Find Academic Supervisors

Harshal SanghviView profile

Adjunct Professor

• Medical Imaging
• Artificial Intelligence
• Computer Vision
• +3 more

Harshal Sanghvi, Ph.D., currently serves as a postdoctoral fellow in the Charles E. Schmidt College of Medicine and holds an adjunct professor role in the College of Business at Florida Atlantic University. He earned his doctorate in computer engineering from FAU. His professional roles include program chair for the Institute for Certified Computing Professionals and vice chair for the Health-Tech and Life Sciences committee at South Florida Tech Hub. Sanghvi chairs the department of technology and clinical trials at Advanced Research. His research focuses on medical imaging, computer vision, augmented reality, artificial intelligence, business intelligence, and embedded systems. He has contributed extensively to peer-reviewed journals and conferences, with recent work emphasizing AI-driven healthcare solutions, cybersecurity, and interdisciplinary applications of technology. Key themes in his publications include AI in ophthalmic diagnostics, IoT in healthcare, digital twin models for ophthalmology, and novel algorithms for medical imaging analysis. His cybersecurity research addresses threats in smart cities and IT systems, while his engineering work explores actuator design and material reinforcement. No scientific awards or grants are explicitly mentioned in the provided texts. His advisory and collaborative efforts span clinical trials, medical device development, and tech policy initiatives in South Florida's innovation ecosystem. Sanghvi’s work bridges clinical medicine and business strategy through technology, exemplified by his roles in healthcare tech hubs and academic leadership in interdisciplinary research areas.

McKay SohlbergView profile

Professor

• Cognitive Rehabilitation
• Traumatic Brain Injury (TBI)
• Neuroscience
• +4 more

Professor McKay Sohlberg is a renowned academic and clinician in the field of cognitive rehabilitation, affiliated with the University of Oregon's College of Education and its Department of Communication Disorders and Sciences. She has held the HEDCO Endowed Professorship since 2010 and is a Fellow of the American Speech-Language-Hearing Association (ASHA). Her work focuses on developing interventions for cognitive impairments post-acquired brain injury, with a particular emphasis on assistive technology and client-centered goal setting. Education : Ph.D. in Educational Psychology, University of Washington (1990) M.S. in Speech-Language-Hearing Sciences, University of Washington (1984) B.A. in Human Biology, Stanford University (1982) Research Interests : Professor Sohlberg’s research spans cognitive rehabilitation strategies for TBI, concussion recovery, and postsecondary education support for individuals with brain injuries. She co-directs the Brain Injury and Concussion Clinic (BrICC) and has pioneered tools like the Attention Process Training-3 (APT-3) and the Read, Understand, Learn & Excel (RULE) framework. Awards : 2020 Mitchell Rosenthal Award for Scientific and Clinical Achievement 2018 Veteran’s Administration Champion 2013 Oregon Pioneer Award for Clinical Research 2008 Senior Distinguished Teaching Award (University of Oregon) Advising & Grants : She leads federally funded grants on assistive technology and has advised numerous graduate students. Her clinical contributions include evidence-based practice guidelines for TBI and social communication rehabilitation. Labs/Teams : Co-directs the Brain Injury and Concussion Clinic (BrICC) within the HEDCO clinic, integrating clinical care and research.

