Find Academic Supervisors

• Micro- and nanoengineering
• Sensors and actuators
• Terahertz devices and systems
• +2 more

Professor Andrew Gallant serves as Head of Department and Professor of Electronic Engineering in the Department of Engineering at Durham University, having assumed the Head of Department role in August 2025. He has been with Durham University since completing his undergraduate studies, progressing from Research Associate to Lecturer, Senior Lecturer (Associate Professor) in 2014, and full Professor in 2020. Andrew Gallant graduated with a first class honours degree in Applied Physics with Electronic Engineering from Durham University in 2000, followed by a PhD in 2004 (EPSRC CASE award with Filtronic Compound Semiconductors) on widely tunable micromachined capacitors. His academic journey at Durham has been continuous since his undergraduate studies. Professor Gallant's research focuses on micro- and nanoengineering, sensors and actuators, and terahertz devices and systems. His group specializes in using micromachining to create new components for manipulating terahertz light, with over twenty years of experience in cleanroom-based fabrication techniques. His work spans both fundamental device physics and practical applications in the RF and THz regions, with over 100 refereed journal and conference publications. His recent publications demonstrate a strong focus on terahertz technology, microfluidics, nanofabrication, and spintronics applications. The research shows progression from fundamental device fabrication to increasingly sophisticated systems integration, with growing emphasis on practical applications in communications, sensing, and energy conversion. Scientific Coordinator of the €3.8M EU Initial Training Network (Notedev) Co-I on the €4M H2020 ITN INDEED Multiple EPSRC grants as PI and Co-I EPSRC CASE award for PhD research Funding from the Royal Society for international travel exchanges Professor Gallant supervises multiple research postgraduates across different research nodes including Electrical Power, Advanced Materials and Electronic Devices, and Communications and THz. He has significant experience managing large international collaborative grants, including the €3.8M EU Initial Training Network. His teaching responsibilities include Digital Systems at L1, Digital Electronics at L3, and supervising MEng/BEng/MSc projects. His research group maintains strong cleanroom fabrication capabilities for micro- and nanoscale devices, with particular expertise in terahertz components and systems.

• Geometric Algebra
• Clifford Algebra
• Medical Imaging
• +5 more

Silvia Giuseppina Franchini serves as a Contract Teacher in the Department of Biomedicine, Neuroscience and Advanced Diagnostics at the University of Palermo's School of Medicine and Surgery. Her academic career demonstrates a strong interdisciplinary focus bridging advanced mathematical frameworks with practical medical applications. Dr. Franchini's research interests include: Geometric and Clifford Algebra applications in medical imaging Hardware acceleration for geometric algebra operations Machine learning approaches for medical diagnosis, particularly for Crohn's disease Embedded systems design for real-time image processing Robotics control systems using conformal geometric algebra Medical image analysis and 3D reconstruction Her publication record spanning fifteen years reveals an evolution from foundational hardware implementations to sophisticated medical applications. She has developed specialized architectures including the GAPPCO system, ConformalALU coprocessor, and GAPP compiler, demonstrating innovative approaches to implementing geometric algebra in hardware for medical imaging. Her recent work emphasizes machine learning applications for Crohn's disease classification, showing how mathematical frameworks can translate to clinical diagnostic tools. Dr. Franchini maintains active research engagement with publications continuing through 2022, indicating ongoing contributions to the field of medical imaging technology development. Her work consistently addresses computational challenges while maintaining clinical relevance, particularly in gastroenterology through her Crohn's disease research.

