Find Academic Supervisors

• Neuroscience
• Parasitology
• Sensory Neurobiology
• +6 more

Elissa A Hallem is a Professor in the Department of Microbiology, Immunology, and Molecular Genetics at the David Geffen School of Medicine, University of California, Los Angeles (UCLA) . Her research lies at the intersection of neurobiology and parasitology , focusing on the sensory neural circuits that drive host-seeking behavior in skin-penetrating nematodes like Strongyloides stercoralis , a human-parasitic worm. She also investigates chemosensation , host-pathogen interactions , and sensory plasticity using both parasitic nematodes and the free-living Caenorhabditis elegans as comparative models. Education BA in Biology and Chemistry from Williams College (1999) PhD in Neuroscience from Yale University (2005) Postdoctoral training in Biology at Caltech (2010) Research Focus Her work addresses fundamental questions about how sensory circuits enable parasitic worms to detect and infect hosts. Key findings reveal the neural basis of heat seeking , chemosensory valence , and experience-dependent plasticity in nematodes. She has developed genetic tools for Strongyloides and studies steroid hormone pathways in Pristionchus pacificus . Scientific Awards 2023: UCLA Life Sciences Excellence in Research Award 2020: UCLA Faculty Mentor Award 2016: HHMI Faculty Scholar Award 2015: Burroughs-Wellcome Fund Investigators in the Pathogenesis of Disease Award 2014: NIH Director's New Innovator Award 2012: MacArthur Fellowship 2011: Rita Allen Foundation Fellowship Lab Overview The Hallem Lab at UCLA emphasizes inclusive research and tool development for parasitic nematode studies, aiming to uncover novel strategies for preventing infections through understanding sensory-driven parasitic mechanisms.

Aftab AhmadView profile

Professor

• Machine Learning
• Cyber Security
• Public Health Prediction
• +5 more

Aftab Ahmad is a Professor in the Department of Computer Science at the City University of New York (CUNY), specializing in cybersecurity and machine learning applications. He holds a Doctor of Science from George Washington University. His research focuses on developing machine learning algorithms for cyber threat intelligence (CTI) and public health prediction, along with designing secure generative deep learning models resistant to reverse-engineering. Key research areas include: Cybersecurity frameworks and privacy-preserving architectures Generative adversarial networks (GANs) with embedded security features Biomedical signal analysis and human body channel modeling Secure wireless protocols for critical infrastructure His publication trends emphasize: Privacy metrics and data protection mechanisms Smart grid and IoT security Neuroscience-inspired machine learning models Wireless network vulnerability assessments No scientific awards or grants were explicitly mentioned in the provided texts. He teaches advanced courses in computer security and network forensics at undergraduate and graduate levels. No advising relationships or lab affiliations were detailed in the available information.

Khandaker Mamun AhmedView profile

Assistant Professor

• Computer Vision
• Federated Learning
• Cybersecurity
• +4 more

Dr. Khandaker Mamun Ahmed is an Assistant Professor at The Beacom College of Computer & Cyber Sciences, Dakota State University. He teaches undergraduate and graduate courses in artificial intelligence, algorithms, and data structures. He holds a Ph.D. in Computer Science from Florida International University (2024), an M.Sc. from the same institution (2023), and a B.Sc. in Software Engineering from the University of Dhaka (2016). His research focuses on computer vision, federated learning, cybersecurity, explainable AI, vision-language models, and optimization algorithms. He has contributed to peer-reviewed publications and conference presentations, with notable work in federated learning for IoT, anomaly detection in videos, and AI applications in healthcare and agriculture. Recent articles highlight advancements in federated learning frameworks, AI-driven healthcare systems, and real-time object detection using neural networks. His work also addresses cybersecurity challenges in DevOps pipelines and generative AI for educational datasets. Recipient of the 'Best graduate student in research award' (2022), Dr. Ahmed advises on AI ethics and mentors students through academic-industry collaborations. His research bridges theoretical computer science with practical applications in agriculture, healthcare, and infrastructure monitoring.

