Symposium on Science, Technology and Health 2026 Making the World Smarter, Safer and Healthier Request Info Apply Now Attend an Info Session Contact Us Artificial Intelligence Biotechnology Computer Science Cybersecurity Data Analytics and Visualization Digital Marketing and Media Mathematics Nursing Occupational Therapy Physician Assistant Physics Speech-Language Pathology 2026 Symposium on Science, Technology and Health New York City I May 19, 2026Showcasing graduate student research across science, technology and health sciences. ALL PROJECTS | VIEW PHOTOS All ProjectsArtificial IntelligenceBiotechnology Management & EntrepreneurshipComputer ScienceCybersecurityData Analytics & VisualizationDigital Marketing & MediaM.A. in MathematicsPh.D. in MathematicsOccupational TherapyPhysician Assistant StudiesSpeech-Language Pathology Artificial Intelligence Autonomous Navigation and Viewpoint Optimization for mmWave Radar-Based Contactless Vital Sign Extraction Author: Lei Zhang and Chengyi Liu, Artificial IntelligenceFaculty Mentor: Yucheng Xie, Ph.D.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. VIEW POSTER PAFL: Personalized and Adaptive Federated Learning for Canine Cardiomegaly Keypoint Prediction Authors: Jialu Li, Artificial IntelligenceFaculty Mentor: Honggang Wang, Ph.D.Jialu Li 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. VIEW POSTER When "Anonymous" Data Stops Being Anonymous: Measuring Cumulative Re-Identification Pressure in Public Data Ecosystems Author: Tirth Joshi, Artificial IntelligenceFaculty Mentor: Aaron Ross, MBATirth 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. VIEW POSTER Biotechnology Management & Entrepreneurship Field Fit App: AI- Driven Decision Support for Agriculture Biotechnology Author: Sapna Rani, Angel White and Sree Harshini, Biotechnology Management & EntrepreneurshipFaculty Mentor: Robert Friedman, MBASapna 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. VIEW POSTER | READ STORY NEURADAPTIVE: Market and Investor Strategy for an AI-Native Brain Repair Platform Author: Dharani Vedula, Biotechnology Management and EntrepreneurshipFaculty Mentors: Robert Friedman, MBADharani Vedula explored how new brain-repair technologies can move from the laboratory into real medical use in her project, “NEURADAPTIVE: Market and Investor Strategy for an AI-Native Brain Repair Platform.” 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. VIEW POSTER Computer Science Low-Resource Multimodal Prediction of Caregiver and Child Interaction Author: Dengyi Liu, Computer ScienceFaculty Mentor: Honggang Wang, Ph.D.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. VIEW POSTER Cybersecurity MCP-Enabled Intelligent Cyber Agent for Red and Blue Team Automation Author: Srujan Dasari, CybersecurityFaculty Mentor: Daniel Galeon, MBASrujan 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. VIEW POSTER VISHWAR: A Simulation-Based Framework for Measuring and Reducing Human Cyber Risk Author: Mayukh Paul, CybersecurityFaculty Mentor: Daniel Galeon, MBAMayukh Paul’s 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. VIEW POSTER | READ STORY Data Analytics & Visualization When There is No Internet: An Offline Multilingual Retrieval-augmented Generation System for AI-powered Education Author: Emmanuel Olimi Kasigazi, Data Analytics and VisualizationFaculty Advisor: Andrew Catlin, M.S.Education access stood at the center of Data analytics student Emmanuel Olim Kasigazi’s 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. VIEW POSTER A Multi-Domain Feature Framework for Predicting Music Streaming Success Author: Benjamin Morris, Data Analytics and VisualizationFaculty Mentor: Andrew CatlinBenjamin Morris introduced a new approach to analyzing music streaming success through what he described as “musical DNA.” 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. VIEW POSTER | READ STORY Digital Marketing & Media Agentic AI and Faith-Informed Consumer Segments: Increasing Engagement in Digital Marketing Messaging Authors: Chipo Prudence Pasi and Tiyese Kyle Phiri, Digital Marketing and MediaFaculty Mentor: William Wedo, MJ, MBAChipo Prudence Pasi and Tiyese Phiri examined how “agentic AI” 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. VIEW POSTER Rebuilding Trust and Visibility in Mortgage Technology: A Strategic Adoption Framework for Lendware Authors: Swaraj Acharekar, Digital Marketing and MediaFaculty Mentor: Shimon Perry, MBASwaraj 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. VIEW POSTER | READ STORY Enhancing Renewal Intent through Value Demonstration: A Strategic ROI and Modular Product Approach for Cytel Authors: Hangmu Mabuhang, Sebika Bomjan Shahi, Thulani Arnold Nsingo and Aditya Bhandari, Digital Marketing and MediaFaculty Mentor: Shimon Perry, MBAAditya 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. VIEW POSTER Elevating Speech-Language Pathology Through Market-Driven Research Authors: Gayathri Rajesh Kumar and Joyanta Mallick, Digital Media and MarketingFaculty Mentor: Larry Cohen, MBAGayathri 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. VIEW POSTER Redefining Rental Access: A New Standard for Housing Equity for Newcomers in New Jersey Author: Fildah Tsuro, Digital Media and MarketingFaculty Mentor: Joseph Panzerella, M.S.Housing access was the focus of Fildah Tsuro’s research on newcomers to the United States. Her project proposed replacing traditional credit-score requirements with a “Multi-Factor Reliability Index” 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. VIEW POSTER | READ STORY An AI-Driven Consumer Research Pipeline for Designing and Validating Advertising Strategies Authors: Arunima Chandra and Mrinal Chaman, Digital Media and MarketingFaculty Mentors: Joseph Panzarella, M.S. and Erik Wennerod, MBAArunima 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. VIEW POSTER Comparative Study of Cattle Producer Challenges in the U.S. and Zimbabwe: Identifying Opportunities for AI‑Enabled Extension and Digital Decision Support Author: Denelsen Dandi, Digital Marketing and MediaFaculty Mentors: Erik Wennerod, MBA and Joseph Panzarella, M.S.