جست‌وجوی استاد و پژوهشگر

Maja J Matarićمشاهده پروفایل

استاد

• Socially Assistive Robotics
• Human-Robot Interaction
• Assistive Technology
• +۷ مورد دیگر

Maja J Matarić is the Chan Soon-Shiong Chaired and Distinguished Professor of Computer Science at the University of Southern California's Viterbi School of Engineering, with courtesy appointments in Neuroscience and Pediatrics. She serves as founding director of the USC Robotics and Autonomous Systems Center, co-director of the USC Robotics Research Lab, and Principal Scientist at Google DeepMind. Previously, she held leadership roles as USC's interim Vice President of Research (2020-2021) and Vice Dean for Research (2006-2019). Her educational background includes: PhD in Computer Science and Artificial Intelligence from MIT (1994) MS in Computer Science from MIT (1990) BS in Computer Science from University of Kansas (1987) Matarić pioneers Socially Assistive Robotics (SAR) , a field her lab named, focusing on human-robot interaction that provides assistance through social rather than physical support. Her research targets critical health and wellness challenges including post-stroke rehabilitation, autism spectrum disorder therapy, cognitive exercises for Alzheimer's patients, ADHD academic support, and mental health interventions. She develops systems modeling user engagement, personality, and motivation, with extensive real-world deployments in schools, rehabilitation centers, and homes. Analysis of her recent publications reveals dominant themes in cognitive health robotics (2025 CHI paper on LLM-powered elder care), pediatric assistive technology (2025 IDC speech therapy review), and adaptive preference modeling (2025 HRI contrastive learning work). Her research consistently bridges machine learning with human-centered design for vulnerable populations. Major scientific recognition includes: ACM Athena Lecturer Award (2024) ACM Eugene L. Lawler Humanitarian Award (2024) ACM Fellow (2020) Presidential Mentoring Award (2011) Multiple society fellowships (AAAS, IEEE, AAAI) As a dedicated mentor, Matarić has championed underrepresented groups through CRA-W, placing numerous women in faculty positions. She leads USC Viterbi's K-12 STEM Outreach Program serving low-income Los Angeles schools and authored The Robotics Prime for student education. Her research has secured significant funding enabling real-world technology transfer, with documented impact in rehabilitation centers and homes through deployable SAR systems. Her Robotics Research Lab at USC drives innovation in embodied AI, with current projects spanning LLM-integrated elder care robots, ADHD academic companions, and autism therapy systems. The lab emphasizes co-design with end-users and rigorous real-world validation across diverse populations.

• Artificial Intelligence
• Natural Language Processing
• Multimodal Dialogue Processing
• +۶ مورد دیگر

Cecilia O. Alm is a Professor in the Department of Psychology within the College of Liberal Arts at Rochester Institute of Technology (RIT), where she serves as the Artificial Intelligence Program Director. She holds multiple leadership roles including Director of the Center for Human-aware AI and Director of the Computational Linguistics and Speech Processing Lab (CLaSP). Her institutional affiliations span the School of Information, Ph.D. Programs in Cognitive Science and Computing and Information Sciences, Department of Computer Science, and MS in Data Science program. Dr. Alm earned her Ph.D. from the University of Illinois at Urbana-Champaign. Her research focuses on human-centered artificial intelligence with particular emphasis on linguistic and multimodal sensing, affective computing, and natural language processing. She investigates how AI systems can better understand and respond to human communication through multimodal dialogue processing, with applications in accessibility, education, and healthcare. Her recent publications demonstrate a strong trend toward developing inclusive AI systems, particularly through projects addressing Deaf community needs (MULTICOLLAB-ASL), subtle emotion recognition (FUSE corpus), and bias mitigation in NLP. The work consistently integrates multimodal data streams (speech, gaze, gesture) to create more responsive human-AI interaction frameworks. Current research directions emphasize diversity in AI education, visual prosody in sign languages, and human-in-the-loop AI development. Dr. Alm leads several significant NSF-funded initiatives including the AWARE-AI program, IRES AI-PROWIL international research experience, and collaborative projects with Gallaudet University focused on Deaf scientist-centered AI research. She has secured over $2.5 million in external funding for her work on human-aware AI systems. She directs the CLaSP lab which provides research opportunities for PhD, MS, and undergraduate students, with graduates employed at major technology companies including Amazon, Apple, Microsoft, and Facebook. The lab focuses on real-world AI applications in accessibility, human-robot interaction, and multimodal communication systems.