• Massive MIMO
• Cognitive Radio Networks
• Smart Grids
• +6 more

Professor Sangarapillai Lambotharan is a Professor of Digital Communications and Head of the Signal Processing and Networks Research Group at Loughborough University's Wolfson School of Mechanical, Electrical and Manufacturing Engineering. He holds qualifications including BEng, PhD, DIC, PGCAP, and is a Senior Member of IEEE, Fellow of IET, and Fellow of the Higher Education Academy. His research focuses on advanced wireless communication technologies such as Massive MIMO, Cognitive Radio Networks, and Smart Grids, alongside Machine Learning, Data Mining, and Cyber Security. He has authored over 200 publications in top-tier journals and conferences. His work integrates machine learning with signal processing to address challenges in adversarial attacks, federated learning, and network optimization. Recent research emphasizes intelligent reflecting surfaces (RIS), OTFS satellite communications, and federated learning defenses against model poisoning. Prof. Lambotharan's contributions span theory development, algorithm design, and practical implementations in 5G/6G systems, UAV networks, and edge computing environments. He leads collaborative projects on secure communications, distributed intelligence, and blockchain-based network security mechanisms. Prof. Lambotharan's academic leadership includes editorial roles at IET Signal Processing and teaching Digital Signal Processing and Information Theory. His lab explores cutting-edge topics like RIS-aided systems, anomaly detection in IoT, and context-aware caching strategies for heterogeneous networks. Key achievements include pioneering work on Kalman filtering for channel estimation and game-theoretic solutions for resource allocation in cognitive radio networks.

Carlo RussoView profile

Senior Lecturer

• Medical Imaging
• Deep Learning
• Neuroscience
• +3 more

Dr. Carlo Russo is an Honorary Senior Lecturer at the Macquarie Medical School, Macquarie University, and a Research Associate at the Computational NeuroSurgery (CNS) Lab. His research focuses on applying non-linear geometry, fractal analysis, and deep learning to image analysis in neurosciences. He previously spent over 15 years at Humanitas Research Hospital in Milan, Italy, developing software/hardware for computer-aided diagnosis in clinical workflows. His work includes fractal geometry applications in histopathology and radiology images. Research Interests: Medical Imaging, Deep Learning, Fractal Geometry, Neuro-Oncology, and Biomedical Engineering. He has authored/co-authored 18 peer-reviewed articles and 5 patents. Collaborations & Projects: Active in the 'Computational Neurosurgery Lab' project (2019–present), collaborating on AI-driven approaches for glioma diagnosis and neurosurgical applications. Recent work includes MRI-deep learning fusion for tumor segmentation and synthetic PET generation. Lab Affiliation: Computational NeuroSurgery (CNS) Lab, Macquarie University.

Kosmia LoizidouView profile

Research Fellow

• Biomedical Engineering
• Medical Image Processing
• Machine Learning
• +2 more

Kosmia Loizidou serves as a Post-Doctoral Researcher at the KIOS Research and Innovation Center of Excellence, University of Cyprus, following the completion of her Ph.D. in Electrical Engineering from the same institution in June 2023. Her doctoral research focused on Detection, Classification, and Prediction of Breast Abnormalities using Sequential Mammograms. Her academic credentials include: BSc in Mechanical and Manufacturing Engineering with a minor in Biomedical Engineering from the University of Cyprus (2016) MSc in Electrical Engineering, specializing in Biomedical Engineering, from the University of Cyprus (2018) PhD in Electrical Engineering from the Department of Electrical and Computer Engineering, University of Cyprus (2023) Dr. Loizidou's research centers on biomedical engineering with a specialized focus on medical image processing and machine learning applications for cancer diagnosis. She pioneers methodologies for breast cancer detection through temporal subtraction of sequential mammograms, developing advanced computer-aided diagnosis systems that classify masses and micro-calcifications while predicting near-term cancer occurrence. Her work bridges engineering innovation with clinical oncology to enhance early detection accuracy. Analysis of her publication trajectory reveals a concentrated research program leveraging machine learning and image processing on sequential mammograms. Key themes include temporal subtraction techniques for improving cancer localization, classification of benign versus malignant abnormalities, and predictive modeling of near-term breast cancer development. Her contributions span algorithm development, comprehensive reviews, and specialized applications for micro-calcifications and mass detection. Scientific awards: No awards or fellowships are documented in the provided information. Regarding academic mentoring and funding, no details are available about supervised students or secured research grants. Her professional activities appear centered on independent research within the KIOS framework. She operates within the KIOS Research and Innovation Center of Excellence, a premier hub for intelligent systems research at the University of Cyprus focused on critical infrastructure networks. This environment supports her interdisciplinary work at the intersection of biomedical engineering, computer science, and oncology.

