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Wookhee MinView profile

Researcher

• artificial intelligence
• human-computer interaction
• educational technologies
• +4 more

Wookhee Min is a Research Scientist at the Department of Computer Science, NC State University. His work bridges artificial intelligence, human-computer interaction, and educational technologies, with a focus on game-based learning environments, multimodal learning analytics, and natural language processing for K-12 education. Research Interests : Min specializes in developing AI-driven educational tools that enhance student engagement, particularly in rural and underrepresented communities. His research integrates stealth assessment , user modeling , and multi-task learning to create adaptive learning systems tailored for diverse learners. Publication Trends : Min's recent articles emphasize AI education for middle school students, collaborative learning analytics, and the use of games to teach computational concepts. Themes include multimodal data analysis, adaptive training systems, and equitable access to STEM resources. Scientific Awards : Multiple best paper awards Grants : Min contributes to NSF-funded projects such as AI Play (2022-2026, $1.17M) and ExplainIt (2021-2026, $1.46M), focusing on AI literacy and classroom response systems. Labs & Collaborations : A senior member of the IntelliMedia Group, Min collaborates with interdisciplinary teams to advance adaptive learning technologies.

Anuj KumarView profile

Professor

• Business Value of Information Technology
• Digital Goods Markets
• Information Technology Enabled Multi-Channel Service Operations
• +4 more

Anuj Kumar serves as the Walter J. Matherly Professor of Information Systems at the Warrington College of Business, University of Florida, within the Information Systems and Operations Management Department. His academic journey spans prestigious institutions in India and the United States, culminating in a PhD from Carnegie Mellon University. Dr. Kumar earned his PhD in Information Systems Management from the Heinz College at Carnegie Mellon University (2011), an MBA from the Indian Institute of Management (2006), an MTech in Thermal Engineering from the Indian Institute of Technology (1992), and a BE in Mechanical Engineering from the Indian Institute of Technology Roorkee (1990). His research centers on understanding how information technology influences human behavior and organizational outcomes across three primary domains: omnichannel customer behavior in technology-mediated environments, the economic value of algorithmic recommendation systems, and the societal impact of information technology. Dr. Kumar has developed an AI-enabled platform called EPInc to identify students' knowledge gaps and facilitate peer learning, which has been implemented in K-12 schools across India, benefiting thousands of students. His work on multichannel customer behavior examines how consumers interact with businesses across different channels for various products and services. Dr. Kumar's publication record demonstrates consistent high-impact contributions to top-tier journals including Management Science, Information Systems Research, Manufacturing & Service Operations Management, and Management Information Systems Quarterly. His research on product recommendation networks has shown these systems can increase product page views by 7.5% and sales revenue by 11% on average, with even greater impact for products at the 'center of the network.' His work spans theoretical foundations of information systems while maintaining strong practical relevance to business operations and societal challenges. INFORMS ISS Sandra A. Slaughter Early Career Award (2018) First runner-up award for INFORMS-Industry Studies Association Best Paper Prize Wharton Customer Analytics Initiative Research Grant Marketing Science Institute Research Grant Best Reviewer award at Sixteenth Conference on Information Systems and Technology Dr. Kumar has advised numerous PhD students including Xinyu Zang, Zhechao Yang, Maxim Terekhov, Youhyun Lee, Lucy Zhang, and Xiang Wan. His research has received competitive funding from the Marketing Science Institute and Wharton Customer Analytics Initiative. He serves as an Associate Editor for Information Systems Research and has reviewed for prestigious journals including Management Information Systems Quarterly and Management Science. His EPInc platform represents a significant applied contribution, creating peer-driven learning in K-12 classrooms, particularly benefiting underprivileged students in Indian schools.

Bashir I. MorshedView profile

Associate Professor

• Mobile Health
• Wearable Sensors
• Artificial Intelligence in Healthcare
• +4 more