Mehrdad Nojoumianمشاهده پروفایل

دانشیار

• Security
• Privacy
• Trust
• +۱۰ مورد دیگر

Mehrdad Nojoumian is an Associate Professor at Florida Atlantic University's College of Engineering and Computer Science, specializing in Security, Privacy, Trust, and Human-Autonomy Interaction. His research bridges computer science with FinTech and autonomous systems, focusing on cryptographic protocols, blockchain, and IoT security. PhD, University of Waterloo (Computer Science, 2012) MSc, University of Ottawa (Computer Science, 2007) BSc, Islamic Azad University (Computer Engineering, 2002) His research explores privacy-preserving mechanisms in autonomous systems, trust modeling in blockchain, and cross-disciplinary applications of cryptography. Recent work includes patents on adaptive driving modes and ongoing studies on IoT vulnerabilities and autonomous coordination. Notable awards include the Excellence and Innovation in Undergraduate Teaching Award (2023), NAI Induction (2022), and multiple Best Paper Awards . His publications span journals like Information and Computation and conferences such as GameSec and IEEE Blockchain . He mentors graduate students in cybersecurity bootcamps, high school outreach programs, and collaborative research projects funded by NSF , ARO-AFOSR , and AFRL . His lab emphasizes diversity and inclusion, particularly supporting underrepresented groups in STEM.

Gerry Dozierمشاهده پروفایل

استاد

• Artificial Intelligence
• Cyber Security
• Computational Intelligence
• +۶ مورد دیگر

Gerry Dozier is the Charles D. McCrary Eminent Chair Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering. His research focuses on artificial intelligence, computational intelligence, cybersecurity, identity science, and cyber identity protection. He leads initiatives like the Center for Artificial Intelligence and Cybersecurity Engineering and contributes to Alabama's AI policy through the state commission. Dr. Dozier holds a Ph.D. from North Carolina State University and has pioneered work in adversarial machine learning, biometric security, and low-resource language NLP. Education: Ph.D. Computer Science, North Carolina State University (Raleigh) M.S. Computer Science, North Carolina State University (Raleigh) B.S. Computer Science, Northeastern Illinois University Research Themes: Combines AI with cybersecurity to address modern digital challenges. Specializes in adversarial attacks/defenses, biometric authentication systems, and ethical NLP applications in multilingual contexts. Active in developing tools for sentiment analysis in underrepresented languages and mitigating biases in automated systems. Impact: Spearheaded Auburn's AI@AU initiative with lecture series and forums. Collaborates internationally on facial recognition, malware detection, and medical AI applications like bacterial vaginosis diagnosis. His work bridges theoretical CS advancements with real-world security and ethical considerations. Labs/Teams: Directs Auburn's AI & Cybersecurity Engineering Center and contributes to interdisciplinary groups like the McCrary Institute for Cyber and Critical Infrastructure Security.