• Medical Image Analysis
• Video Surveillance Systems
• Pattern Recognition
• +3 more

Lorenzo Putzu is a Researcher (Assistant Professor) at the University of Cagliari's Department of Computer Science. He holds a PhD in Computer Science from the same institution (2016). His work focuses on pattern recognition techniques applied to medical imaging and video surveillance, including automated diagnosis support systems, security applications, and synthetic data generation for AI training. Since 2017, he has been part of the PRA Lab, contributing to projects like the IMMAGINA initiative for trustworthy AI in surveillance. Education: Bachelor's Degree in Computer Science (2010) Master's Degree in Computer Science (2012) PhD in Computer Science (2016) Research Interests: Medical image analysis for automated diagnosis (e.g., blood cell classification, histopathology) Video surveillance systems using AI (e.g., person re-identification, crowd counting) Synthetic data generation for improving model robustness Federated learning in healthcare applications Adversarial defense mechanisms in computer vision Key Projects: Development of MIRIAMS for multiple sclerosis segmentation Advancing leukocyte classification methods for hematological analysis Pioneering work on federated learning for cell nuclei segmentation Grant & Advising Activities: No explicit grants or advising roles listed Labs/Teams: Active contributor to the PRA Lab, collaborating on interdisciplinary AI projects in healthcare and security.

Dario SiegenView profile

Researcher

• Science and environmental communication
• Political communication
• Social change
• +1 more

Dario Siegen is a Researcher at the Institute of Communication Science and Media Research (IKMZ) at the University of Zurich, affiliated with the Department of Public Sphere and Society under Prof. Mark Eisenegger. He also held roles as Student Conference Coordinator for the International Sustainable Campus Network at ETH Lausanne and Research/Teaching Assistant during 2016-2018 under Prof. Mike Schäfer. His academic background includes a Master’s in Development Studies (Graduate Institute Geneva, 2018-2020), and a dual Bachelor’s in Journalism & Communication Science and Business Administration from the University of Zurich (2014-2017). Research focuses on intersections between science/environmental communication, political dynamics, societal transformation, and computational methods. Notable projects include analyzing climate change media coverage during the pandemic, academic-industry engagement patterns, and South African climate perception studies. His work bridges qualitative and quantitative methods, often using automated content analysis. Key awards include the Swiss Study Foundation’s recognition (2019) and the University of Zurich’s Outstanding Academic Achievement Award (2018). His contributions span peer-reviewed journals like Environmental Communication and Plos One, with recent conference presentations at ECREA (2022) and ICA (2022) on topics ranging from vaccination debates to media quality in conflict reporting. Active in interdisciplinary teams such as the fög Research Center, his research emphasizes societal communication challenges in contemporary issues.

Cristina LopesView profile

Professor

• Software Engineering
• Programming Languages
• Distributed Virtual Environments
• +5 more

Cristina Lopes is a Professor of Informatics at the Donald Bren School of Information and Computer Sciences , University of California, Irvine. She holds administrative roles including Director of the Master of Software Engineering Program and former Director of the Institute for Software Research . Her research focuses on software engineering, programming languages, and distributed systems, with contributions to open-source projects like OpenSimulator and AspectJ. She has authored the influential book Exercises in Programming Style . Education: PhD from Northeastern University, MS/BS from Instituto Superior Técnico (Portugal). Awards include IEEE Fellow (2019), ECOOP Test of Time Award (2017), and ACM Distinguished Scientist (2011). She co-founded a virtual reality company for urban redevelopment and leads NSF-funded projects, including the prestigious CAREER Award. Research Interests: Large-scale software systems, aspect-oriented programming, code clone detection, and applying AI to programming challenges. Her work bridges theory and practice, with applications in urban simulation and healthcare systems. Awards and Grants: Over 15 awards including national and international distinctions. Grants focus on scalable software tools and environmental sustainability in computing. Labs/Teams: Leads the Software Engineering Research Group and collaborates with industry partners on open-source infrastructure and AI-driven development tools.