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. VIEW POSTER Beyond the Falls: Strategic Tourism Development for Profitable Youth Employment in Zimbabwe Author: Monalissa Zibwowa, Digital Marketing and MediaFaculty Mentor: Erik Wennerod, MBA and Joseph Panzarella, M.S.Industry Collaborators: Ropafadzo Dunira, Embassy of Zimbabwe to the USA; Hannah Pratt, Project Manager, CentimentMonalissa 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’s 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. VIEW POSTER | READ STORY M.A. in Mathematics Do FOMC Minutes Signal Future Rate Moves? Author: Ian Phiri Chigada, M.A. in MathematicsFaculty Mentor: Yuri Katz, Ph.D. Ian Phiri Chigada 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. VIEW POSTER Ph.D. in Mathematics MambaVoiceCloning: Efficient and Expressive Text-to-Speech Via State-Space Modeling and Diffusion Control Authors: Sahil Kumar and Namrataben Patel, Ph.D. in MathematicsFaculty Mentor: Honggang Wang, Ph.D.Collaborator: Youshan Zhang, Ph.D., Chuzhou UniversitySahil 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. VIEW POSTER Investigating New Resonance Transitions in Oterma's Orbit to Explain the Latest Observations Author: Arya Dutta, Ph.D. in MathematicsFaculty Mentor: Marian Gidea, Ph.D.Collaborator: Claudio Sierpe, Ph.D., University of San PaoloArya Dutta 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. VIEW POSTER Quasiperiodic Noise For Bifurcation Mapping And Optimization: Numerical Study of Voltage Output in a Nonlinear Energy Harvester Author: Penghui Han, Ph.D. in MathematicsFaculty Mentor: Marian Gidea, Ph.D.Penghui Han explored how carefully controlled “noise,” 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. VIEW POSTER | READ STORY Linear vs. Transformer Models for Long-Horizon Exogenous Temperature Forecasting Author: Ruslan Gokhman, Ph.D. in MathematicsFaculty Mentor: Marian Gidea, Ph.D.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. VIEW POSTER Occupational Therapy Exploring Cultural Humility Among Emerging Occupational Therapistsin the U.S.: A Call for Competemility Author: Carly Ettinger, Occupational TherapyFaculty Mentor: Terrie Ludwig, OTD, OTR/LCarly 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. VIEW POSTER Freed to Function: Occupational Therapy's Role in Pre- and Post-Frenectomy Care Author: Rachel Riemenschneider, Occupational TherapyFaculty Mentor: Teresa Ludwig, OTD, OTR/L, ASDCSRachel 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. VIEW POSTER The SELf Project: A Yoga-Based SEL Program for Neurodivergent Adults Author: Sydney Ostroff, Occupational TherapyFaculty Mentors: Teresa Ludwig, OTD, OTR/L, ASDCSIndustry Partner: Grace Denfeld, OTR/LSydney 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. VIEW POSTER | READ STORY Occupational Therapy's Role in Treating Youth with Picky Eating and ARFID: An Education Guide for Parents and Caregivers Author: Vanessa Murad, Occupational Therapy DoctorateFaculty Mentor: Terrie Ludwig, OTD, OTR/L, ASDCSIndustry Partner: Anne Sinha, MOT, OTR/L, SWC, Art of LivingVanessa Murad 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. VIEW POSTER Physician Assistant Studies Does Quadruple Therapy Result in More Effective Eradication of H.Pylori? Author: Abigail Assenza, M.S. in Physician Assistant Studies Faculty Mentor: Brian Baker MD, JDAbigail 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. VIEW POSTER Speech-Language Pathology Asthma's Relationship to Speech Production in Children Author: Jemma (Shayna) Lifschitz, M.S. in Speech-Language PathologyFaculty Mentor: Elisabeth Mlawski, Ph.D., CCC-SLPJemma (Shayna) Lifschitz studied how asthma affects children’s speech production and found that breathing exercises may improve both asthma control and speech clarity. VIEW POSTER | READ STORY The Role of Prenatal Alcohol Exposure and Its Implications on Cognition and Language Across the Lifespan Author: Shirah Niknam, M.S in Speech-Language Pathology Faculty Mentor: Marissa A. Barrera, Ph.D., MSCS, CCC-SLPShirah Niknam examined how prenatal alcohol exposure affects language, memory and executive functioning throughout life, emphasizing the importance of long-term speech-language support. VIEW POSTER | READ STORY SLP in Pre-Hospital Stroke Care: Evaluating EMS Accuracy in Identifying Aphasia and Dysarthria and Its Impact on Patient Outcomes Author: Jennifer Schneider, M.S. in Speech-Language PathologyFaculty Advisor: Marissa A. Barrera, Ph.D., MSCS, CCC-SLPIn 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. VIEW POSTER Hush is Harm? Debunking Whispering Myths in Voice Therapy Author: Nicole Aziz, M.S. in Speech-Language PathologyFaculty Advisor: Andrew Christler, MBA, MA, CCC-SLPNicole Aziz investigated whether whispering truly harms the voice and found that scientific evidence remains mixed, challenging long-standing assumptions in voice therapy. VIEW POSTER