• Computer Science Education
• AI in Education
• AI Literacy
• +۵ مورد دیگر

Michael O'Dea is a Senior Lecturer in the Department of Computer Science at the University of York, United Kingdom. He has held previous academic positions at York St John University, Beijing University of Technology, University of Hull, and Waikato Institute of Technology, bringing extensive international experience in computer science education. He is actively engaged in pedagogical scholarship and leadership in higher education innovation. Senior Lecturer, Department of Computer Science, University of York Senior Lecturer in Computer Science, York St John University Lecturer in Software Engineering, Beijing University of Technology, China Lecturer in Computer Science, University of Hull Lecturer in Information Technology, Waikato Institute of Technology, NZ Dr. O'Dea earned his Ed.D. in Computer Based Learning from the University of Leeds. His research centers on the integration of artificial intelligence into educational practices, with a strong emphasis on AI literacy, the effectiveness of generative AI in teaching and learning, and the evolving landscape of technology acceptance in higher education. He investigates how AI tools can enhance student learning, faculty development, and institutional policy. His recent publications span topics such as AI literacy assessment, the future of online and blended learning, the application of machine learning in earthquake prediction, and international study abroad effectiveness. These works reflect a broad interdisciplinary approach, combining computer science, educational theory, and policy analysis. His scholarship is increasingly focused on the transformative potential of generative AI in academic settings, as evidenced by his leadership in special journal issues and funded research projects. Dr. O'Dea holds significant editorial responsibilities as Associate Editor and Lead Guest Editor for the Journal of University Teaching and Learning Practice and as Guest Editor for a special issue in Education Sciences on generative-AI-enhanced learning. He is also an Invited External Academic Affiliate at the King's Institute for Artificial Intelligence, King's College London. Associate Editor - Special Issues, Journal of University Teaching and Learning Practice Lead Guest Editor, Special Issue on Technology Acceptance Models, JUTLP (2024) Guest Editor, Special Issue on Generative-AI-Enhanced Learning, Education Sciences Principal Investigator, QAA Collaborative Enhancement Project on Graduate Attributes in the Era of GenAI (2025) He has delivered numerous invited talks and workshops at institutions such as the University of York, Queen Mary University of London, and international conferences including the Academy of Management and the International Conference on Artificial Intelligence in Education. His work bridges research, practice, and policy in higher education, with a strong commitment to inclusive and innovative teaching methodologies.

• Data Governance
• Computer Supported Collaborative Learning
• Student Persistence
• +۴ مورد دیگر

Dawn Laux serves as Assistant Dean of Academic Programs and Professor of Practice in the School of Applied and Creative Computing at Purdue Polytechnic Institute, Purdue University. She concurrently holds the position of Division Head for Military Science and Technology and chairs the Purdue University Teaching Academy. With over 15 years of service since 2007, Dr. Laux teaches undergraduate information governance courses and has earned recognition including the Charles B. Murphy Award for Outstanding Undergraduate Teaching (2019) and induction into Purdue's Book of Great Teachers (2023). Her educational background includes: PhD in Human Computer Interaction, Iowa State University (2014) MS in Management Information Systems, Iowa State University (2007) BS in Business Education and Office Administration, Ball State University (1994) Dr. Laux's research centers on data governance, computer-supported collaborative learning, and student persistence in technology education. She investigates technology acceptance, recruitment of women and minorities into IT, database management, and information governance frameworks. Her work bridges educational theory with practical applications to enhance student engagement and diversity in computing fields. Analysis of her publications (2011-2016) reveals consistent focus on educational technology interventions, particularly examining virtual communities for student persistence, diversity initiatives in computing, and classroom technology adoption. Her research demonstrates interdisciplinary integration of information systems, educational psychology, and social computing principles with practical applications in higher education settings. Her distinguished recognition includes: Book of Great Teachers, Purdue University (2023) Academic Leadership Program Fellow, Big Ten Academic Alliance (2022-2023) Teaching Academy Member, Purdue University (2019) Charles B. Murphy Award for Outstanding Undergraduate Teaching (2019) College of Technology Exceptional Early Career Teaching Award (2014-2015) Teaching for Tomorrow Fellowship Award (2013-2014) Bringing 10 years of pre-academic industry experience from Purdue Employees Federal Credit Union and Insight Communications, Dr. Laux integrates practical IT expertise into her teaching and leadership. Her administrative roles encompass academic program oversight and military technology education initiatives, supported by her active participation in the National Center for Women and Information Technology Academic Alliance since 2011. As Division Head of Military Science and Technology, Dr. Laux leads specialized technology education programs while chairing the university-wide Teaching Academy to advance pedagogical excellence across Purdue's academic units.

• Human Activity Recognition
• Wearable Sensors
• Machine Learning
• +۴ مورد دیگر

Thomas Ploetz is an Adjunct Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology. His work focuses on sensor-based human activity recognition, wearable computing, and computational behavior analysis with applications in healthcare, smart homes, and education. He leads interdisciplinary research integrating machine learning, IoT systems, and human-centered design. His research interests include improving activity recognition robustness through synthetic data generation, developing explainable AI for time-series analysis, and advancing healthcare technologies like diabetic foot ulcer monitoring systems. He explores ethical implications of wearable sensing in diverse populations, including underrepresented groups. Key contributions include IMUTube (virtual sensor data generation), ProxiCycle (cyclist safety monitoring), and DISCOVER (smart home activity recognition framework). His work addresses challenges in data scarcity, domain adaptation, and long-term system maintenance in pervasive computing environments. He has been awarded grants such as the GVU/IPaT Research and Engagement Grant (2020), and his research appears in top venues like UbiComp and ISWC. He actively contributes to the wearable computing community through conference organization and editorial work.