Pranav RajpurkarView profile

Associate Professor

• Artificial Intelligence
• Medical Imaging
• Clinical Decision Making
• +4 more

Pranav Rajpurkar is an Associate Professor of Biomedical Informatics at Harvard Medical School, leading the Rajpurkar Lab. His research focuses on developing AI technologies for clinical decision-making, particularly in medical imaging and clinician-AI collaboration. He holds a PhD in Computer Science from Stanford University and has collaborated widely with clinicians across radiology, cardiology, and pathology. His work emphasizes scalable dataset curation, AI algorithms for limited data, and ethical integration of AI into healthcare workflows. Education: B.S., M.S., and Ph.D. in Computer Science from Stanford University. Research Interests: Artificial Intelligence in healthcare, medical imaging analysis, generative AI models, human-AI collaboration, and healthcare policy for AI adoption. His lab’s innovations include foundational work on chest X-ray interpretation and frameworks for medical AI certification. Key Contributions: Over 57 publications, including high-impact studies in Nature , Lancet , and NEJM . Active in global initiatives like the MAIDA data-sharing framework and clinical certification pathways for medical AI systems. Labs/Teams: Directs the Rajpurkar Lab at Harvard DBMI, collaborating with industry and academic partners to advance AI-driven healthcare solutions.

• Medical Imaging
• Radiology
• Pediatrics
• +3 more

Alexandra J Sardi is a Clinical Assistant Professor of Pediatrics affiliated with the University of Southern California (USC) through Children's Hospital Los Angeles (CHLA). Her work focuses on medical imaging applications in pediatrics, particularly in evaluating mammographically suspicious lesions using advanced imaging technologies. She holds an email address at asardi@chla.usc.edu. Her research interests center on improving diagnostic accuracy through computerized imaging analysis, with a specific emphasis on pediatric and breast-related medical imaging challenges. This is reflected in her 2003 publication in AJR Am J Roentgenol , which explores infrared imaging techniques. No scientific awards, grants, or advisory roles are explicitly listed in the provided text. No lab affiliations or future research directions are mentioned.

Wilfried PhilipsView profile

Professor

• Computer Vision
• Real-time Computer Vision
• Video Quality Improvement
• +4 more

Wilfried Philips is a senior full professor at Ghent University and scientific lead of imec's Center of Excellence on Image Processing and Sensor Fusion. He leads the Image Processing and Interpretation (IPI) research group at imec-UGent and Ghent University's valorization consortium iKnow, which has created 9 spin-off companies including Senso2Me (IoT services for elderly care). His research focuses on real-time computer vision and video quality improvement for industrial applications, with key domains spanning automotive sensing, industrial inspection, machine learning, and video surveillance. The IPI group's work has directly generated three commercial spin-offs through applied research in these areas. Dr. Philips' publication portfolio demonstrates significant impact across remote sensing, medical imaging, and biological computer vision, with multiple highly-cited papers including a 2014 Best Paper Award-winning study on hyperspectral-LiDAR fusion. His honors include: Best Paper Award, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2014) Senior Member, IEEE Fellow, Belgian-American Educational Foundation As a translational research leader, he has successfully bridged academic innovation and industrial implementation through multiple technology spin-offs and industry partnerships.

Ayla Rigouts TerrynView profile

Assistant Professor

• Automatic Terminology Extraction
• Machine Learning
• Language and Translation Technology
• +3 more

Ayla Rigouts Terryn is an Assistant Professor at KU Leuven, with a focus on language and translation technology. She previously served as a postdoctoral researcher at Ghent University's LT3 research group. Her research centers on computational terminology, particularly supervised machine learning approaches for monolingual and multilingual automatic term extraction. She developed the open-source ACTER dataset and organized the TermEval shared task, advancing methodologies in data-driven terminology research. Recent publications highlight her work on sequential labelling approaches (2022), hybrid term extraction frameworks (2019), and cross-lingual embeddings (2022). The ACTER dataset (2020) covers corruption, dressage, heart failure, and wind energy domains across English, French, and Dutch. FWO scholarship recipient for her EXTRACT project (2017) She co-lectures on Advanced Website Management at Ghent University, covering CMS development, web design principles, and team dynamics. Her tools, like D-Terminer, demonstrate practical applications of her research.