Min ShinView profile

Professor

• Computer Vision
• Multiple Object Tracking
• Automated Visual Inspection
• +4 more

Min Shin is a Professor and Chair of the Computer Science Department at the University of North Carolina at Charlotte (UNC Charlotte), where he also serves as Assistant Dean for Research in the College of Computing and Informatics. He earned his Ph.D. in Computer Science & Engineering from the University of South Florida in 2001. His research focuses on Computer Vision, particularly multiple object tracking and automated visual inspection of nuclear power plants. He leads the Video and Image Analysis Lab, developing user-friendly tracking software funded by NSF, NIH, DARPA, and industry grants. Notable projects include the ABCTracker.org platform, which deploys algorithms refined over 10+ years of research. Dr. Shin’s work spans tracking applications in diverse domains such as ants, bees, cells, termites, robots, and vehicles. He has mentored Ph.D. and undergraduate students extensively, emphasizing computational methods in biology and engineering. His service includes roles as Associate Editor for IEEE Transactions on Systems, Man, and Cybernetics-B, and program committees for top conferences (ICCV, CVPR, ECCV). His grants and collaborations reflect interdisciplinary strengths in vision algorithms, usability, and real-world deployment.

Marco FarinaView profile

Professor

• Electromagnetic Fields
• Scanning Probe Microscopy
• Nanotechnology
• +4 more

Marco Farina is a Full Professor in Electromagnetics at the Department of Information Engineering, College of Engineering, Polytechnic University of Marche, Italy. His research spans electromagnetic modeling, scanning microwave microscopy, and nanotechnology, with applications in 2D materials, biosensors, and advanced measurement systems. He is a Senior Member of IEEE and actively contributes to Technical Committees on RF Nanotechnology. Laurea and Ph.D. in Electronic Engineering from University of Ancona Research interests focus on quantitative scanning microwave microscopy, electromagnetic analysis of active/passive components, and nanoscale characterization techniques. His work bridges theoretical modeling with practical implementation, including the development of the EM3DS software suite and novel inverted SMM systems. Recent publications highlight interdisciplinary applications in biomedical analysis and semiconductor physics. Scientific recognition includes the 3M-Nano Best Conference Paper Award and grants from US Army Research Laboratory and US Air Force Office of Scientific Research. He holds an ESA-funded patent for VNA calibration and has co-authored a book on planar structure analysis. Collaborative projects emphasize RF device optimization and biological imaging.

Arnaldo Delli CarriView profile

Associate Professor

• Nonlinear Dynamics
• Finite Element Analysis
• Nonlinear Vibration Analysis
• +3 more

Arnaldo Delli Carri is an Associate Professor at the CEES School of Engineering, serving as Curriculum Lead and actively involved in academic leadership. His research focuses on Nonlinear Dynamics and Finite Element Analysis, with expertise in structural analysis, modal testing, and vibration dynamics. He is currently accepting PhD students in areas like Nonlinear Vibration Analysis and FE model validation. Research interests include advanced topics such as nonlinear system identification, model upgrading, and machine learning applications in structural performance prediction. Notable projects involve analyzing planetary gearboxes, 3D printing opportunities in Africa, and laser vibrometer-based nonlinear detection. His work integrates experimental and computational methods to address challenges in mechanical systems and biomedical engineering. Collaborations span international partnerships, focusing on structural dynamics and nonlinear systems. His contributions include over 17 publications since 2011, with a focus on vibration analysis, finite element validation, and additive manufacturing applications. He currently supervises PhD candidates exploring nonlinear dynamics and FE formulations.

• Cyber-Physical Systems
• Industry 4.0
• Augmented Reality
• +4 more

Thomas Ludwig is a Professor of Information Systems with a focus on Cyber-Physical Systems at the University of Siegen. He holds a PhD (summa cum laude) from the same institution and has led numerous research initiatives in Industry 4.0, digital transformation, and human-centered technology design. His work spans augmented reality (AR), gamification, and AI integration in manufacturing. Ludwig co-founded and coordinates the 'Mittelstand 4.0-Kompetenzzentrum Siegen' to support SMEs in digitalization. He has authored over 50 publications in top-tier journals and conferences, including Computer Supported Cooperative Work (CSCW) and Proceedings of the ACM on Human-Computer Interaction . His research has been recognized with awards such as the IHK Preis 2017 for Best Dissertation and the Artur-Woll-Preis. Education: Diplom-Wirtschaftsinformatiker from University of Siegen (2012), PhD in Information Systems (2016), with a focus on socio-technical systems and mobile/social media research. Research Interests: Cyber-Physical Systems, AR applications, gamification design, AI in production planning, and digital competency frameworks for SMEs. He leads projects like Fusion, KOKOS, and EKPLO, addressing challenges in collaborative work, disaster management, and industrial digitalization. Grants & Projects: Projects include EU-funded EMERGENT, BMBF-funded KOKOS, and the self-acquired EKPLO initiative for APS systems in SMEs. He also coordinates the Zukunftszentren KI NRW and the EDIH Südwestfalen. Awards: 32. IHK Preis 2017, Artur-Woll-Preis, pwc-Preis, and multiple best paper awards at international conferences. Labs/Teams: Part of the Cyber-Physical Systems Lab at University of Siegen and the interdisciplinary team behind the 'Rendezfood' and 'Advanced Planning Systems' initiatives.