• Natural Language Processing
• Explainable AI
• Fact-Checking
• +۴ مورد دیگر

Isabelle Augenstein is a Professor at the University of Copenhagen, Department of Computer Science (DIKU), where she heads the Copenhagen Natural Language Understanding (CopeNLU) research group and the Natural Language Processing section. She is also a co-lead of the Danish Pioneer Centre for Artificial Intelligence, Denmark's largest research center initiated by the Danish Ministry of Higher Education and Science. In October 2022, she became Denmark's youngest ever female full professor. Dr. Augenstein earned her undergraduate degree in Computational Linguistics and Psychology from Heidelberg University, followed by a Master's in Computational Linguistics. She completed her PhD in Computer Science at the University of Sheffield under the supervision of Dr. Diana Maynard and Prof. Fabio Ciravegna. In 2021, she earned a Habilitation at the University of Copenhagen in Explainable Fact-checking. Professor Augenstein's primary research focuses on fair and accountable Natural Language Processing, with particular emphasis on explainability, factuality, and bias detection. Her work spans multiple subfields including automated fact-checking, stance detection, gender bias analysis, and cultural bias in language models. She has pioneered research in explainable fact-checking, developing methods that not only predict claim veracity but also provide meaningful explanations of the decision-making process. Her research group has produced numerous influential papers on measuring model fragility, quantifying gender biases, and developing robust fact-checking systems that account for distribution shifts. Her significant contributions have been recognized with several prestigious awards: ERC Starting Grant on 'Explainable and Robust Automatic Fact Checking' DFF Sapere Aude Research Leader fellowship on 'Learning to Explain Attitudes on Social Media' Karen Spärck Jones Award from the British Computing Society and Bloomberg Hartmann Diploma Prize from the Hartmann Foundation Member of the Royal Danish Academy of Sciences and Letters since 2024 Professor Augenstein has secured significant research funding including her ERC Starting Grant supporting five years of blue-sky research. She actively mentors PhD students and postdoctoral researchers through her 'ExplainYourself' project. She served as President of SIGDAT (which organizes the EMNLP conference series), having previously held leadership roles as Vice President and Vice President-Elect. She is a co-founder of Widening NLP (WiNLP), an initiative to increase diversity in the NLP community, and maintains the BIG Directory of underrepresented groups in NLP. She leads the Copenhagen Natural Language Understanding (CopeNLU) research group, which relocated to the historic Østervold Observatory in Copenhagen's Botanical Gardens in 2023. The group focuses on developing methods for explainable and robust natural language understanding, with applications in fact-checking, bias detection, and social media analysis. Professor Augenstein also co-leads the Speech and Language collaboratory at the Pioneer Centre for Artificial Intelligence, where her team investigates how language models can better serve diverse populations while maintaining accountability and transparency.

Daniel Harrisonمشاهده پروفایل

استادیار

• Human-Computer Interaction (HCI)
• Digital Health
• Inclusive Technology Design
• +۳ مورد دیگر

Dr. Daniel Harrison is an Assistant Professor in the School of Design, Arts, and Creative Industries at Northumbria University, where he serves as EDI and Athena SWAN Co-Lead and leads the HCI+Design Research Group. His academic journey includes a PhD from UCL's Interaction Centre (UCLIC) and research at Georgia Institute of Technology and Microsoft Research Cambridge. His work focuses on Human-Computer Interaction (HCI), digital health, and inclusive technology design, particularly in sports and wellbeing. Education: PhD in Human-Computer Interaction, UCL Interaction Centre (2020) MSc (2012), BSc (Hons) (2010) Research Interests: Intersection of technology, inclusivity, and sports (SportsHCI) Participatory methods (co-design, ethnography) Developing inclusive technologies for underrepresented groups Recent Projects: Co-authored Grand Challenges in SportsHCI Initiatives for inclusive sports technology Design of wellbeing-focused digital tools Advising: Mentors three PhD students researching topics such as neurodivergent workers, financial technology for international students, and gamified sports participation. Labs/Teams: HCI+Design Research Group at Northumbria University.