Yangbo YeView profile

Professor

• Number Theory
• Medical Imaging
• Automorphic Forms
• +3 more

Yangbo Ye is a Professor in the Department of Mathematics at the University of Iowa. He holds a PhD from Columbia University. His research focuses on Number Theory and Medical Imaging, with notable contributions in automorphic forms, L-functions, and advancements in medical image reconstruction techniques. His work bridges pure mathematics and applied fields, particularly in computational tomography and deep learning applications. Ye's research in Number Theory includes studies on analytic aspects of automorphic forms, subconvexity bounds for L-functions, and applications of Petersson's formula. In Medical Imaging, he has developed algorithms for CT reconstruction, including framelet-based methods and neural network approaches for tumor segmentation. His interdisciplinary work has led to advancements in both theoretical mathematics and practical medical imaging technologies. Selected publications highlight his exploration of GL(n) automorphic forms, resonance sums, and innovative CT scanning methodologies. Despite his extensive publication record, no specific awards or grants are explicitly listed in the provided text. He advises no listed students but has collaborated on numerous projects in computational mathematics and biomedical imaging. Ye’s research also extends to algebraic structures in number theory, including functoriality and Dirichlet series, while his medical imaging work addresses challenges in spiral CT data reconstruction and interior tomography. His contributions reflect a deep integration of mathematical theory with real-world applications in healthcare technology.

Irene WeberView profile

Research Fellow

• Structural Biology
• Biochemistry
• HIV Drug Resistance
• +6 more

Irene Weber is a Research Fellow at Georgia State University's College of Arts & Sciences, Department of Physics. She holds a D.Phil. in Molecular Biophysics from Oxford University and has a distinguished career spanning postdoctoral research at Yale University, research positions at the National Bureau of Standards, and staff scientist roles at NCI-Frederick Cancer Research Facility. B.A., Physics, Cambridge University (1974) M.A., Physics, Cambridge University (1978) D.Phil., Molecular Biophysics, Oxford University (1978) Her research focuses on structural biology and biochemical mechanisms of key proteins involved in drug resistance in HIV/AIDS and bacterial infections. She specializes in crystallographic analysis, machine learning for resistance prediction, and structure-guided inhibitor design. Current projects include studying molecular mechanisms of chronic diseases and developing computational methods for drug resistance prediction. Recent publications highlight her work on HIV protease inhibitors with novel ligand designs, multidrug resistance mechanisms, and structural dynamics of resistant variants. Collaborations span local, national, and international institutions. Structural studies of HIV protease with darunavir-derived inhibitors Analysis of mutation clusters in drug resistance Crystallographic characterization of bacterial enzymes

Sangam Ankmnal VeerannaView profile

Assistant Professor

• Psychoacoustics
• Electrophysiology
• Auditory Processing Disorder
• +3 more

Dr. Sangam Ankmnal Veeranna is an Assistant Professor in Audiology at the University of Southern Mississippi. He holds a Ph.D. in Hearing Science from Western University, Canada (2017), following a postdoctoral fellowship at the National Center for Audiology there. His research focuses on auditory processing in individuals with and without listening difficulties, employing psychoacoustic and electrophysiological methods. He teaches courses such as SHS-302 Anatomy and Physiology of Hearing and SHS-701 Psychophysics . Dr. Veeranna’s work integrates clinical audiology with cutting-edge technologies, including machine learning applications for auditory diagnostics. His recent studies explore the impact of maternal COVID-19 during pregnancy on infant hearing, mobile psychoacoustic testing systems, and neural mechanisms behind auditory processing disorders. His expertise spans psychoacoustics, electrophysiology, and APD assessment. Notable contributions include developing novel methods to simultaneously assess subcortical and cortical auditory sensitivity and advancing cluster analysis techniques for auditory brainstem responses. He actively publishes in journals like American Journal of Otorhinolaryngology and Frontiers in Audiology and Otology .

• Mechanical Systems Design
• Robotics
• Kinematics
• +2 more

Raymond J. Cipra is Professor Emeritus of Mechanical Engineering at Purdue University's College of Engineering. He holds B.S., M.S., and Ph.D. degrees from the University of Wisconsin. His research focuses on mechanical systems design, robotics, kinematics, dynamics, and computer-aided engineering. Cipra has contributed to several NASA-supported projects involving reconfigurable exploratory robotic vehicles. His publications cover robotic path planning, composite manufacturing, assistive wheelchair technologies, and mechanism design. Recent work includes developing discrete angular joints for digital robots and expanding manipulation workspaces using friction dynamics. His applied research spans industrial automation, space exploration systems, and rehabilitation engineering, with collaborations extending to NASA technology development initiatives.