• Social Media Analysis
• Misinformation Dynamics
• Machine Learning Applications
• +5 more

Anees Baqir is an Assistant Professor of Data Science at Northeastern University London, affiliated with the CoMENS Faculty's Data and AI department. He is also a research fellow at the Complex Human Behavior (CHuB) lab at Fondazione Bruno Kessler (FBK), Trento, Italy, contributing to the European-funded AI-CODE project studying misinformation and polarization in social media. His research focuses on analyzing online information dynamics, polarization, and machine learning applications in healthcare, crime prediction, and language processing. Education details are not explicitly provided here, but his work bridges computer science and social sciences through interdisciplinary projects. He is part of the Complex Systems Society and collaborates globally, leveraging Northeastern University's transnational network across 13 campuses in the UK, US, and Canada. Research interests include: (1) Misinformation spread and polarization in digital ecosystems, (2) Machine learning for health analytics and behavioral prediction, (3) NLP innovations for Urdu and multilingual content analysis, (4) Spatio-temporal crime modeling for smart cities, and (5) Computational social science methods for political and societal dynamics. His recent publications span 2020–2025, exploring topics like Twitter-based PTSD detection, Urdu language processing systems, and AI-driven crime prediction. His work frequently intersects technical methodologies with societal impact, such as analyzing polarization in Pakistan’s political discourse or developing frameworks for university course scheduling. He holds no explicitly listed academic awards but is actively involved in research initiatives addressing global challenges like misinformation and public health surveillance. His advisory roles and grant activities are not detailed here, though his CHuB lab affiliation suggests collaborative funding opportunities. Key affiliations include the CHuB lab (FBK, Italy), Complex Systems Society, and Northeastern’s global network. He contributes to projects like AI-CODE, focusing on federated social media analysis and European misinformation trends.

• New Product Development
• Knowledge Management
• Collaborative Work Environments
• +5 more

Angelo Corallo is an Associate Professor at the Department of Experimental Medicine, University of Salento, specializing in technologies and methodologies for collaborative processes in industrial systems. His research spans Digital Business Ecosystems , Cybersecurity , and Collaborative Product Design , focusing on the interplay between technology and organizational dynamics. He leads interdisciplinary research divisions in Open Networked Business Management , Learning and Innovation , and Collaborative Product Design . Research Interests : Corallo's work integrates Information and Communication Technologies (ICT) with Business Management, particularly in Digital Twins for healthcare and manufacturing Knowledge Modeling and Ontology Engineering Industry 4.0 and Smart Manufacturing Agri-Food Sustainability through digitalization Scientific Contributions : His recent articles explore trends in Cybersecurity for Industrial IoT Metaverse Applications in business models Traceability Systems in food supply chains Collagen-Based Biomaterials from aquaponics