Shirin Nilizadehمشاهده پروفایل

دانشیار

• Cybersecurity
• Privacy
• Social Media Analysis
• +۷ مورد دیگر

Dr. Shirin Nilizadeh is an Associate Professor in the Department of Computer Science and Engineering at The University of Texas at Arlington's College of Engineering. She leads the Security and Privacy Research Lab, conducting interdisciplinary research at the intersection of cybersecurity, privacy, machine learning, and social media analysis. Her work addresses critical societal issues related to online security, privacy, and safety through data-driven approaches. Dr. Nilizadeh received her PhD in Computer Science from Indiana University in 2014, followed by MS in Computer Science from Amirkabir University (2007) and BS in Computer Engineering from Islamic Azad University (2004). Her research focuses on security and privacy in systems and social networks, employing techniques from machine learning and big data analytics. She takes a highly interdisciplinary approach, integrating AI, NLP, social sciences, and public health to address societal issues in cybersecurity and privacy. Her research objectives include: (1) detecting and characterizing emerging threats in online social networks like social engineering attacks, misinformation, and online hate speech; (2) advancing the adversarial robustness and fairness of ML and NLG systems; and (3) studying humans' online behaviors through data-driven interdisciplinary research. Analysis of her recent publications reveals a strong focus on AI-generated security threats, particularly phishing scams using LLMs, NFT fraud detection, social media toxicity analysis, and content moderation systems. Her work bridges theoretical security research with practical applications, often addressing real-world security challenges through innovative technical solutions. Among her notable scientific achievements are the prestigious NSF CAREER award (2023), Comcast Innovation Awards (2022 and 2024), College of Engineering Outstanding Early Career Research award (2024), and IEEE SP 2024 Distinguished Paper Award. Her work has also received best paper and technical poster awards at eCrime 2021 and NDSS 2022. Dr. Nilizadeh has successfully mentored numerous doctoral and master's students while securing significant research funding, including multiple NSF grants and Comcast Innovation Fund awards. She leads a vibrant research group that has produced impactful work cited in official reports submitted to The Supreme Court and the EU Committee on Civil Liberties, Justice, and Home Affairs. Her lab has also received coverage from WIRED, MIT Technology Review, Orange's Hello Future, and Communications of the ACM. She serves on numerous program committees for top international conferences including ACM CCS, USENIX Security, and POPETS, and has organized outreach programs like OurCS@DFW to broaden participation of underrepresented students in computing.

Paul Ralphمشاهده پروفایل

استاد

• Software Engineering
• Empirical Software Engineering
• Human-Computer Interaction
• +۱۷ مورد دیگر

Dr. Paul Ralph is a Professor in the Faculty of Computer Science at Dalhousie University , where he leads the Dalhousie Software Engineering Lab (DalSEL) . His work bridges software engineering, human-computer interaction, and project management, with a focus on empirical research and social sustainability in software development. Education: PhD in Computer Science, University of British Columbia BSc in Computer Science, Memorial University BComm in Business, Memorial University Dr. Ralph's research centers on the sociotechnical aspects of software engineering , particularly how team dynamics, ethics, and human factors influence software success. He rejects pseudoscientific models like Waterfall and SDLC, and avoids AI/ML/data science, instead emphasizing rigorous qualitative and quantitative human-participant studies. His lab is known for its work on socially sustainable software engineering and evidence standards in computing research. His recent publications reflect a strong trend toward methodological rigor, ethical computing, and human-centered practices . Themes include empirical standards, agile methods, requirements engineering, and the social impact of technology. He publishes in top venues like IEEE TSE and ICSE , and has authored over 80 scholarly works. Scientific Awards and Recognition: Award-winning scientist (multiple unspecified awards) Editor-in-Chief, SIGSOFT Empirical Standards for Software Engineering Research Dr. Ralph is actively involved in mentoring and funding graduate students , particularly through external scholarships like NSERC, Killam, and Banting. He prioritizes applicants from underrepresented groups and emphasizes original, non-AI-generated work. His lab offers strong industry connections, professional development, and support for tenure-track aspirations among postdocs. Labs and Research Groups: Dalhousie Software Engineering Lab (DalSEL) : Focuses on empirical, human-centered software engineering research, with active projects in social sustainability and evidence standards.

