جست‌وجوی استاد و پژوهشگر

• Intra-Body networks
• 5G Radio Technologies
• Cognitive Radio Networks
• +۳ مورد دیگر

Anna Vizziello serves as Assistant Professor at the Department of Industrial and Information Engineering, University of Pavia, specializing in intra-body networks, 5G radio technologies, and cognitive radio systems. Selected as an EU Commission expert since 2013, she actively referees research proposals and contributes to global telecommunications standards through IEEE committees. Her educational foundation includes a Laurea in Electronic Engineering and Ph.D. in Electronics and Computer Science, both from the University of Pavia. International research experience spans Northeastern University (2023, 2016, 2011), Georgia Tech's Broadband Wireless Lab (2009-2010), and UPC Barcelona (2009-2010), building on earlier work at EUCENTRE on emergency communications. Dr. Vizziello's research program bridges theoretical innovation with practical implementation. Her intra-body communication testbed—requiring only two PCs, a cable, and electrodes—enables accessible experimentation in neural interfaces and implantable devices. In 5G/mmWave systems, she pioneered Kalman-based hybrid precoding techniques that optimize spectral efficiency while reducing hardware complexity. Current investigations integrate neuromorphic computing with wireless networks to achieve unprecedented energy efficiency in biomedical telemetry. Recent publications reveal converging trends across biomedical wireless systems (galvanic coupling for EMG transmission), AI-enhanced communications (spiking neural networks for data compression), and environment-aware networking (weather-impacted LoRaWAN forecasting). These works demonstrate her signature approach: solving real-world constraints through cross-disciplinary innovation. Her recognition includes: N2Women Rising Star in Networking (2018) ACM NanoCom Best Paper Award (2021) Top-Cited Internet Technology Letters Paper (2019-2020) Outstanding Research Visitor at Northeastern University (2015-2016) As N2Women Award Co-chair (2021) and TPC member for 40+ conferences (IEEE ICC, GLOBECOM), she actively shapes the field. Her IEEE senior membership spans WIE and Green Communications committees, while tutorial invitations (IEEE MELECON, LATINCOM, CCNC) highlight her thought leadership in intra-body networks. Though specific grants aren't detailed, her extensive conference leadership and award record indicate substantial research funding. Collaborative frameworks include Northeastern University's GENESYS Laboratory and Georgia Tech's Broadband Wireless Networking Lab, where she develops open-source testbeds shared via IEEE and Code Ocean. Future work targets neural communication interfaces and beyond-6G satellite-terrestrial integration.

Ryan Boydمشاهده پروفایل

استادیار

• Computational Social Science
• Psychology
• Personality Assessment
• +۳ مورد دیگر

Ryan Boyd is an Assistant Professor in the School of Behavioral and Brain Sciences at the University of Texas at Dallas. As a computational social scientist, he specializes in analyzing everyday language (social media, speeches, writings) to uncover psychological patterns in personality, emotion, and cognition. Affiliation: University of Texas at Dallas Research Focus: Language analysis, mental health detection, AI psychology His work leverages computational linguistics and NLP to study: Personality through text Emotion regulation via social media Mental health indicators in digital language Historical and political discourse analysis Recent publications emphasize AI integration in psychological assessment, radicalization detection, and cultural language frameworks like MR-LIWC2015 for Marathi NLP. He develops accessible tools like LIWC, BUTTER, and WhisperingWizard for non-technical researchers, bridging complex analytics with user-friendly interfaces.

• Robot Vision
• Robot Learning
• Computer Vision
• +۵ مورد دیگر

Joni Kämäräinen is a Professor of Signal Processing at Tampere University’s Computing Sciences department under the Faculty of Information Technology and Communication Sciences. He leads the Vision Group and has a tenure-track career at Tampere University since 2012, achieving full professorship in 2020. Prior, he conducted postdoctoral research at the University of Surrey’s Center of Vision, Speech and Signal Processing and held a faculty position at LUT University. His research spans robot vision and robot learning , focusing on computer vision and machine learning applications. Key applied projects address industrial collaboration with Huawei, Nokia Technologies, and others, emphasizing robust visual perception, autonomous systems, and depth sensor integration. Notable work includes long-term visual place recognition, RGB-D tracking, and color constancy solutions. Recent publications (2023–2025) reflect expertise in digital twins for industrial manipulators, probabilistic subgoal modeling, depth-aware video deblurring, and LiDAR-place recognition datasets. His team’s outputs bridge robotics, AI, and signal processing, with interdisciplinary impacts in healthcare and autonomous navigation. Teaching responsibilities include graduate and doctoral colloquia, and the textbook Koneoppimisen perusteet (2023) . Funding sources include the Academy of Finland, EU Horizon 2020, Business Finland, Huawei, and Nokia Technologies.