Dr. Bashir I. Morshed serves as Associate Professor in the Department of Computer Science at Texas Tech University, where he directs research at the intersection of wearable electronics and artificial intelligence for healthcare applications. His work pioneers inkjet-printed flexible sensors and edge-computing AI systems for real-time physiological monitoring, with significant contributions to cardiac arrhythmia detection and mobile health diagnostics. His academic foundation includes: B.Sc. in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology (2001) M.A.Sc. in Electrical and Computer Engineering from University of Windsor, Canada (2004) Ph.D. in Electrical and Computer Engineering from Carleton University, Canada (2010) Dr. Morshed's research program centers on body-worn electronic patch sensors developed through inkjet printing technology , enabling novel applications in mobile health . His lab creates dry flexible electrodes for ECG/EMG monitoring, wireless sensor systems using conjugate coils, and edge-AI classifiers that operate directly on wearable devices. Current projects focus on real-time seizure detection from EMG signals, respiratory pattern classification using multi-stage AI, and severity assessment of cardiac conditions through beat-by-beat ECG analysis. This work bridges biomedical engineering and computer science to solve critical challenges in continuous health monitoring. Analysis of his 2024-2025 publications reveals dominant trends in resource-constrained edge AI for healthcare, with 80% of recent work focusing on cardiac monitoring systems. His research demonstrates exceptional consistency in developing beat-by-beat analysis frameworks that extract maximal diagnostic value from minimal sensor inputs. Key innovations include fusion features combining signal-specific and signal-independent characteristics, transformer neural networks adapted for physiological time-series, and GAN-enhanced models for robust performance with limited training data. These approaches consistently prioritize clinical deployability through ultra-low power consumption and smartphone-compatible processing. His scientific recognition includes: Canadian Commonwealth Fellowship 2018 MHTI Scholar award from NIH mHealth Summer Training Institute at UCLA Senior Membership in IEEE Dr. Morshed has produced over 30 journal articles, 100+ conference publications, and 3 patents, demonstrating prolific scholarship in wearable health technology. His research group actively develops the BRAINsens platform (Body-worn Reconfigurable Architecture of Integrated Network Sensors) for modular physiological monitoring. While specific student mentorship details aren't documented in source materials, his work shows strong collaboration with medical researchers through NIH-funded initiatives like the mHealth Summer Training Institute. He maintains active involvement in STEM education through Texas Tech's STEM CORE program, recently developing virtual approaches to build STEM confidence as evidenced by his 2025 publication on the topic. His laboratory operations focus on inkjet-printed flexible electronics fabrication and edge-AI validation using medical datasets. Current infrastructure supports printing of silver-ink electrodes on polyimide substrates, characterization of MIM capacitors, and development of portable scanners for wireless resistive analog passive (WRAP) sensors. The team maintains strong industry connections through patents in wearable ECG systems and conjugate coil signal capture, with several technologies transitioning toward clinical deployment.

• Chemical Engineering
• Fluidized Bed Reactors
• Chemical Reactor Design
• +8 more

Katarzyna Danuta Bizon serves as an Associate Professor in the Department of Chemical and Process Engineering within the Faculty of Chemical Engineering and Technology at Cracow University of Technology. Her academic profile demonstrates deep expertise in chemical engineering with a focus on reactor design, process optimization, and advanced modeling techniques. She maintains an active research program evidenced by 86 publications and significant bibliometric indicators including an h-index of 12 (Scopus) and total Impact Factor of 61.1. Her research interests center on fluidized bed reactors, combustion systems, model reduction methodologies, and diffusion processes in porous media. She investigates energy systems, imaging techniques for process analysis, and optimization of hybrid reactor configurations. Current work emphasizes carbon dioxide capture technologies, reaction-diffusion dynamics, and the application of reduced-order modeling to complex chemical processes. Her methodology integrates computational simulations with experimental validation to address challenges in environmental protection and energy efficiency. Analysis of her recent publications (2022-2024) reveals three dominant research thrusts: (1) Advanced CO 2 capture using structured sorbents and hybrid fixed-bed reactors, (2) Development of reduced-order modeling techniques (POD/DEIM) for reaction-diffusion systems, and (3) Fundamental studies of bubble dynamics and multicomponent diffusion in membrane systems. This work consistently bridges theoretical modeling with practical applications in emission control and process intensification. Dr. Bizon has successfully supervised 2 PhD students to completion, demonstrating her commitment to academic mentoring. Her research is supported by the infrastructure of Cracow University of Technology's Department of Chemical and Process Engineering, where she contributes to both fundamental research and applied process engineering solutions.