• Human-Computer Interaction (HCI) Education
• Inclusive Design
• Computing Education Research
• +۳ مورد دیگر

Alannah Oleson is an Assistant Professor in the Department of Computer Science at the University of Denver's Ritchie School of Engineering and Computer Science. Her work focuses on inclusive design, computing education, and addressing equity issues in technology. She is actively involved in the KIHA Innovation Labs, exploring human-centered approaches to computing education and HCI. Her research investigates how demographic factors influence learning outcomes in computing courses, develops pedagogical methods for teaching inclusive design (e.g., the CIDER framework), and examines the ethical implications of technology in K-12 and university settings. Notable areas include algorithmic fairness, gender bias in software systems, and culturally responsive computing education for underrepresented groups. Dr. Oleson's research emphasizes practical methods for integrating critical thinking into software design processes, with recent work exploring peer feedback systems for equity analysis in large courses and curriculum reforms to promote ethical awareness. Her contributions bridge theory and practice, aiming to make computing education more equitable and socially responsible.

Shaundra B. Dailyمشاهده پروفایل

استاد

• Identity-inclusive computing
• Human-centered design & engineering
• Justice-centered STEM education
• +۵ مورد دیگر

Shaundra 'Shani B' Daily serves as the Cue Family Professor of the Practice in the Department of Electrical and Computer Engineering at Duke University's Pratt School of Engineering. She also holds appointments as Professor of the Practice of Computer Science and serves as Faculty Director of the Duke Technology Scholars program. As a core faculty member in Innovation & Entrepreneurship and one of Duke's inaugural Levitan Faculty Fellows, Daily plays a pivotal role in connecting faculty with undergraduate residential life through the QuadEx initiative. Daily's educational background includes a Ph.D. from the Massachusetts Institute of Technology (2010), an S.M. from the MIT Media Lab, and B.S. and M.S. degrees in Electrical Engineering from the Florida Agricultural and Mechanical University – Florida State University College of Engineering. Her academic journey includes previous positions as an Associate Professor with tenure at the University of Florida (2015-2017) and Associate Professor in the School of Computing at Clemson University (2011-2015). Daily's research focuses on analyzing, designing, and building sociotechnical systems to support meaningful participation and success in STEM fields. Her work encompasses four interconnected strategies: understanding sociotechnical ecosystems through mixed methods approaches; employing participatory approaches that empower communities to shape technology development; designing technologies that enhance emotional development and interpersonal skills; and building supportive infrastructure through programs and curricula. Her research areas include identity-inclusive computing, human-centered design and engineering, and justice-centered STEM education, with particular emphasis on creating pathways for historically underrepresented groups in computing. Analysis of Daily's recent publications reveals a consistent focus on embodied approaches to computational thinking education, particularly through dance and movement-based learning. Her work bridges computer science education with affective computing, exploring how technologies can support emotional development while teaching technical skills. A significant thread throughout her research is the development of inclusive computing environments that address systemic barriers faced by women and underrepresented minorities in STEM fields. Educator of the Year, ACHI Magazine (2022) Program of the Year, CoNECD Conference (2022) North Carolina Black STEM Leaders, Governor Roy Cooper (2022) Capers and Marion McDonald Award for Excellence in Mentoring and Advising, Pratt School of Engineering (2021) Undergraduate Mentor of the Year, Mary Lou William Center for Black Culture (2020) Technology, Instruction, Cognition and Learning Early Career Research Award, American Education Research Association (2015) Daily has secured over $40 million in funding from public and private sources to support her collaborative research activities. Notable recent grants include the NSF INCLUDES Alliance: The Alliance for Identity-Inclusive Computing Education ($10 million), the AI Institute: Athena, and The Alliance for Interdisciplinary Innovation in Computing Education-Postdoctoral Research Fellowship. As Faculty Director of Duke Technology Scholars, she oversees a program providing comprehensive support for students from underrepresented backgrounds. Daily also serves as Education and Workforce Director for the Athena AI Institute and was appointed to develop competencies for the National Academies' Future Of Data And Computing Committee. Through her work with the Alliance for Identity-Inclusive Computing Education and the Duke Technology Scholars program, Daily has established herself as a leader in creating supportive infrastructure for learners to thrive in STEM. Her approach combines technology development with programmatic interventions to address systemic barriers in computing education. As a Levitan Faculty Fellow, she continues to bridge the gap between academic research and residential student life, creating opportunities for meaningful faculty-student connections that support intellectual and personal development.