• Sociolinguistics
• Sociophonetics
• Finnish Dialects
• +۵ مورد دیگر

Liisa Mustanoja is a Senior University Lecturer at Tampere University's Faculty of Information Technology and Communication Sciences, within the Department of Language Studies. She leads the Languages Unit and directs the Doctoral Programme in Language Studies (DPLA). Her research focuses on sociolinguistics, sociophonetics, Finnish dialects, and historical language change, particularly analyzing wartime letters and affective speech. She heads the Plural research center and collaborates on projects like Tunteiden Tampere (Kone Foundation grant 2024–2027) and the Sulka corpus initiative. Her academic career includes a PhD in Language Studies and a Docent title. She has held leadership roles in ethics committees and networks like Langnet. She has received teaching awards (2021) and contributed over 38 publications since 2003, focusing on Finnish language variation, speech corpus development, and sociolinguistic methodology. Key grants: Kone Foundation grants for Sulka (2023–2026), Kippo (2017–2022), and Tunteiden Tampere (2024–2027) Research groups: Sumu (Sulka), Plural (Languages and Cultures) Her work bridges human-machine interaction in language, emphasizing ethical communication and inclusivity. Recent projects explore affective speech processing and language policy innovations like the 'Data Protection Passport' concept.

Won-Jae Yiمشاهده پروفایل

عضو هیئت علمی

• Internet of Things (IoT)
• Wireless Body Sensor Networks
• Wearable Devices for Health Monitoring
• +۷ مورد دیگر

Won-Jae Yi is an Associate Teaching Professor of Electrical and Computer Engineering at the Illinois Institute of Technology (Illinois Tech), part of the Armour College of Engineering. He holds a B.S., M.S., and Ph.D. in Computer Engineering from Illinois Tech, completed in 2010, 2012, and 2017, respectively. In addition to his teaching role, Yi serves as the Undergraduate Laboratory and Computing Facilities Supervisor in the Department of Electrical and Computer Engineering. He has over 13 years of experience in research focusing on IoT, wireless sensor networks, wearable devices for health monitoring, FPGAs, cyber-physical systems, and edge computing. Education: B.S. in Computer Engineering (cum laude, 2010), Illinois Tech M.S. in Computer Engineering (2012), Illinois Tech Ph.D. in Computer Engineering (2017), Illinois Tech Research Interests: Yi’s work spans IoT-enabled systems, AI-driven smart devices, cybersecurity for embedded systems, and assistive technologies for visually impaired individuals. His research emphasizes practical applications such as smart home automation, wearable health monitoring, and real-time data fusion for IoT systems. He consistently integrates his expertise in hardware-software co-design, including FPGAs and SoCs, to create robust, low-power solutions. Teaching Contributions: Yi teaches undergraduate and graduate courses in Software Engineering, Internet of Things, Cybersecurity, and Artificial Intelligence. His teaching excellence was recognized with the 2023 Bauer Family Excellence in Undergraduate Teaching Award. Labs and Facilities: As Laboratory Supervisor, Yi manages computing facilities and oversees the development of experimental setups for student projects in IoT, embedded systems, and AI. His lab focuses on prototyping smart systems that bridge theoretical concepts with real-world applications.

Valentina Gonzalez-Rostaniمشاهده پروفایل

استادیار

• Political Economy
• Political Methodology
• Automation and Politics
• +۳ مورد دیگر