• Automatic Control
• Systems Engineering
• Neural Networks
• +4 more

Laurent Signac is an Associate Professor in Automatic Control and Systems at ENSIP (École Nationale Supérieure d'Ingénieurs de Poitiers), part of the University of Poitiers. He maintains dual affiliations with the LIAS laboratory at both ENSIP in Poitiers and ISAE-ENSMA in Chasseneuil, contributing to the Automatic Control, Data Engineering, and Real Time research teams. His research spans automatic control, neural networks, and artificial intelligence with applications in industrial fault detection, robotics, and algorithmic problem-solving. Key contributions include neural network-based stator fault diagnosis in induction motors, fractional-order system identification, and explorations of algorithmic survival mechanisms. His work bridges theoretical control systems with practical engineering solutions across electrical engineering and computer science domains. Analysis of his publication timeline reveals consistent innovation in neural system identification (2001-2009), evolving toward interdisciplinary applications in cryptography (2013), light diffusion modeling (2014), and computational thinking education (2017). His research demonstrates sustained integration of control theory with neural computation across industrial, biological, and educational contexts. As a core member of LIAS laboratory's Automatic Control team, he participates in France's national research ecosystem focused on signal processing and real-time systems. The laboratory's dual-campus structure facilitates collaboration between ENSIP's engineering programs and ISAE-ENSMA's aerospace expertise, positioning his work at the intersection of academic research and industrial application.

• Operations Management
• Healthcare Analytics
• Pharmaceutical Industry
• +4 more

Ujjal Mukherjee is an Associate Professor of Business Administration at the Gies College of Business, University of Illinois Urbana-Champaign. His research spans interdisciplinary domains, with a focus on operational strategies in healthcare systems, pharmaceutical innovations, and data-driven decision-making in complex environments. He holds a leadership role in advancing methodologies for predictive analytics and computational drug discovery, with notable contributions to understanding drug resistance mechanisms in oncology. Dr. Mukherjee’s work integrates quantitative approaches from operations research, epidemiology, and bioinformatics. His recent studies address critical challenges such as optimizing testing strategies for pandemic control, modeling product recall decision-making in supply chains, and developing algorithms to identify novel drug combinations for treatment-resistant cancers. He collaborates extensively with medical institutions and public health agencies, contributing to real-world solutions for healthcare delivery and crisis management. Research Themes: Drug Resistance Mechanisms, Epidemic Modeling, Predictive Analytics, Operations in Healthcare, Computational Biology Affiliations: Gies College of Business, University of Illinois Contact: 306 Wohlers Hall, Champaign, IL | ukm@illinois.edu His publications demonstrate a commitment to translational research, bridging theoretical frameworks with practical applications in both business and life sciences domains. Current projects include optimizing school reopening strategies during pandemics and enhancing precision medicine through single-cell omics integration.

Gaurav ChopraView profile

Professor

• Artificial Intelligence
• Immunology
• Neurodegeneration
• +7 more

Gaurav Chopra is the James Tarpo Jr. and Margaret Tarpo Professor of Chemistry at Purdue University, part of the College of Science's Department of Chemistry. His research integrates artificial intelligence (AI), experimental chemistry, and immunology to develop novel therapies for cancer and neurodegenerative diseases, with a focus on lipidomics and immunomodulation. His lab pioneered AI-driven drug discovery platforms, including the MINT virtual reality game for molecular visualization and the 'AI co-pilot' infrastructure for automated experiments. Education: Ph.D. in Computational Mathematics, Stanford University (2010) M.S. in Scientific Computing, Stanford University (2005) B.Tech in Mechanical Engineering, Indian Institute of Technology Delhi (2002) Research interests include AI in drug discovery, lipidomics, immunotherapy, and neuroimmunology. Chopra’s lab has developed tools such as single-cell lipidomics, targeted drug design, and AI-enhanced mass spectrometry. His work emphasizes translational research, bridging basic science with clinical applications in cancer and Alzheimer’s disease. Notable achievements include the 2024 Scialog Fellowship, leadership in the Merck-Purdue Center, and multiple NIH awards. He has mentored over 20 students and postdocs, fostering a diverse, inclusive lab environment. Chopra’s outreach initiatives include K-12 science education through virtual reality games and open-source software like GitHub repositories for AI-driven drug discovery. Grants and collaborations include partnerships with Indiana companies (via AnalytiXIN Fellowships) and federal funding through the NIH HEAL Initiative. His lab’s infrastructure includes advanced facilities for molecular modeling, high-throughput screening, and AI integration.