Brent Lagesseمشاهده پروفایل

دانشیار

• Cybersecurity
• Machine Learning
• Pervasive Computing
• +۶ مورد دیگر

Brent Lagesse is an Associate Professor at the University of Washington - Bothell , affiliated with the Division of Computing & Software Systems under the School of Science, Technology, Engineering & Mathematics . His research focuses on security in emerging environments , particularly secure machine learning and privacy in sensor-rich systems . Ph.D. in Computer Science from the University of Texas at Arlington (2009) Research Interests include: Detecting and locating hidden webcams Scalable AI/ML defense mechanisms Privacy-preserving video sharing AI systems for air quality prediction Automated yeast cell analysis CRISPR/CAS9 guide-donor libraries Article Trends : Recent publications emphasize secure machine learning for smart city applications, privacy-preserving technologies , and resource-constrained security in crowdsensing environments . Collaborative work spans cybersecurity education , environmental monitoring , and context-aware systems . Scientific Awards : Cybersecurity Fulbright Scholar (University of Cambridge, 2018) Johann-von-Spix International Guest Professorship (University of Bamberg, 2019-20) Advising & Grants : Advises current research students Neil Prakasam and Nicholas Handaja NSA grant ($96k) for GenCyber curriculum development (2022) NSF grant ($300k) for AI-enhanced cybersecurity workforce studies (2021) T-Mobile grants for ML security metrics and dataset anonymization (2020-2022) Laboratory : Leads the Security of Emerging Environments (SEE) Lab , developing practical and theoretical frameworks for smart city security and privacy-preserving technologies .

Cheryl Sealsمشاهده پروفایل

استاد

• Artificial Intelligence
• Natural Language Processing
• Educational Technology
• +۴ مورد دیگر

Cheryl Seals is the Charles W. Barkley Endowed Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering. She holds a Ph.D. in Computer Science from Virginia Tech, with additional degrees from Virginia Tech, North Carolina A&T State University, and Grambling State University. Her research focuses on AI ethics, natural language processing (NLP), virtual reality (VR) applications in healthcare and education, and promoting diversity in STEM. She leads initiatives like the NSF-funded AI ethics education project and the Institute for African Americans in Computing Sciences (IAAMCS). Notable awards include the Charles W. Barkley Professorship (2020) and participation in Drexel’s ELATES fellowship program. Her work bridges technology and social impact, including VR-based empathy training for medical students and interventions to mitigate pandemic-induced learning loss. She collaborates on interdisciplinary projects, such as automated grading tools for speech therapy and pavement crack recognition systems. Education: Ph.D. Computer Science, Virginia Tech M.S. Computer Science, Virginia Tech M.S. Software Engineering, North Carolina A&T State University B.S. Computer Science, Grambling State University Research Interests: AI Ethics and STEM Education Reform NLP for Sentiment Analysis and Hate Speech Detection VR Applications in Healthcare Training and Empathy Development Computing Equity and Underrepresented Groups Interdisciplinary Tools for Education and Accessibility Awards and Recognition: Charles W. Barkley Endowed Professor (2020–2025) ELATES Fellowship Participant (2024) Grants and Collaborations: NSF Grant: Integrating AI Ethics into STEM Curricula Collaborative Research: Evolution of IAAMCS National Science Foundation (NSF) AI Ethics Initiative Labs and Affiliations: Center for Artificial Intelligence and Cybersecurity Engineering McCrary Institute for Cyber and Critical Infrastructure Security