Valentina Gonzalez-Rostani is an Assistant Professor in the Department of Political Science and International Relations at the University of Southern California. She is also affiliated with the Mobilization and Political Economy NSF-REU program at the University of Pittsburgh, which supports underrepresented students in social science research. Prior to joining USC, she was a Postdoctoral Research Associate in the Department of Politics at Princeton University. Her educational background includes a Ph.D. in Political Science from the University of Pittsburgh (2024), an M.A. in Political Science from the same institution (2021), an M.S. in Public Policies from Universidad Catolica del Uruguay (2019), and a B.A. in Accounting from Universidad de la Republica (2015). Gonzalez-Rostani specializes in political economy, with a focus on understanding how economic polarization fuels political polarization. Her research examines the political consequences of job automation, including effects on political attitudes, voting behavior, and political participation. She also develops methodological tools such as hierarchical models with spatial autocorrelation and computational methods to measure populism. Her work spans advanced economies and the Global South, with particular attention to Latin America. Her recent publications reveal a strong trend connecting technological change with political outcomes. She has produced influential work on automation and political apathy, right-wing populism, and the interplay between economic and cultural factors in shaping political behavior. Her methodological contributions include innovative approaches to analyzing political discourse using social media data and developing scalable tools to measure political phenomena. She is a member of the 2025 APSA Task Force on AI and Political Science, where she serves on the committee on economic inequality and the labor force. She also co-directs Razones y Personas, a 14-year-old blog where social scientists publish weekly pieces on politics and policy, with a focus on Latin America and Uruguay. Gonzalez-Rostani is deeply committed to mentoring underrepresented students. She is affiliated with the Mobilization & Political Economy NSF-REU program, which supports the research paths of underrepresented students. Her work on inclusive mentorship has been published in PS: Political Science & Politics. Before moving to the United States, she worked in Uruguayan politics as a grassroots organizer and advised a member of Congress. She teaches courses on Text as Data for Social Scientists, Introduction to Data Analysis, and The Politics of International Trade at USC. Her methodological expertise includes R programming, natural language processing, machine learning techniques, and advanced statistical modeling.

Jan Breitsohlمشاهده پروفایل

مدرس ارشد

• Consumer Behavior
• Social Media Marketing
• Online Communities
• +۳ مورد دیگر

Dr. Jan Breitsohl is a Senior Lecturer in Marketing at the University of Glasgow, joining in April 2020. Previously, he held positions at the University of Kent and Aberystwyth University. He holds a PhD in Marketing Psychology from Bangor University and a German IHK diploma in Industrial Sales Management with managerial experience. His research focuses on the 'dark side' of social media and consumerism, including consumer aggression, online conflict management, and brand community dynamics. Research interests include consumer behavior in online environments, conflict resolution strategies, and ethical implications of digital marketing. He is a member of the Marketing Research Cluster at Glasgow and contributes to editorial boards including The Information Society . His teaching emphasizes digital marketing, consumer psychology, and social media tools. Notable awards include the 2017 Most Original Paper Award at the Global Brand Conference and multiple Best Paper in Track awards at AM Conferences (2016–2014). He has served as a track chair, reviewer, and external examiner for academic programs. Current research priorities include quantifying consumer bullying in online spaces, brand moderation during crises, and the interplay between digital CSR and consumer well-being.

• Privacy
• Malware Analysis
• Systems Security
• +۷ مورد دیگر

Dr. Oluwafemi Olukoya is a Lecturer in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast. His research focuses on privacy, malware analysis, systems security, and cybercrime, with an emphasis on mobile systems security, sustainable malware analysis, and cyber-attack attribution. He is particularly interested in interdisciplinary projects addressing socio-technical dynamics in cybersecurity. Research interests include malware detection engineering, digital forensics, and integrating legal/regulatory frameworks with software development. He is actively involved in PhD supervision and has secured research funding, including participation in the NIO New Deal Cyber Bid project (AIDE_NICYBER2025). Dr. Olukoya has published extensively in top-tier venues, leveraging machine learning for cybersecurity challenges such as concept drift in malware classification and vulnerability detection. He received the Queen's Merit Award for Fellowship in 2022. His work bridges technical cybersecurity solutions with real-world regulatory and societal implications, contributing to both academic and applied domains.

Antonio Servettiمشاهده پروفایل

استادیار

• Speech and Audio Processing
• Multimedia Communications
• Real-Time Multimedia Network Protocols
• +۷ مورد دیگر

Antonio Servetti is an Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, Italy, where he has been a faculty member since 2007. He is affiliated with the Internet Media Group (IMG) and the Interdepartmental Center PIC4SeR for Service Robotics. His work bridges multimedia processing, network communications, and web technologies. MS in Computer Engineering, Politecnico di Torino, 1999 PhD in Computer Engineering, Politecnico di Torino, 2004 Visiting Scholar, University of California, Santa Barbara, 2003 His research focuses on speech and audio processing , multimedia communications over wired and wireless networks , and real-time web-based multimedia applications . Key interests include WebRTC, Web Audio, HTTP adaptive streaming, and perceptual quality assessment. He has contributed to the development of secure multimedia transmission techniques, including selective encryption of speech and audio. The recent publications highlight a strong trend toward AI-driven modeling of subjective quality in multimedia, especially through deep learning for image and video quality prediction, understanding observer behavior, and remote music performance systems. His work often involves collaboration with researchers in the VQEG JEG-Hybrid group and the NEXA Center. Best Paper Award, Web Audio Conference 2021 Dr. Servetti has led and contributed to several research projects, including BRIC-2024 (acoustics in educational settings), PNRR HiFiReM (remote music education), and INAR (artistic research). He teaches courses such as 'Web Applications', 'Machine Learning for Vision and Multimedia', and 'Digital Audio Processing' across various engineering programs. He is also involved in educational governance as a member of academic councils for multiple degree programs. He is a core member of the Internet Media Group (IMG) , which focuses on multimedia processing and transmission, and contributes to the VQEG JEG-Hybrid working group on video quality assessment, where he develops frameworks for reproducible research and modeling of human perception.