Seiji IsotaniView profile

Professor

• Artificial Intelligence in Education
• Gamification in Education
• Evidence-based Education Policies
• +3 more

Seiji Isotani is a Professor of Computer Science and Learning Technology at the University of São Paulo and a Visiting Professor at Harvard University. His research focuses on AI in Education, Gamification, and Evidence-based Policy. He holds a Ph.D. from Osaka University and a postdoc from Carnegie Mellon University. He advises government policies in Brazil, including the K-12 Computer Science Curriculum and the National Plan for Textbooks. His honors include ACM Senior Membership, IEEE Fellowships, and multiple awards for research and teaching excellence. His lab, Applied Computing in Education, explores AI-driven education equity and policy impact. Roles: Faculty Associate at Harvard’s Berkman Klein Center Education: Ph.D. (Osaka), Postdoc (CMU) Key Projects: Brazil’s National Textbook Program, Gamification Frameworks Research interests include AI for resource-constrained education, personalized gamification, and public policy design. Grants include over $5M for education tech projects. He leads teams developing systems like MeuTutor and Linkn, impacting 40M+ students.

Igor KadotaView profile

Assistant Professor

• Communication Networks
• Wireless Networks
• Full-Duplex Systems
• +6 more

Dr. Igor Kadota is an Assistant Professor of Electrical and Computer Engineering at Northwestern University's Robert R. McCormick School of Engineering and Applied Science. His research focuses on next-generation communication networks, blending rigorous theory, system implementation, and machine learning to address challenges in full-duplex systems, millimeter-wave networks, and spectrum sharing markets. He leads the Wireless Lab and is affiliated with the Communications and Networking Lab, SpectrumX, and the Trienens Institute for Sustainability and Energy. Educations: Ph.D. and S.M. in Communication Networks, MIT B.S. in Electrical Engineering, ITA, Brazil Affiliations: Communications and Networking Lab, SpectrumX, Trienens Institute Research Interests: Prof. Kadota’s work emphasizes Age of Information theory, spectrum sharing markets, full-duplex wireless systems, and drone networking. His projects include FPGA-based full-duplex prototypes, real-time adaptive algorithms, and machine learning pipelines for atmospheric sensing via millimeter-wave radar. Recent initiatives focus on bridging techno-economic gaps in spectrum zone management and deploying autonomous resource allocation strategies. Awards & Recognition: Best Student Paper Awards at WiOpt 2024 and 2025 NSF grants (SII-NRDZ-SBE, SII-NRDZ, and RINGS) Senior Member of IEEE (2024) ACM SIGCOMM 2023 SRC 1st Place Award (collaborative work) Grants & Service: Organized workshops at IFIP Performance and Asilomar Conferences Technical Program Committee member for ACM SIGMETRICS/IFIP Performance and IEEE INFOCOM Outreach initiatives include K-12 STEM programs and NSF PAWR COSMOS testbed demonstrations Labs & Teams: The Wireless Lab recruits Ph.D., Master’s, and undergraduate students to tackle interdisciplinary projects. Current openings exist in spectrum sharing algorithms, drone networks, and full-duplex hardware-software co-design.

Christina Gardner-McCuneView profile

Associate Professor

• Computer Science Education
• AI Education
• Learning Technologies
• +3 more

Dr. Christina Gardner-McCune is an Associate Professor and Director of the Engaging Learning Lab in the Department of Computer and Information Science and Engineering at the University of Florida's Herbert Wertheim College of Engineering. Her research focuses on computer science education, AI curriculum development, and learning technologies for K-12 and undergraduate education. Education: Postdoctoral Research at Georgia Institute of Technology (2012) Ph.D. in Computer Science, Georgia Institute of Technology (2011) M.S. in Computer Science, Georgia Institute of Technology B.S. in Computer Engineering, Syracuse University Research Focus: Dr. Gardner-McCune develops innovative approaches to teaching computing concepts through after-school programs, summer camps, and formal classroom settings. Her work includes creating national K-12 AI education guidelines and studying how emerging technologies can enhance computational thinking. Awards: ACM Education Advisory Committee Member (2020-2023) UF Faculty Career Influencer Award (2020) Google Faculty In Residence Fellow (2019) UF Graduate Student Champion Award (2019) Publication Trends: Recent works emphasize K-12 AI integration, VR learning environments, and equity-focused computing education, demonstrating strong alignment with national STEM education initiatives.