• System Security
• Fault Injection
• Fuzzing
• +5 more

Erik van der Kouwe is an Assistant Professor at the Faculty of Science, Vrije Universiteit Amsterdam, holding dual appointments in the Computer Systems department and the Network Institute. His research focuses on system security, fault injection, fuzzing, and embedded systems security. He contributes to both theoretical advancements and practical implementations of security mechanisms. Key research areas include mitigating vulnerabilities through hardware-software co-design, exposing compiler optimization flaws that evade sanitizers, and developing efficient fuzzing frameworks for malware analysis. His work often bridges academic research with real-world applications in embedded systems and operating systems. Recent publications highlight innovations like InvisiGuard for microcontroller security, hwdbg for hardware debugging frameworks, and Enviral for environment-aware malware analysis. His research has been published in top-tier venues such as IEEE Transactions, ACM conferences, and workshops like EuroSEC. Teaching responsibilities include Advanced Operating Systems, Secure Programming, and Software Security courses. Collaborations span international teams working on topics like compiler hardening, embedded system resilience, and vulnerability benchmarking.

Kerstin VokingerView profile

Associate Professor

• Health Policy
• Pharmaceutical Economics
• Medical Technology Regulation
• +3 more

Prof. Kerstin Vokinger is an Associate Professor at the Department of Health Sciences and Technology, ETH Zurich. Her research focuses on pharmaceutical economics, healthcare policy, AI in medicine, and regulatory science. She investigates drug pricing strategies, managed entry agreements, and the therapeutic value of medicines. Her work often compares policies between the US, Europe, and Switzerland, addressing issues like cancer drug pricing, orphan drug designation, and AI-based medical devices' regulation. Key research areas include: Clinical trial outcomes and drug approval processes Health technology assessment and cost-effectiveness analysis Legal frameworks governing healthcare innovation Data privacy in medical research and AI applications Her recent articles analyze trends such as the 'cancer premium' in drug pricing, the impact of expedited approvals on therapeutic value, and global disparities in cancer drug access. She also explores regulatory challenges in AI-driven medical devices and the ethical implications of anonymized healthcare data. Prof. Vokinger collaborates with institutions worldwide to shape evidence-based health policies and improve drug affordability. Her work bridges legal, economic, and scientific dimensions of healthcare systems.

Aidan HoggView profile

Assistant Professor

• Spatial Acoustics
• Immersive Audio
• Statistical Signal Processing
• +3 more

Aidan Hogg is an Assistant Professor/Lecturer in Computer Science at Queen Mary University of London (QMUL) and an Honorary Research Associate at Imperial College London. His primary affiliation is with the Centre for Digital Music (C4DM) and the School of Electronic Engineering and Computer Science at QMUL. He co-leads the Virtual, Immersive, Augmented and Binaural Audio Lab (VIABAL) . Education: PhD and MEng from Imperial College London, specializing in engineering and computer science disciplines. His research focuses on deep learning for spatial acoustics , immersive audio , and statistical signal processing with applications to speech and audio systems. Key areas include HRTF upsampling , speaker diarization , and acoustic localization . Grants: Secured funding such as the Online Speech Enhancement in Scenarios with Low Direct-to-Reverberant-Ratio grant (£65,621 from L-ACOUSTICS UK LIMITED, 2024–2025). His work bridges academia and industry, particularly in audio engineering and AI-driven audio solutions. Labs/Teams: Active in the Centre for Multimodal AI and collaborates with institutions like the Central Conservatory of Music, China. His research outputs include datasets like the SONICOM HRTF Dataset and contributions to conferences such as DAFX, ICASSP, and WASPAA.