• Cochlear Implants
• Auditory Perception
• Music Perception
• +۳ مورد دیگر

Christina Fuller is a researcher at the University of Groningen, active in interdisciplinary research bridging auditory neuroscience, medical data mining, and cancer therapy analysis. Her work primarily focuses on cochlear implants, music perception, and quality of life assessments for hearing-impaired individuals, while also contributing to symptom analysis in oncology through machine learning techniques. Key Research Areas: Cochlear implants, music perception, human-machine collaboration in clinical contexts, and cancer symptom management. Academic Collaborations: Works with institutions like Advanced Bionics and Mandema Foundation, with international partnerships in data science and oncology. Awards: Recognized with the Mandema Stipendium (2016) for auditory perception research and Advanced Bionics Industry Support (2013) for music therapy development in cochlear implant users. Public Engagement: Frequently contributes to public discourse on hearing rehabilitation through media appearances and community-focused presentations. Dataset Contributions: Created open-access datasets on music perception in implant users, hosted at University of Groningen and DataverseNL.

Gültekin Işıkمشاهده پروفایل

دانشیار

• Deep Learning
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Assoc. Prof. Gültekin Işık is affiliated with the Department of Computer Hardware at Iğdır University's Faculty of Engineering. He holds a PhD in Computer Engineering from Hacettepe University (2011–2019), focusing on Turkish dialect recognition using deep learning. His academic roles include serving as Head of the Department from 2019 to 2021. His research interests span deep learning applications in computer vision (e.g., YOLO-based crowd detection), optimization algorithms (e.g., Slime Mould Algorithm), environmental modeling (solar power efficiency prediction), and healthcare (breast cancer detection). He has authored numerous peer-reviewed articles and books, including works on convolutional neural networks for plant disease identification and hybrid optimization techniques for data clustering. Prof. Işık teaches advanced courses such as İleri Derin Öğrenme (Advanced Deep Learning) and Sinir Ağları (Neural Networks). His recent work emphasizes real-time video analysis for public health (social distancing) and energy systems optimization. Despite no listed awards, his contributions to interdisciplinary fields like bioacoustics and renewable energy are notable. He has advised two master’s students: Mehmet Şirin Gündüz (2023) on YOLO-based crowd detection and Seda Bayat (2021) on bird species recognition using deep learning. His research integrates theoretical models with practical applications in domains ranging from agriculture to medical imaging.

• Artificial Intelligence
• Affective Computing
• Speech Processing
• +۳ مورد دیگر

Fabio Catania is a Postdoctoral Fellow at the McGovern Institute for Brain Research, Massachusetts Institute of Technology. His work focuses on developing conversational agents and AI systems tailored for neurodevelopmental disorders, emotion recognition in speech, and inclusive technology design. He has pioneered projects such as the Emozionalmente Italian emotional speech corpus and the Emoty conversational agent for individuals with autism spectrum disorder. Research Interests: AI-driven therapeutic interventions for neurodevelopmental disorders Multimodal emotion recognition systems Design of accessible conversational interfaces for marginalized groups Linguistic and acoustic analysis of non-verbal communication cues Key Contributions: Developed AI tools like Smemo (multimodal interface for children's creativity) and OK, DNA! (genomic data explorer) Created voice-controlled music production systems for motor-impaired users Explored irony and sarcasm detection through multimodal analysis His work bridges computational linguistics, human-computer interaction, and clinical applications, with a focus on creating ethical and inclusive AI systems for healthcare and education contexts.

