جست‌وجوی استاد و پژوهشگر

• Wireless Sensor Networks
• Machine Learning
• Internet of Things (IoT)
• +۳ مورد دیگر

Ali Nauman is a researcher affiliated with Yeungnam University in Gyeongsan, South Korea, specializing in wireless communications, machine learning, and IoT systems. His work focuses on cutting-edge technologies for 5G/6G networks, UAVs, and biomedical applications. Co-author in 61+ academic publications (2019–2025) Collaborates extensively with scholars from King Saud University, University of Turku, and Yeungnam University Research Interests span Wireless Sensor Networks , Machine Learning for Communications , and AI-Driven Network Optimization . Key areas include electromagnetic emission management, underwater network topologies, and secure biometric systems. Recent publications highlight AI integration in 6G networks , UAV communication frameworks , and privacy-preserving biometrics . His work bridges theoretical advancements with practical implementations in smart cities and industrial IoT.

• Biomedical Circuits and Systems
• Machine Learning Applications
• Internet of Things (IoT) Security
• +۳ مورد دیگر

Amine Bermak is a Professor at the Department of Electrical and Electronic Engineering, Hong Kong University of Science and Technology. His research focuses on biomedical circuits, machine learning applications, and hardware security. Key contributions in CMOS sensors for bioluminescence and bacterial monitoring Pioneering work in IoT security and physical unclonable functions (PUFs) Developed edge computing frameworks for healthcare and industrial applications Significant publications in IEEE Transactions on Biomedical Circuits and Systems His recent articles highlight advancements in deepfake detection, energy-efficient ADCs, and wearable strain sensors. Collaborations span institutions in Hong Kong, Qatar, and Japan.

• Computer Science
• Artificial Intelligence
• Cybersecurity
• +۵ مورد دیگر

Kaushik Roy is an academic researcher affiliated with multiple institutions including North Carolina State University, Purdue University, and North Carolina A&T State University. His primary focus is on computer science, cybersecurity, and AI-driven solutions for real-world challenges. He has extensive experience in machine learning applications for intrusion detection, deepfake detection, biometrics, and federated learning frameworks. His work often bridges theoretical advancements with practical implementations in domains like IoT security, healthcare analytics, and cyber-physical systems. Affiliations: North Carolina State University, Purdue University, North Carolina A&T State University, and others Research Interests: Cybersecurity, Deep Learning, Biometric Authentication, Federated Learning, and AI Ethics He has co-authored over 105 publications, focusing on topics like anomaly-based intrusion detection, malware traffic classification, and privacy-preserving techniques. His recent work emphasizes federated learning architectures for healthcare and transportation IoT systems. Roy collaborates with industry partners to translate research into deployable solutions, particularly in edge computing and sensor networks.

• Children's Literature
• Intermedial Studies
• Cultural Studies
• +۳ مورد دیگر

Corina Löwe is a Lecturer in German with a focus on literature at Linnaeus University, where she has worked since 2004. She holds a PhD from Stockholm University, focusing on East German children's literature. Her research explores societal processes reflected in children's and young adult literature, intermediality, and climate change communication. She is affiliated with the Linnaeus University Centre for Intermedial and Multimodal Studies (IMS) and leads projects on intermedial ecocriticism and narrative authenticity in legal contexts. Löwe also contributes to educational initiatives, including virtual mobility programs and MOOCs (Massive Open Online Courses). She currently serves as pro-dean for the Faculty of Arts and Humanities and is part of the university's sustainability council. Her teaching includes German conversation, literature, and cultural studies, with a focus on fostering critical engagement with texts and media. Education: PhD in German Literature (Stockholm University, 2011) Research Projects: Intermedial Ecocriticism, Narrating the Trial, Food Culture in Climate Fiction Teaching: German language, literature, and cultural studies; advisor for bachelor's and master's theses Research Interests: Children’s literature as a societal seismograph, multimodal storytelling, climate change representation, and educational innovation. She emphasizes the role of literature in addressing contemporary challenges like ecological crises and societal memory.

• Graphic Memoirs
• Medical Humanities
• Intermediality in Education
• +۴ مورد دیگر

Nina Ernst is a Senior Lecturer at the Department of Film and Literature, Linnaeus University, Sweden. She holds a PhD in Comparative Literature from Lund University and previously served as a lecturer in Swedish at Columbia University (2018–2020). Her work bridges literary studies and comics research, focusing on graphic memoirs, medical humanities, and intermedial education. She leads research in IMS Literacy and IMS Memory clusters under the Linnaeus University Centre for Intermedial and Multimodal Studies, exploring media intersections in teaching and memory through textiles and embroidery. Her research interests include graphic medicine, intermedial pedagogy, and memory studies. She supervises across undergraduate to doctoral levels and teaches Comparative Literature and teacher training programs. Notable publications include her 2017 monograph Depicting One’s Self: Graphic Memoirs in Sweden and articles on trans narratives and healing through art.