Mahsa SalehiView profile

Senior Lecturer

• Data Mining
• Machine Learning
• Time Series Analysis
• +5 more

Mahsa Salehi is a Senior Lecturer in the Department of Data Science & AI at Monash University’s Faculty of Information Technology. She holds a PhD in Computer Science from the University of Melbourne and previously served as a postdoctoral researcher at IBM Research Australia. Her research focuses on data mining, machine learning, and time series analysis, with applications in healthcare, cybersecurity, and smart grids. Education: PhD in Computer Science, University of Melbourne (2016) MSc in Software Engineering, Amirkabir University of Technology (2009) BSc in Information Technology & Computer Engineering, Amirkabir University of Technology (2008/2006) Her key research interests include multi-dimensional time series analysis, anomaly detection, brain-inspired machine learning, and non-stationary data learning. She has led or contributed to over 40 research outputs, including high-impact papers on anomaly detection frameworks (e.g., CARLA) and EEG representation learning (EEG2Rep). Her work bridges theoretical advancements with practical applications, such as detecting urinary anomalies in seniors and securing smart grid systems against cyberattacks. Dr. Salehi has secured significant grants, including AU$246K from ARENA (2019–2021) and AU$30K from Emotiv Research (2022–2024). She is an Associate Editor of the ACM Transactions on Knowledge Discovery from Data and has been recognized with awards like the ICDM 2022 Best Paper Runner-Up and IBM’s Manager’s Choice Award (2016). Grants & Projects: Privacy-Preserving Machine Learning (CSIRO Next Gen, 2023–2027) AI for Clean Energy & Sustainability (Monash, 2023–2027) Deep Learning for Brain EEG Analysis (PhD Top-Up, 2022–2025) Her contributions extend to editorial and patent activities, including roles at IBM Research and collaborative projects with industry partners like Emotiv.

Bernadette Hyland-WoodView profile

Lecturer

• Public Data Policy
• Digital Communications
• Data Ethics
• +8 more

Dr. Bernadette Hyland-Wood is a Lecturer in the School of Communication at Queensland University of Technology (QUT) and a Research Fellow at QUT's Centre for Data Science. She serves as an Affiliated Investigator in the Computational Communication and Culture Program within QUT's Digital Media Research Centre and is a chief investigator in the QUT Digital Media Research Centre. Her academic journey began with a Bachelor of Arts (Honours equivalent) in Computational Linguistics from UCLA, followed by a PhD in Policy and Governance from the University of Queensland in 2021. Dr. Hyland-Wood's research focuses on: Public data policy and digital communications during crisis situations Data ethics, AI governance, and organizational behavior in data-driven environments Responsible data science and deployment of generative AI technologies Indigenous Data Sovereignty and ethical considerations in AI development Science and technology policy with applications in health data infrastructure Her scholarly work demonstrates a consistent trajectory examining the intersection of data, policy, and public communication, particularly during periods of societal disruption. Recent publications reveal an increasing focus on AI governance frameworks, Indigenous perspectives on technology, and regulatory compliance in emerging technological landscapes. Her research has evolved from foundational work on open government data to more complex analyses of AI ecosystems and their societal implications. Dr. Hyland-Wood has received recognition through media features in the Australian Broadcasting Corporation (ABC) and Radio New Zealand. Her expertise has been sought for high-level policy contributions, including chairing the W3C Government Linked Data Working Group and authoring influential publications on crisis communications during the COVID-19 pandemic. Professional highlights include: Founding four tech startups in Australia and the U.S., two of which were acquired by major companies Serving as professional CEO of a semantic technology spin-out from MIT Co-founding Women in Technology (WiT) Australia in 1997, now Australia's largest professional networking organization supporting women in digital technologies Two decades of involvement in Open Source Software projects and W3C data standards development Leadership in international initiatives on data exchange standards to support digital research and evidence-based policymaking Dr. Hyland-Wood's career bridges academia, industry, and policy, emphasizing applied research and knowledge translation to ensure responsible AI and data-driven decision-making. Her work contributes to multiple United Nations Sustainable Development Goals, particularly those related to quality education, industry innovation, and reduced inequalities.

Nitesh V. ChawlaView profile

Professor

• Artificial Intelligence
• Data Science
• Network Science
• +4 more

Nitesh V. Chawla is the Frank M. Freimann Professor of Computer Science and Engineering at the University of Notre Dame, serving as founding director of the Lucy Family Institute for Data and Society. He also holds concurrent faculty appointments in the Department of Applied and Computational Mathematics and Statistics (College of Science) and the Department of Information, Technology, Analytics and Operations (College of Business). Ph.D., Computer Science and Engineering, University of South Florida, 2002 M.S., Computer Science, University of South Florida, 2000 B.E., Computer Science and Engineering, University of Poona, 1997 Chawla's research focuses on advancing artificial intelligence, data science, and network science to address societal challenges through interdisciplinary collaboration. He applies machine learning and big data analytics to domains such as public health, peace processes, and community development, with an emphasis on ethical and translational impact. Scientific recognition includes: Fellowships: AAAS, AAAI, ACM, IEEE Awards: IEEE CIS Outstanding Early Career, IBM Watson Faculty, IBM Big Data and Analytics, 1st Source Bank Technology Commercialization Honors: Rodney F. Ganey Award, Michiana 40 under 40 He founded the Inference Analytics and Learning (DIAL) Lab and co-founded Aunalytics, a data science software company. Affiliations span Notre Dame's Kellogg Institute, Kroc Institute, Liu Institute, Pulte Institute, Reilly Center, and Technology Ethics Center.