Alexander N. HananiaView profile

Assistant Professor

• Head and Neck Cancers
• Thoracic Cancers
• Gastrointestinal Cancers
• +3 more

Alexander N. Hanania, MD MPH, is the Clinical Director of Radiation Oncology at the Smith J. Evans and Mary P. Attwell Radiation Therapy Center and an Assistant Professor (tenure track) in the Department of Radiation Oncology at Baylor College of Medicine. He is affiliated with the Dan L. Duncan Cancer Center and Harris Health System. His clinical and research focus includes head and neck, thoracic, and gastrointestinal cancers, with expertise in radiomics, brachytherapy, and radiation therapy optimization. He has been recognized with awards such as the Early Career Faculty Award (2023) and the Roentgen Resident/Fellow Research Award (2019). Dr. Hanania holds a BS from Baylor University, an MD from the University of Texas Medical School at Houston, and an MPH in Biostatistics/Epidemiology from the University of Texas School of Public Health. His research emphasizes minimizing radiation toxicities, predictive biomarkers, and improving radiation oncology workflows. His articles span topics like brachytherapy response prediction, SBRT outcomes in underserved populations, and MRI-based dosimetry. Awards: Early Career Faculty Award, Educator of the Year (2022-23), Roentgen Resident Award (2019), Alpha Omega Alpha (2015). Professional Interests: Radiation therapy protocols, health disparities, and oncology innovation. Labs/Teams: Smith J. Evans Radiation Therapy Center, Dan L. Duncan Cancer Center. His publications highlight advancements in radiation oncology, including 3D-printed medical devices for brachytherapy and interobserver variability studies in dosimetry. Dr. Hanania advocates for equitable care access in safety-net systems.

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.

• Operations Research
• Artificial Intelligence
• Optimization Algorithms
• +3 more

Dr. Ozge Buyukdagli is an Associate Professor in the Department of Computer Science and Engineering at the International University of Sarajevo. She serves as Program Coordinator for both the Software Engineering and Artificial Intelligence and Data Engineering programs, and is a member of the Sustainable Development Goals committee at IUS. She holds a PhD in Industrial Engineering from Yasar University, Turkey (2018). Her research focuses on mathematical modeling, optimization algorithms, production systems performance evaluation, and sustainable development applications in education and technology. Education: PhD in Industrial Engineering: Yasar University, Turkey (2018) Research Interests: Dr. Buyukdagli explores interdisciplinary topics including: Optimization frameworks for smart cities and energy systems AI applications in image annotation and education technology Gender dynamics in STEM education and ICT workforce Data-driven approaches to academic performance analysis Sustainable development metrics in higher education Project Activities: She leads initiatives such as the Ai4CUAV project and ON-THE-JOB TRAINING PROGRAM FOR THE IT SECTOR, demonstrating commitment to bridging academic-industrial collaboration. Her work frequently integrates multi-objective optimization techniques with real-world implementation challenges.

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.

Hongye LiuView profile

Academic

• Computer Science Education
• Accessibility in Education
• Universal Design for Learning
• +5 more

Dr. Hongye Liu is a Teaching Assistant Professor in the Department of Computer Science at the University of Illinois Urbana-Champaign, affiliated with the Siebel School of Computing and Data Science. She joined the Illinois Department of Computer Science after years of research in Biomedical informatics at Harvard Medical School and its affiliated hospitals in the Boston Longwood Medical area. Her educational background includes a B.E. in Precision Machinery and Instrumentation from the University of Science and Technology of China and a PhD from MIT in computer aided design for 3-D Printing. Her academic journey reflects her belief that 'learning is a lifelong journey' and 'there are always surprises and we must embrace changes.' Dr. Liu's research focuses on understanding the needs of students with disabilities and broadening their participation in STEM fields. She is passionate about mentoring undergraduate students and developing Universal Design for Learning (UDL) approaches for STEM education. Her work specifically targets making mathematics and other STEM content more accessible in college engineering courses. Her publication record shows a clear evolution from biomedical informatics to educational research, with recent publications heavily concentrated on accessibility in engineering education. Her work bridges computer science education with practical applications that improve learning experiences for all students, particularly those with disabilities. She has received several awards for her contributions to diversity and inclusion: 2nd Best DEI paper award in NEE session at ASEE Conference 2025 Best DEI paper award in NEE session at ASEE Conference 2022 2nd best DEI paper and 3rd best paper in NEE session at ASEE Conference 2021 As Principal Investigator, Dr. Liu leads multiple projects including the SIIP project 'UDL based best practices including utilizing Canvas for the needs of students with disability' and the GIANT project 'Developing tools to make Mathematics and other STEM contents more accessible in college engineering courses.' She actively mentors undergraduate researchers and serves on committees focused on broadening participation across campus. Dr. Liu leads the UDL and Accessibility Research Lab, collaborating with faculty across engineering disciplines to develop inclusive learning environments and tools that support diverse student needs.

