Health Sciences Research
Health sciences research was equally prominent throughout the event, highlighting new approaches to patient care, communication disorders and family support systems.
鈥淥ur students are tackling healthcare challenges that affect people across the lifespan,鈥 said Marissa Barrera, assistant dean of health sciences and director of the M.S. in Speech-Language Pathology. 鈥淲hat makes this research especially meaningful is its emphasis on compassionate, evidence-based care that can improve quality of life not only for patients, but also for families, caregivers and communities.鈥
Vanessa Murad, a student in the Occupational Therapy Doctorate, examined how occupational therapists can help children with picky eating and Avoidant Restrictive Food Intake Disorder, or ARFID. Her educational guide for parents explained how occupational therapy can support feeding skills, sensory challenges and family mealtimes.
Carly Ettinger studied cultural humility among future occupational therapists and found that although most students understood the concept, many did not feel prepared to apply it clinically. Her educator guide proposed more interactive and hands-on approaches to teaching culturally responsive care.
Rachel Riemenschneider created an occupational therapy guidebook for families navigating frenectomy procedures, helping parents better understand feeding support, exercises and recovery after surgery involving oral tissues.
Sydney Ostroff developed a yoga-based social and emotional learning program for neurodivergent adults. Her six-week intervention improved self-regulation, communication skills and confidence in handling everyday situations.
Physician assistant studies student Abigail Assenza reviewed treatments for Helicobacter pylori infections and found that four-drug therapies generally eliminated the infection more effectively than traditional three-drug approaches, potentially helping reduce stomach ulcers and cancer risk worldwide.
Speech-language pathology research focused heavily on communication and long-term care. Jemma (Shayna) Lifschitz studied how asthma affects children鈥檚 speech production and found that breathing exercises may improve both asthma control and speech clarity. Shirah Niknam examined how prenatal alcohol exposure affects language, memory and executive functioning throughout life, emphasizing the importance of long-term speech-language support. And Nicole Aziz investigated whether whispering truly harms the voice and found that scientific evidence remains mixed, challenging long-standing assumptions in voice therapy.
In Jennifer Schneider's research, she examined how accurately emergency medical workers identify communication problems such as aphasia, a disorder affecting language understanding and expression, and dysarthria, a condition that causes slurred or weakened speech, when evaluating possible stroke patients. By reviewing commonly used ambulance stroke screening tools, she found that communication symptoms are often described too generally or inconsistently, which can lead to missed strokes, incorrect treatment decisions, and delays in life-saving care. Her findings showed that no single screening tool consistently identifies communication problems accurately, highlighting the need for better training and greater involvement of speech-language pathologists in emergency stroke care.
