Find Academic Supervisors

• 3D Modeling
• Digital Design
• Computer-Aided Design
• +7 more

Saverio Paglianiti is a Professor at the Brera Academy of Fine Arts (ABABO) in Milan, where he has taught since 2011. He also teaches at the Academy of Fine Arts of Bologna (since November 2022) and previously at ACME of Novara (2016-2018) and ACME of Milan (2010-2011) Private Academies of Fine Arts. He earned an Academic Diploma in Scenography from the Academy of Fine Arts in Milan on February 24, 1998, scoring 110/110. His professional credentials include Certified 3d Studio Max 2012 Associate and Certified 3d Studio Max 2012 Professional – Models to Motion certifications. Paglianiti specializes in comprehensive 3D digital modeling techniques across multiple creative disciplines. His expertise spans line and polygonal modeling, material creation, advanced lighting systems (VRAY SUN, LIGHT, DOME, IES), rendering techniques, and 3D animation. He founded A23DS, a Milanese graphic studio in 2017 that produces high-quality 3D content for nautical, architectural, mechanical and cinematographic applications. He teaches the course 'Digital Modeling Techniques – 3D Computers' (Code: ABTEC41) across six different departments with varying credit values (6-8 CFA), requiring Windows-based systems with NVIDIA RTX graphics. His instruction methodology combines in-person teaching with custom video tutorials, assessing students through project-based evaluations including storyboard creation, concept development, and 3D scene construction. His technical proficiency includes: 3D Modeling & Animation: Autodesk 3D Studio Max Rendering: VRAY by Chaos Group Fluid Dynamics: PhoenixFD by Chaos Group Video Editing: Adobe Premiere & After Effects Image Processing: Adobe Photoshop & Illustrator

• Computer Security
• Pattern Recognition
• Digital Image Processing
• +3 more

M. N. Islam is a Professor and Chair of the Computer Security department at Farmingdale State College, State University of New York (SUNY), a position he has held since 2016. His academic career spans multiple institutions including Old Dominion University, University of West Florida, University of South Alabama, and Bangladesh University of Engineering and Technology, where he served in various roles from Lecturer to Associate Professor. He has held significant administrative positions including Program Coordinator for Security Systems & Law Enforcement Technology (2013-2015) and currently serves as Chair of the Computer Security department. Dr. Islam earned his Doctor of Engineering in Electrical and Electronic Engineering from Muroran Institute of Technology, Japan (1999), Master of Science in Engineering from Bangladesh University of Engineering and Technology (1994), and Bachelor of Science in Engineering (with 1st Class Honors) from the same institution (1991). His doctoral research focused on optical communication systems. His research spans multiple interdisciplinary fields with a strong emphasis on applying optical techniques to security problems. Dr. Islam's work in pattern recognition has led to innovations in distortion-invariant target detection using log-polar transformation and joint transform correlation. His security research includes robust information security systems using steganography and optical techniques, with applications in biometrics and data protection. He has also made significant contributions to digital image processing, particularly in super-resolution enhancement techniques for video scenes, and has conducted extensive research on optical communication systems and wireless networks. Dr. Islam has received numerous prestigious awards including Senior Membership in IEEE (2008) and SPIE (2010), inclusion in Marquis Who's Who in America (2010), and multiple Individual Development Award Program (IDAP) awards from the State of New York (2011, 2014). His research has been supported by grants from SUNY High Need Program, NYSUNY 2020 Program, W.E.B. Du Bois Faculty Student Research Experience, Farmingdale Students First Grant, and US Army Medical Research. As an educator and mentor, Dr. Islam has supervised numerous graduate and undergraduate students across multiple institutions. He has developed new curricula including B.S. degrees in Computer Security Technology and Infrastructure Security, and Microcredentials in Computer Security. His teaching portfolio includes over 30 courses ranging from foundational electrical engineering subjects to advanced computer security topics. He directs the Digital Image Processing Research Lab, which focuses on machine vision and security research, developing new facilities and securing research funding for innovative security applications.