• Eye Tracking Methodology
• Human-Computer Interaction
• Computer Graphics
• +5 more

Andrew T. Duchowski is a Professor at Clemson University, specializing in Eye Tracking Methodology, Human-Computer Interaction, and Computer Graphics. His work spans over two decades with significant contributions to gaze-based interaction systems, foveated rendering, and cognitive load measurement. He authored three editions of the influential textbook Eye Tracking Methodology (Springer, 2003/2007/2017). Duchowski's research integrates eye movement analysis with applications in virtual reality, medical imaging (e.g., colonography viewers), and aviation safety. He actively collaborates with institutions globally and serves on editorial boards for journals like Proceedings of the ACM on Human-Computer Interaction . His recent projects include developing real-time gaze analytics pipelines and exploring entropy-based metrics for visual attention analysis. Publications (selected 15 recent): Focus on advancing gaze interaction in immersive environments, optimizing 3D visualization, and measuring cognitive load through pupillary activity and microsaccades. Key co-authors include Krzysztof Krejtz, Matias Volonte, and Donald House.

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +5 more

Christian Eichhorn is an Assistant Professor in the Department of Computer Science at Technical University of Munich, specializing in Human-Computer Interaction, Virtual Reality, and Augmented Reality applications. His research primarily focuses on developing serious games and immersive technologies for healthcare, education, and older adults. He has established a strong collaborative network, particularly with David A. Plecher and Gudrun Klinker, resulting in numerous publications in top HCI and VR venues. Dr. Eichhorn's research interests center around creating accessible and engaging technology applications. His work demonstrates particular expertise in developing serious games for various educational purposes (language learning, history education), healthcare applications (rehabilitation, dementia care), and technologies specifically designed for older adults. His research combines technical innovation in AR/VR systems with practical applications addressing real-world challenges in healthcare and education. Analysis of his recent publications (2022-2025) reveals a consistent focus on practical applications of immersive technologies. His work spans educational tools for programming and language learning, healthcare applications for rehabilitation and clinical training, and specialized technologies for older adults. The research demonstrates a strong interdisciplinary approach, bridging computer science with healthcare, education, and gerontology. His technical contributions include innovations in AR/VR system design, collaborative environments, and novel interaction techniques. Dr. Eichhorn has been actively involved in organizing workshops and contributing to major conferences in the VR/AR field, including IEEE VR and ISMAR. His collaborative approach is evident in his extensive co-authorship network spanning multiple institutions. His laboratory work focuses on developing practical AR/VR applications, with particular emphasis on creating systems that bridge virtual and physical experiences. Current projects include serious games for health behavior change, rehabilitation assessment tools using wearable sensors, and social VR environments for older adults.

Malcolm MacdonaldView profile

Professor

• Space Technology
• Astrodynamics
• Networked Systems
• +3 more

Eur Ing Malcolm Macdonald is a Professor of Electronic and Electrical Engineering at the University of Strathclyde. He serves as Director of the Applied Space Technology Laboratory (ApSTL) and the Centre for Signal and Image Processing (CeSIP). Additionally, he holds Visiting Professor roles at University College Dublin's Centre for Space Research and is Vice-Chair of the UK Space Agency's Space Technology Advisory Committee. His expertise spans space mission design, networked systems, and sustainable space technologies, with a focus on democratizing space data accessibility. He contributed to Scotland's first CubeSat and led initiatives like the Scottish Centre of Excellence in Satellite Applications (SoXSA). Research interests include astrodynamics, swarm engineering, and Earth observation, leveraging systems engineering to address global challenges. Notable awards include the 2020 Copernicus Masters Transport Challenge and the 2024 CompleNet Best Poster Award. He advises on over 80 research projects, focusing on satellite constellations, offshore energy monitoring, and space debris mitigation. His work integrates multidisciplinary approaches, emphasizing resilience and innovation in space systems. Labs and teams include ApSTL and CeSIP, where he leads a team of researchers and postgraduate students. Equipment resources include specialized drones and control systems for experimental validation. Collaborations span academia, industry, and government, driving advancements in space technology and policy.