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.

Donghyun KimView profile

Assistant Professor

• Robotics
• Artificial Intelligence
• Computer Vision
• +3 more

Dr. Donghyun Kim is an Assistant Professor at the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst since 2021. He held postdoctoral roles at MIT's Biomimetic Robotics Lab (2019-2020) and the University of Texas at Austin's Human-Centered Robotics Lab (2018). He earned his PhD in mechanical engineering from the University of Texas at Austin (2017), an MS from Seoul National University, and a BS from KAIST. Kim's research focuses on control architectures for dynamic legged robots, emphasizing experimental validation and real-world hardware constraints. He extends his work into perception and machine intelligence to enhance autonomy and versatility. Key areas include humanoid and quadruped systems, assistive robotics (e.g., guide dog robots), and sensor integration using event cameras. His research interests span robotics control systems, biomechanical modeling, human-centered design, and AI-driven perception. Recent projects highlight the fusion of theory and practice, such as developing robots capable of mimicking animal movement and ensuring safety in unstructured environments. Kim has received the Best Paper Award in Transactions on Mechatronics (2020) and the Best Paper Award at CHI 2024 for human-centered guide dog robotics. His publications reflect trends in autonomous systems, perception algorithms, and bridging robotics with real-world applications. In advising, no formal PhD/Master’s students are listed, but his postdoctoral roles suggest prior mentorship. He has reviewed for major robotics conferences and journals, contributing to academic rigor. His Dynamic and Autonomous Robotic Systems (DARoS) Laboratory advances control strategies and sensor-driven autonomy for real-world robotics challenges.

Jens-Dominik MuellerView profile

Professor

• Computational Fluid Dynamics
• Numerical Optimization
• Shape Optimization
• +7 more

Dr. Jens-Dominik Mueller is a Professor in Computational Fluid Dynamics and Optimization at Queen Mary University of London (QMUL), within the School of Engineering and Materials Science. He holds roles as SEMS Academic Misconduct Officer, Head of the Professional Bodies Liaison Group, and Education Lead for the Centre for Intelligent Transport. His research focuses on adjoint methods, CAD-based shape optimization, and data-driven modeling, with applications in aerospace, biofluids, and energy systems. He has secured significant industrial and EU grants, including Horizon 2020 funding for projects like IODA and MADDOG. Education : - PhD (Aerospace Engineering, University of Michigan, 1996) - MSc (Aerospace Engineering, Von Karman Institute, 1990) - Dipl-Ing (Mechanical Engineering, Technical University of Munich, 1989). Research Interests : Development of multi-disciplinary modeling chains using adjoint sensitivity analysis, CAD integration in design optimization, and turbulence modeling. His work applies automatic differentiation tools to link CAD to objective functions, enabling robust optimization of complex systems like turbine blades and biomedical devices. Grants and Funding : Computational methods for active flow control (€179,947, EU Horizon 2020) MHI2: Mixing plane and nozzle vane design (€186,258, Mitsubishi Heavy Industries) CAD-based wing optimization for Airbus (€27,000, Airbus Defense & Space) MADDOG: Turbine design optimization (€127,046, EU Horizon 2020) Advising and Labs : Leads a research group focusing on adjoint-based optimization. Current projects include CAD-based wing-body junction optimization and LES-aided shape parametrization. Collaborates with industrial partners like Rolls-Royce and Airbus. Affiliations : Member of the editorial board of Aerospace , ASMO-UK, and the UK Fluids Network's Special Interest Group on Numerical Optimization in Fluid Dynamics.