• Generative Art
• Generative AI
• Digital Media
• +5 more

Christopher Fry serves as Senior Lecturer at the University of Westminster, teaching BA Hons Creative Media Arts and MA Art and Emerging Technologies. His academic journey includes Fine Art and Multimedia Arts studies at Liverpool School of Art and Design and a 2008 PhD from Wimbledon School of Art investigating audience roles in pervasive artworks. Fry's research centers on generative systems, exploring data as creative material and coding as generative tool with current emphasis on Generative AI's emerging vocabulary. His work critically examines visuality in virtual spaces, haptic qualities in digital lines, and the productive potential of errors in digital practice. Analysis of his 2016-2022 publications reveals consistent output at the Generative Art Conference, evolving from foundational generative techniques toward critical AI engagements. Key themes include human-system relationships in automated creation, sensory experience in digital environments, and error-driven creative methodologies. Fry actively supervises doctoral research, currently guiding Mx Ocean Stefan's project on unbodied performance in post-Covid/posthuman contexts. His teaching directly integrates research expertise in digital media and emerging technologies. Notable artistic outputs include the Radiant Eye series (2019), Manual Assembly projects (2016), and conference presentations examining visual regimes (2022), error encounters (2021), and certainty/fragility in automated creation (2020).

Jan FröhlichView profile

Professor

• High Dynamic Range (HDR)
• Wide Color Gamut (WCG)
• Image Encoding
• +5 more

Prof. Dr. Jan Fröhlich is a Professor for Motion Picture Engineering at Stuttgart Media University (HdM), specializing in advanced imaging technologies. His research focuses on high dynamic range (HDR) and wide color gamut (WCG) image encoding, color rendering, camera metrology, and HDR workflows. Prior to his academic appointment, he held key industry positions including Senior Image Scientist at ARRI Munich where he contributed to professional cinema camera systems, and Dolby Laboratories where he helped develop the ITU Rec.2100 ICtCp color space and Dolby Vision platform. He also served as Technical Director at CinePostproduction GmbH. His core research areas include: HDR/WCG encoding and color science Virtual production workflows Camera metrology and image sensor technology Perceptual aspects of high frame rate and HDR imaging Real-time HDR/SDR conversion systems Recent publications demonstrate extensive work in virtual production technologies, including LED volume workflows, HDR broadcast graphics, and light field displays. His research consistently addresses both theoretical foundations and practical implementation challenges in cinematography and broadcast engineering.

Shree K. NayarView profile

Professor

• Computational Imaging
• Computer Vision
• Computer Graphics
• +5 more

Shree K. Nayar is the T. C. Chang Professor of Computer Science in the School of Engineering at Columbia University, where he heads the Columbia Vision Laboratory (CAVE). He served as Department Chair from 2009-2012 and was Director of Research at Snap Inc. from 2018-2024. Nayar received his PhD from Carnegie Mellon University and has been at Columbia since 1991, progressing from Assistant to Full Professor. His educational background includes a PhD in Electrical and Computer Engineering from Carnegie Mellon University (1990), an MS from North Carolina State University (1986), and a BS from Birla Institute of Technology in India (1984). He began his career as a Research Engineer at Taylor Instruments in New Delhi before pursuing graduate studies. Nayar's research spans three interconnected areas: novel computational cameras that capture new forms of visual information, physics-based models for vision and graphics, and algorithms for scene understanding. His work in computational imaging has transformed digital photography, with applications in smartphones, robotics, virtual reality, and human-computer interfaces. His research has produced over 300 publications with nearly 60,000 citations and 80 patents. Analysis of his recent publications reveals a strong focus on computational imaging challenges including low-light vision, depth sensing, mobile interaction, and accessibility technologies. His work consistently bridges theoretical foundations with practical applications, as evidenced by commercial implementations of his assorted pixels technology in smartphone cameras. Elected to National Academy of Engineering (2008), American Academy of Arts and Sciences (2011), National Academy of Inventors (2014), and Indian National Academy of Engineering (2022) Okawa Prize (2023), IEEE PAMI Distinguished Researcher Award (2019) Two-time David Marr Prize winner (1990, 1995) - the highest honor in computer vision Multiple best paper awards at major conferences including SIGGRAPH Asia (2024) and ECCV (2024) National Young Investigator Award (1991), Packard Fellowship (1992) Nayar has supervised numerous PhD and Master's students throughout his career at Columbia. His lab has received continuous funding from NSF, industry partners, and foundations. The Columbia Vision Laboratory (CAVE) is known for its interdisciplinary approach, combining optics, hardware design, and algorithms to solve fundamental vision problems. Nayar's Bigshot Camera project demonstrates his commitment to education, providing hands-on learning experiences for students worldwide. The Columbia Vision Laboratory (CAVE) develops cutting-edge computational imaging and computer vision systems. Under Nayar's leadership, the lab has pioneered technologies including self-powered cameras, high dynamic range imaging systems, and novel computational cameras. The lab maintains strong industry connections, particularly through Nayar's role at Snap Research, and emphasizes translating research into real-world applications that benefit society.