Irtaza Shahidمشاهده پروفایل

پژوهشگر

• Secure and Private Speech Communication
• Generative AI and Speech/Audio Models
• Deepfake and Misinformation Detection
• +۳ مورد دیگر

Irtaza Shahid is a Ph.D. candidate in Computer Science at the University of Maryland, College Park, and a Researcher in the Networking, Mobile Computing, and Autonomous Sensing Lab (iCoSMoS) under Prof. Nirupam Roy. He is also a Founding Deep Learning Engineer at Hearvana.ai, a stealth AI startup under the AI2 Incubator. Ph.D. in Computer Science (University of Maryland, College Park) MS in Computer Science (University of Maryland, College Park) BS in Electrical Engineering (Lahore University of Management Sciences, Pakistan) His research spans Human-Centric Acoustics , focusing on Speech Privacy , Deepfake Detection , and Earable-Based Health Sensing . He has published in top venues like USENIX Security, ACM MobiSys, and IEEE ICASSP. Recent publications highlight Secure Speech Communication (USENIX Security 2025), UWB Localization (NSDI 2025), and Privacy Frameworks for Extended Reality (HotMobile 2025). These works emphasize Edge AI , Low-Power Acoustic Systems , and Signal Integrity . Scientific Awards: Student Travel Grant (USENIX Security 2025), Student Seed Funding (Maryland Cybersecurity Center 2023), Dean's Fellowship (University of Maryland 2020), and multiple Dean's Honor List Awards (LUMS 2016-2020) His projects include VoiceSecure (tamper-proof speech systems), DPOAE Estimation (health sensing via earbuds), and ThermWare (side-channel defense for IoT devices). He has contributed to Audio Engineering Society conferences and collaborated with industry partners like Nokia Bell Labs.

Harshvardhan Takawaleمشاهده پروفایل

پژوهشگر

• Wearable Sensing
• Acoustics
• Multimodal Imaging
• +۷ مورد دیگر

Harshvardhan Takawale is a third-year Computer Science PhD student at the University of Maryland College Park, affiliated with the iCoSMoS Lab under Prof. Nirupam Roy. He has previously worked as a Lead Researcher at Silence Laboratories Singapore and interned at Nokia Bell Labs UK and Cambridge. Education: B.E. in Computer Science from BITS Pilani (2020), currently pursuing PhD at UMD. Research Interests: Focus on enabling acoustic and RF sensing on low-power wearable platforms, gesture/micro-motion detection for smart environments, and physics-informed ML for context-aware systems. His work bridges hardware constraints with advanced inference for ubiquitous healthcare and mobility services. Recent Publications: Contributions to wearable interfaces (Scribe), auditory attention detection on earables, and low-power acoustic event sensing highlight his expertise in multimodal systems and signal processing. Earlier works span cybersecurity (malware detection), NoC fault tolerance, and continuous authentication. Scientific Awards: Dean's Fellowship at UMD Computer Science (2022, 2023). Roles & Projects: Interned at Nokia Bell Labs on earable-based attention detection; led Silence Laboratories' projects on co-location authentication (>92% accuracy) and landmark extraction for proof-of-visit. Also served as Publicity Chair for HumanSys 2024.

Leonardo Tenoriمشاهده پروفایل

دانشیار

• Metabolomics
• Foodomics
• Nuclear Magnetic Resonance (NMR) Spectroscopy
• +۴ مورد دیگر

Leonardo Tenori is an Associate Professor at the Department of Chemistry, University of Florence, affiliated with the Magnetic Resonance Center (CERM). He holds a master’s degree in Chemistry (2002) and a PhD in Structural Biology (2008), both from the University of Florence. His research focuses on metabolomics, particularly applying Nuclear Magnetic Resonance (NMR) spectroscopy to biomedical, pharmacological, and agricultural challenges. Education: Master’s in Chemistry, University of Florence, 2002 PhD in Structural Biology, University of Florence, 2008 Research Interests include metabolomics applications in disease diagnosis (e.g., celiac disease, breast cancer, cardiovascular disorders), development of statistical algorithms for data analysis (e.g., KODAMA), and collaborations in clinical and agricultural research. His work emphasizes metabolic biomarker discovery and integrative omics approaches. Recent research highlights include studies on stroke outcome prediction via blood biomarkers, metabolomic profiling of plant-based beverages, and lipidomic analysis of human sperm. These projects underscore his expertise in NMR-based metabolomics and its translational applications. Awards: 2015 Fellowship from the Italian Foundation Veronesi for melanoma metabolomics research He has contributed to over 100 publications and collaborates internationally. His work includes developing predictive models for disease recurrence in cancer patients and exploring metabolomic signatures in chronic diseases. He also investigates applications in agriculture, such as olive oil quality assessment and dairy cow health monitoring. Labs/Teams: Part of the Magnetic Resonance Center (CERM) at the University of Florence, contributing to interdisciplinary research in structural biology and metabolomics.