Ganesh Neelakanta Iyerمشاهده پروفایل

مدرس

• Software Engineering
• Agile Software Development
• Cloud Computing
• +۱۳ مورد دیگر

Ganesh Neelakanta Iyer is a Lecturer in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). He holds a PhD (2012) and MSc (2008) from NUS and a B.Tech. in Computer Science and Engineering from Mahatma Gandhi University, India (2004), where he ranked first. He brings over a decade of industry experience from companies like Salesforce, NXP, and Progress Software, and prior academic roles at Amrita Vishwa Vidyapeetham and IIIT-Hyderabad. His research interests span Software Engineering , Cloud/Edge Computing , Machine Learning , AI for Cultural Heritage , and Software Engineering Education . He founded the STeAdS (Software Engineering and Technological Advancements for Society) research group in 2021, focusing on technology applications in healthcare, education, and traditional arts like Kathakali and Wayang Kulit. The recent publications highlight a strong trend in AI-driven educational technologies , including LLMs for curriculum customization, web-based DevOps learning platforms, and agile project management tools. Another major theme is AI in cultural preservation , with works on Kathakali gesture and facial expression recognition. A third stream involves distributed systems and networking , particularly in edge computing and federated learning. Faculty Teaching Excellence Award 2024, NUS AWS Educate Cloud Faculty Ambassador (2019, 2020) Certified Kubernetes Administrator (CKA) University Topper (First Rank, 2004) NUS Postgraduate Research Scholarship (2009–2012) Dr. Iyer mentors students through UROP, FYP, Master’s, and PhD projects, and has led numerous grants and initiatives in cloud computing education and AI for societal benefit. He has delivered workshops and keynote speeches across the USA, Europe, Australia, and Asia. He actively leads the STeAdS virtual research group, fostering global collaborations. As a maestro in Kathakali, he integrates traditional art with technology, composing and staging performances while applying AI to preserve and analyze this heritage.

• Statistical Inference
• Data Modelling (Environmental events)
• Bayesian Statistics
• +۷ مورد دیگر

Dr. Pragalathan (Prahan) Apputhurai is a Lecturer in Applied Statistics at Swinburne University of Technology's School of Health Sciences . With a PhD in Applied Statistics from Swinburne and prior degrees from the University of Peradeniya, Sri Lanka, his expertise spans Bayesian Statistics , Structural Equation Modeling , and Extreme Events Data Modelling . He teaches undergraduate and postgraduate courses in Applied Statistics and supervises PhD/Master's students in areas including Factor Analysis and Social Determinants of Health. Education: PhD in Applied Statistics, Swinburne University of Technology, Australia Bachelor of Science & Applied Statistics, University of Peradeniya, Sri Lanka Research Interests: Specializing in statistical methods for health and social sciences, Dr. Apputhurai's work addresses issues including intimate partner violence, mental health in chronic disease populations, and empathetic AI in healthcare. His recent publications focus on structural equation modeling applications, psychometric validation in gastrointestinal disorders, and conversational agent empathy assessment. Grants: Rome Foundation (2025): Dietary interventions for IBS pain management Civil Aviation Safety Authority (2022-2024): Bayesian methodology in aviation safety Department of Communities and Justice (2018-2019): Indigenous women's reintegration through empowerment pathways Professional Recognition: Vice Chancellor's Teaching Excellence Award (2016) SUPRA Scholarship Recipient (2009) Academic Excellence in B.Sc. Examinations (2003) Academic Supervision: Currently supervising research projects in inflammatory bowel disease mental health support, conversational agent development, and trauma impact on quality of life across various health conditions.

• Human-Computer Interaction
• Data Visualization
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Alvitta Ottley is an Assistant Professor in the Department of Computer Science & Engineering at Washington University in St. Louis, with a courtesy appointment in the Department of Psychological & Brain Sciences. Her research focuses on interdisciplinary approaches to visualization systems, machine learning, and cognitive science to enhance decision-making in healthcare, intelligence analysis, and scientific discovery. She leads the AIR-D Summer Science Camp, a program aimed at underrepresented high school students in STEM. Education: PhD and MS in Computer Science from Tufts University (2016, 2013). Research Interests: Developing adaptive visualization systems that account for users' cognitive traits and goals. Her work integrates AI-driven insights with human factors to create context-aware interfaces. Recent studies explore trust dynamics in visualizations, cross-cultural visualization literacy, and the impact of chart types on legal decision-making. Awards: NSF CRII Award (2018), NSF Career Award, EuroVis Early Career Award (2022), and multiple best paper recognitions at top visualization conferences. Grants & Advising: Active in mentoring students and securing grants such as the NSF CAREER Award for context-aware systems. Her work on medical decision-making visualization received NSF support in 2018. Labs & Teams: Affiliated with the Division of Computational & Data Sciences and the Center for Trustworthy AI in CPS, focusing on ethical AI integration in visual analytics.