Daniel FreyView profile

Professor

• Robust Design
• Design of Experiments
• Adaptive Experimentation
• +3 more

Professor Daniel Frey is a Professor and current Area Head for Design and Manufacturing in the Department of Mechanical Engineering at the Massachusetts Institute of Technology (MIT). With over 25 years at MIT, he leads research in robust design methodologies and experimental techniques while maintaining deep engagement with D-Lab's mission to develop technologies for underserved communities worldwide. His work bridges theoretical engineering principles with practical applications in global development contexts. Education: B.Sc. in Aeronautical Engineering from Rensselaer Polytechnic Institute (1987) M.Sc. in Mechanical Engineering from University of Colorado at Boulder (1993) Ph.D. in Mechanical Engineering from MIT (1997) Frey's research centers on robust design and adaptive experimentation methodologies, particularly his pioneering work on one-factor-at-a-time adaptive experimentation. He extends these principles to develop medical devices and sustainable technologies for resource-constrained environments, including vaccine coolers that prevent temperature-related vaccine spoilage and Surgibox systems for maintaining sterile surgical conditions in austere settings. His D-Lab leadership (2016-2022) advanced projects in off-grid energy, mobile health technology, and agricultural innovation while emphasizing community-driven design approaches. Analysis of his recent publications reveals consistent focus on adaptive experimental frameworks that optimize design processes under uncertainty, with growing emphasis on real-world implementation challenges in developing contexts. His work increasingly integrates statistical learning techniques with traditional engineering design while maintaining core contributions to robust parameter design theory. Scientific Awards: R&D 100 Award for Software for Virtual Machining (1997) R&D 100 Award for Leveraged Freedom Chair (2010) NSF CAREER Award (2005) ASME Fellow (2013) SAE Charles M. Manly Memorial Medal (2020) Multiple teaching awards including Junior Bose Award (2006) and Teaching with Digital Technology Award (2022) 12+ best paper awards across engineering design and quality control conferences Frey actively mentors students through D-Lab projects and MIT's Electric Vehicle Team, having supervised over 10 D-Lab initiatives including the vaccine cooler development with graduate student Prithvi Sundar. As faculty advisor for USAID's $30M Comprehensive Initiative on Technology Evaluation (CITE), he secured substantial funding for technology assessment in developing countries. His SUTD-MIT International Design Center collaboration generated field-tested experimental frameworks for developing world applications, while BLOSSOMS educational videos reach global high school classrooms. Through MIT D-Lab, Frey co-developed technologies including biomass cookstoves, off-grid energy systems, and mobility devices like the Leveraged Freedom Wheelchair (R&D 100 winner). His current research focuses on Surgibox implementation and vaccine logistics, working directly with communities to ensure solutions address actual needs while respecting local innovation capacities. As Area Head for Design and Manufacturing, he shapes curriculum and research direction for one of MechE's core technical pillars.

Kathi FislerView profile

Research Professor

• Computing Education
• Formal Methods
• Data Science
• +3 more

Kathi Fisler is a Research Professor of Computer Science at Brown University, serving as Director of CS Undergraduate Studies and Research Director at Bootstrap. She holds a PhD and MS from Indiana University and a BA from Williams College. Her research focuses on computing education, formal methods, and data-centric approaches, emphasizing how people learn formal systems. She leads efforts to integrate socially-responsible computing across Brown’s CS curriculum and collaborates on Bootstrap’s K-12 outreach programs. Key projects include data-centric computing education, notional machines, and policy analysis tools like Margrave. Education: PhD in Computer Science, Indiana University (1996) MS in Computer Science, Indiana University (1992) BA in Computer Science, Williams College (1991) Research Interests: Data-centric computing education Computing education pedagogy Formal methods for hardware and security Socially-responsible computing curriculum design Bootstrap K-12 outreach initiatives Teaching: CSCI 0050: Data-Centric Programming CSCI 0200: Data Structures & Algorithms CSCI 2952B: Computer Science Education Research Awards: Best Paper Award at Koli Calling 2017 Best Paper Award at SIGCSE 2011 Labs/Teams: Brown Computing Education Research Group Bootstrap (K-12 outreach)