Greg Neilمشاهده پروفایل

پژوهشگر ارشد

• Learning and Memory
• Forensic Psychology
• Biometrics
• +۳ مورد دیگر

Greg Neil is a Research Fellow at Solent University, serving as the Social Sciences and Nursing Research Group Convenor and a member of the Wellbeing and Applied Research in Psychology (WARP) team. He holds a PhD from the University of Southampton (2011), focusing on bridging learning and memory theories. His research spans forensic psychology, cognitive processes, biometrics, and metacognition, with a focus on memory accuracy in legal contexts, vocal and facial recognition, and implicit learning models. He employs signal detection theory and ROC analysis in his methodologies. Key areas of research include eyewitness testimony reliability, vocal identity processing challenges, and the application of machine learning in biometric studies. Collaborative projects like the SuperIdentity initiative highlight his work in multimodal biometric systems and cybersecurity. His publications (20+ articles) reflect contributions to forensic science, cognitive psychology, and interdisciplinary cybersecurity analysis. Neil’s work emphasizes the intersection of human and computational approaches to recognition tasks, such as iris identification and hand dimension analysis. His findings on misinformation effects on memory and judgment underscore contributions to applied psychology and legal evidence evaluation.

• Speech Processing
• Machine Learning
• Affective Computing
• +۶ مورد دیگر

Professor Julien Epps is the Dean of the Faculty of Engineering at the University of New South Wales (UNSW). He holds a Professorship and previously served as Head of the School of Electrical Engineering and Telecommunications. His academic journey includes roles as Senior Lecturer (2007), Associate Professor (2014), and Head of School (2019). Epps earned his BE (Hons I) and PhD in Electrical Engineering from UNSW in 1997 and 2001, respectively. His research focuses on speech processing, wearable sensor technology, affective computing, and mental health applications. Notable contributions include work on depression detection via speech analysis, multimodal emotion recognition, and the development of tools like the IREye4Task dataset for wearable mental state analysis. He also investigates human-computer interaction through eye-tracking and biometric sensors. Epps' publications (2021–2025) emphasize speech-based health screening, adaptive signal processing for cybersecurity, and the integration of large language models with acoustic landmarks. His work spans engineering education, including a pioneering undergraduate quantum engineering degree program introduced in 2023. His lab and team collaborations include projects on smartphone-based depression screening, real-time task load estimation, and the design of robust spoofing attack detection systems. Epps has led interdisciplinary efforts in healthcare technology and pedagogical innovation in engineering education.

Srirangaraj Setlurمشاهده پروفایل

پژوهشگر

• AI
• Machine Learning
• Pattern Recognition
• +۶ مورد دیگر

Srirangaraj (Ranga) Setlur is a Principal Research Scientist and Co-Director of the Center for Unified Biometrics and Sensors (CUBS) at the University at Buffalo. He also serves as the Associate Director of Community Engagement at the Institute for Artificial Intelligence and Data Science. His research focuses on AI, Machine Learning, Pattern Recognition, Computer Vision, and Information Retrieval with applications in biometrics, document analysis, and healthcare. Education: MS in Industrial Engineering, University at Buffalo (1995) Research Interests: Development of AI-driven systems for biometric authentication (e.g., fingerprint, facial recognition) Design of datasets for chart analysis (CHART-Info), gait recognition (DIOR), and cross-domain fingerprint analysis Applications in healthcare diagnostics (e.g., dyslexia screening via handwriting analysis) Advancements in multimodal fusion (e.g., audio-visual, physiological signals) Recent Research Trends: His recent work emphasizes cross-domain learning (e.g., Ridgeformer), sparse feature aggregation (Proxyfusion), and AI applications in social robotics (AutoMisty). He consistently addresses challenges in unconstrained environments and under-represented data scenarios. Awards: Senior Member, IEEE 2019 ICDAR Best Student Paper Award (F. Xu) 2010 IBM Best Student Paper Award (X. Peng) UB Visionary Innovator Award Labs/Teams: Leads research teams in CUBS and the Institute for AI & Data Science, focusing on biometric systems, surveillance optimization, and multimodal AI applications.