• Robotics
• Computer Vision
• Machine Learning
• +5 more

Zhang Fangyi is a research fellow at Queensland University of Technology's School of Electrical Engineering and Robotics, specializing in robotics, computer vision, and machine learning. With a PhD completed in 2018 titled 'Learning real-world visuo-motor policies from simulation,' Zhang has established a strong research trajectory focusing on bridging the gap between simulation and real-world robotics applications. Zhang's research interests center around robotic perception and manipulation, with particular expertise in sim-to-real transfer techniques, tactile sensing systems, and graph neural networks. Their work spans multiple domains including robotic grasping, fabric manipulation, face clustering algorithms, and graphene-based sensor development. A consistent theme throughout Zhang's research is the development of robust systems that can effectively transition from simulated environments to real-world applications. The publication record shows a clear evolution from foundational work in sim-to-real transfer (2015-2019) toward more specialized applications in tactile sensing and material science (2021-2024). Recent work demonstrates expanding interests into graphene-based sensor technology while maintaining core expertise in robotic perception. Zhang frequently collaborates with leading researchers at QUT including Peter Corke, with whom they've published multiple papers on robotic grasping and tactile sensing. Zhang's research has practical applications across multiple domains including assistive robotics, sensor development, and computer vision systems. Their work on laser-induced graphene sensors shows particular promise for next-generation tactile interfaces and wearable technology.

Francois Xavier COUDOUXView profile

Professor

• Digital video communications
• Multimedia transmissions
• End-to-end optimization
• +7 more

Francois Xavier COUDOUX is a Professor in the Digital Communications group at IEMN DOAE and currently serves as Director of the Electronics Department at INSA Hauts-de-France since 2020. His academic career has been primarily associated with institutions in the Hauts-de-France region, including significant roles at the University of Valenciennes and now INSA Hauts-de-France. Within IEMN, he has held leadership positions including Deputy Director of IEMN-DOAE (2010-2018), member of the IEMN Laboratory Council (2001-2011), and current member of the Scientific Council of the IEMN (2019-present). His educational background includes a Doctorate in Electronics from the University of Valenciennes (1994), Magistère in Image Engineering (1991), DEA in Electronics: imaging and ultrasound (1991), Master's in Audiovisual Communication (1990), and DEUG in Sciences (1988). Professor COUDOUX's research focuses on four main areas: end-to-end optimization strategies for multimedia transmissions over wired or wireless networks; robust MIMO-OFDM transmission of video streams; video pre- and post-processing systems; and data transmission over electrical networks. His work integrates expertise in image/video processing with telecommunications to optimize quality of service in video communication systems. He has contributed significantly to the reduction of blocking artifacts in DCT-coded images and videos, developing perceptual approaches to enhance visual quality in compressed video. His scientific contributions have been recognized through numerous publications since the early 1990s, with consistent output in prestigious journals and conferences. His research shows a clear evolution from foundational work on blocking artifact reduction to more complex systems involving MIMO-OFDM transmission and cross-layer optimization approaches. The publications demonstrate expertise spanning signal processing, image/video coding, telecommunications, and perceptual quality assessment. Among his notable achievements are leadership of the ANR TOSCANE project (2007-2010), participation in the CPER 2009-2013 CISIT research program, and two research contracts with Philips Electronics Laboratories. He has also served as a scientific expert for the ANR, AERES, and for both Walloon and Flemish regions of Belgium. Professor COUDOUX has supervised 8 PhD theses throughout his career and has been actively involved in academic service, including organizing conferences like ISIVC 2012, serving on program committees for CISST and ITST conferences, and reviewing for journals including IEEE Communications Letters and IEEE Transactions on Broadcasting. His teaching responsibilities focus on telecommunication systems, digital communications, and signal processing, particularly in image and video domains.