Kareen CoulombeView profile

Associate Professor

• Biomaterials
• Cardiac Tissue Engineering
• Regenerative Medicine
• +3 more

Kareen Coulombe is an Associate Professor of Engineering at Brown University, affiliated with the School of Engineering and the Institute for Biology, Engineering, and Medicine. She serves as Program Advisor for Biomedical Engineering and Committee Chair for the Honors Program. Her research focuses on cardiovascular regenerative engineering, leveraging biomaterials, stem cell biology, and mechanobiology to develop therapies for heart attack patients and improve cardiotoxicity assessment. She earned a B.S. in Biomedical Engineering (summa cum laude, 2001) from the University of Rochester and a Ph.D. in Bioengineering (2007) from the University of Washington, followed by an NIH postdoctoral fellowship. Notable grants include NIH R01 HL135091 and NSF CAREER Award (2021). Research Interests: Biomaterials, cardiac tissue engineering, regenerative medicine, stem cell biology, mechanobiology, and revascularization. Recent breakthroughs include a $2.8M NIH grant (2024), Hazeltine Innovation Awards (2024), and a 2023 Brown Innovation of the Year award. Her Coulombe Lab develops engineered cardiac tissues and vascularized microenvironments, with applications in toxicity testing and heart regeneration. Publications highlight advancements in collagen microfibers, anisotropic scaffolds, and 3D cardiac microtissues for arrhythmia risk assessment. Awards include the Salomon Award (2015), NSF CAREER (2021), and recognition for mentoring (2019). She teaches Biomaterials (ENGN 1490), Cardiovascular Engineering (ENGN 1520), and Cell-Material Interactions (ENGN 1931K). Grants and collaborations span NIH, AHA, and industry partners. Recent work includes developing in vitro platforms for environmental cardiotoxicity testing and optimizing vascular integration in engineered tissues. The Coulombe Lab emphasizes diversity in STEM through K-12 outreach, mentorship programs, and inclusive research practices. Labs/Teams: Coulombe Lab focuses on cardiac regeneration, with collaborations in biomaterials science and clinical translation. Key projects include heparinized alginate therapies, anisotropic scaffold design, and IVIVE modeling for toxicity prediction.

Robert BlairView profile

Lecturer

• Data Science and AI
• Educational Technology
• Teacher Agency
• +3 more

Robert Blair is a Lecturer in Computing Sciences at the University of East Anglia's School of Computing Sciences, and a member of the Data Science and AI research group. His work focuses on enhancing teacher agency through technology, with active involvement in interdisciplinary projects. Education: Not explicitly stated in text. Research interests include educational technology, teacher professional development, and the application of AI in learning ecosystems. Collaborative projects emphasize technology integration in K-12 education and place-based learning models. Recent work includes a review on psychiatric care for individuals with intellectual disabilities and autism, published in BJPsych Open . Awards: None explicitly mentioned. Advising/Grants: Co-investigator on the £1.5M ESRC-funded 'ETAT' project (2022–2025), exploring teacher agency through technology. Active collaborations with researchers in education, computer science, and healthcare. Labs/Teams: Part of the Data Science and AI group at UEA, and the ETAT interdisciplinary research team.

Jean Mohammadi-AraghView profile

Associate Professor

• Engineering Education
• Programming Skill Development
• Pedagogical Uses of Digital Systems
• +4 more

Dr. Jean Mohammadi-Aragh is an Associate Professor and Associate Department Head in the Department of Electrical and Computer Engineering at Mississippi State University (MSU), where she also serves as Director of the Bagley College of Engineering's Office of Student, Faculty, and Staff Professional Development. She holds a Ph.D. in Engineering Education from Virginia Tech (2013), and both an M.S. (2004) and B.S. (2002) in Computer Engineering from MSU. Her research focuses on engineering education innovations, including pedagogical uses of digital systems, programming skill development, and strategies to increase diversity in engineering and computing. Key areas include improving student retention through Summer Bridge programs, analyzing first-year engineering pathways, and integrating computational thinking into K-12 education using 3D visualizations. Dr. Mohammadi-Aragh has led initiatives to support transfer students, enhance academic advising, and foster inclusive learning environments. Her work emphasizes leveraging technology to improve learning outcomes and understanding student attention patterns through machine learning techniques. She collaborates with the Rural S-Stem Investigations Network Groups to advance STEM education in underserved areas. Her publications span educational interventions, student success metrics, and curriculum design, reflecting her commitment to evidence-based practices in engineering education. She actively promotes professional development for students and faculty through her directorship role in the Bagley College.