Dalya Al Khafajiمشاهده پروفایل

مدرس

• Machine Learning
• Deep Learning
• Biometrics
• +۳ مورد دیگر

Dalya Al Khafaji is affiliated with the School of Computer Science & Engineering at Al-Nahrain University. She holds a Master of Science in Performance Evaluation of OpenFlow Controllers (2013–2016) and a Bachelor of Science from the same institution (2008–2012). Her research focuses on multimodal biometric systems for person authentication using machine learning and deep learning. Specifically, she aims to design neural networks that require minimal training data while maintaining high accuracy in face and voice modality fusion. This work emphasizes efficiency and adaptability across datasets. She has served as a Lecturer in an external academic engagement (2018–2022), contributing to teaching and research collaborations. No publications or awards are explicitly listed in the available data.

Ravi Kuberمشاهده پروفایل

دانشیار

• Accessibility
• Human-Computer Interaction (HCI)
• Haptic Technologies
• +۹ مورد دیگر

Dr. Ravi Kuber is an Associate Professor and Undergraduate Program Director in the Department of Information Systems at the University of Maryland, Baltimore County (UMBC). His research focuses on accessibility technologies, particularly haptic and multimodal interfaces for visually impaired users and older adults. He explores situational awareness enhancement, usable security for disabled users, and assistive technologies for situational impairments. He holds a Ph.D. from Queen's University Belfast and M.Sc./B.Sc. degrees from University College London. Education: Ph.D., Queen's University Belfast (Northern Ireland); M.Sc. & B.Sc., University College London (UK). Research Interests: Haptic technologies, accessibility for disabilities, situational impairments, BCI/gestural interfaces, mobile interaction design, and security for visually impaired users. He leads the Multimodal Interactions Lab and has NSF-funded projects on wearable technology for non-visual wayfinding. Grants: NSF Award No. 1352924 (Situational Awareness via Tactile Feedback). Labs & Teams: Multimodal Interactions Lab at UMBC, collaborating on projects like H4Plock (tactile authentication) and firefighter alert systems.

• Data Visualization
• Human-Computer Interaction
• Creative Computing
• +۳ مورد دیگر

Jonathan C. Roberts is a Professor in the Department of Computer Science at Bangor University, UK. His research focuses on data visualization, creative computing, and human-computer interaction. He leads projects like ZeroBench, a benchmark for multimodal AI models, and develops tools such as ColloCaid to assist academic writing. Roberts emphasizes creative design methodologies, including the Five Design-Sheets approach, and advocates for interdisciplinary education through data art exhibitions and visualization literacy programs. His work bridges technical innovation with pedagogy, addressing challenges in emergency response visualization (RAMPVIS), ethical AI (Humanity's Last Exam), and storytelling with time-series data. Roberts collaborates internationally, publishing in venues like IEEE VIS and ACM conferences. His contributions span academic journals, workshops (EduVis), and tools bridging design education and technology.

Tim Polzehlمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Speech Technology
• Machine Learning
• +۵ مورد دیگر

Tim Polzehl is a Senior Researcher at the German Research Center for Artificial Intelligence (DFKI) in Berlin's Speech and Language Technology (SLT) Department. He holds a PhD in technical communication sciences from TU Berlin (2014), focusing on automatic personality prediction from speech/user data. Previously, he led the Next-Generation Crowdsourcing group as a postdoc at TU Berlin's Quality and Usability Lab, overseeing projects like the Crowdee crowdsourcing platform. His current research spans speech anonymization, disinformation detection, deepfake analysis, and AI ethics. He actively supervises doctoral students and collaborates on EU-funded projects. Education: PhD in Technical Communication Sciences, TU Berlin (2014) Studies in Technical Communication Sciences, TU Berlin Research Interests: Focuses on applying AI to speech technology, privacy-preserving systems, and combating disinformation through machine learning. Specializes in multimodal systems, ethical AI deployment, and human-AI collaboration frameworks. Publications: Recent work emphasizes regulatory challenges of AI (e.g., EU AI Act compliance), privacy in clinical speech data, and personality-aware chatbots. Key areas include disinformation detection via LLMs and technical cybersecurity for speech systems. Grants & Awards: Participated in BMBF-funded leadership programs and EIT-Digital EU projects. Current projects involve developing frameworks for ethical AI integration in critical applications like elections. Labs/Teams: Leads SLT Department initiatives on autonomous AI agents and voice cloning at DFKI. Collaborates with TU Berlin's Quality and Usability Lab on ongoing research.