Lab Director
Aggelos Katsaggelos
Aggelos Katsaggelos is Professor and Joseph Cummings Chair in the ECE Department at Northwestern University. He also runs the AI in Multimedia – Image and Video Processing Laboratory (AIM-IVPL), whose objective is to generate cutting-edge research results in the fields of multimedia signal processing, multimedia communications, and computer vision. IVPL works in a variety of problems (e.g., recovery, compression, segmentation, and speech and speaker recognition) and applications areas (e.g., medical, multi-spectral, and astronomical image processing). Dr. Katsaggelos is a Fellow of the IEEE (1998) and SPIE (2009), the co-inventor of seventeen international patents, the recipient of the IEEE Third Millennium Medal (2000), the IEEE Signal Processing Society Meritorious Service Award (2001), the IEEE Signal Processing Society Technical Achievement Award (2010), and co-author of several award-winning papers.
Northwestern Website: Visit Dr. Katsaggelos’s Homepage at Northwestern University
Postdoctoral Researchers
Santiago Lopez-Tapia
Received bachelor’s, master’s, and Ph.D. degrees in computer science from the University of Granada in 2014, 2015 and 2021, respectively. He has worked for 6 years with the Visual Information Processing Group, Department of Computer Science and Artificial Intelligence, University of Granada. Since October 2021 he has been working with the Image and Video Processing Lab at Northwestern University. His research mainly focuses on the use of deep learning models for image restoration and classification
Personal Website: Visit Santiago’s Homepage
Leandros Stefanopoulos
Leandros Stefanopoulos earned his Ph.D. (2025) and Medical Informatics M.Sc. (2016) from the School of Medicine and his B.Sc. in Mathematics (2013) from the Department of Mathematics of Aristotle University of Thessaloniki, Greece. Currenlty, he is a Postdoctoral Scholar at Northwestern University, Department of Electrical and Computer Engineering. His research focuses on Behavioral Informatics, Machine Learning, Deep learning and mHealth
Personal Website: Visit Leandros’s Homepage
Shamal Lalvani
Shamal is a postdoctoral research assistant in IVPL working on causal analyses of glitches in gravitational waves from the LIGO (laser interferometer gravitational-wave observatory) project. Shamal’s postdoctoral assistantship is part of the Gravity Spy project – a grant funded by the national science foundation to integrate citizen science in detection of glitches in LIGO project. Shamal holds a PhD in electrical engineering, a MS in mathematics and a MS in operations research.
Personal Website: Visit Shamal’s Homepage
PhD Students/ Candidates
Manuel Ballester
My name is Manuel Ballester, a PhD candidate at Northwestern University, Computer Science department. I have studied a BSc in Mathematics at University of Cadiz (Spain), and an Elite MSc Program in Advanced Optical Technologies at University Erlangen-Nuremberg (Germany). I have an academic interest in physics, mathematics, and computation. I apply the knowledge from these areas to solve complicated problems in modern optics. In the broad branch of optics, my field of study is computational optics and imaging techniques. I am currently working on three projects: – Dynamic 3D holographic displays. – Wave propagation in scattering media. – Optical characterization of dielectric thin films. We intend to bring new computational, optimization, and machine learning techniques to different fields of optics and imaging.
Lawrence Chilrud
Lawrence is a fourth year Ph.D. candidate in Electrical Engineering. Broadly, he develops machine learning and artificial intelligence algorithms for problems in precision medicine and public health. Lawrence is especially interested in uncertainty quantification techniques for deep learning models, and works mostly with radiological and histopathological imaging data. His current projects include brain tumor biomarker prediction from MRI imaging and the development of novel loss function penalties to train highly sensitive or specific histopathology models. Lawrence is funded through the National Science Foundation’s Graduate Research Fellowship Program for his proposal on ensemble learning and Bayesian inference in medical imaging. He is co-advised by both Dr. Aggelos Katsaggelos (Dept. of Electrical and Computer Engineering, McCormick School of Engineering) and Dr. Lee Cooper (Dept. of Pathology, Feinberg School of Medicine). Formerly, Lawrence was a senior programmer at Columbia University’s Mailman School of Public Health, working in the Department of Environmental Health Sciences under the mentorship of Dr. Marianthi-Anna Kioumourtzoglou. Lawrence’s research at Mailman focused on the development of dimension reduction methods for assessing complex mixtures of environmental exposures. Lawrence also worked to develop automatic fact-checking models to identify misinformation surrounding COVID-19, climate change, and the 2020 U.S. presidential election under Dr. Kathleen McKeown (Dept. of Computer Science, Columbia University). Lawrence received his B.A. in Computer Science from Columbia University in May of 2020, specializing in Intelligent Systems.
Personal Website: Visit Lawrence’s Homepage
Charis Apostolidis
Charis is an electrical engineering PhD candidate, primarily interested in medical applications. His research is focused on the AI-driven assessment of diseases of the aorta. He is co-advised by Dr. Katsaggelos at AIM-IVPL, and by Dr. Michael Markl in the Cardiovascular MRI Group at the Northwestern Department of Radiology. Charis received an integrated Master’s degree in mechanical engineering from Cardiff University (2017) and a Master’s degree in electrical engineering from Northwestern University (2023). He has industry experience in areas including biotech (cancer genomics) and robotic process automation.
Personal Website: Visit Charis’s Homepage
Jiaqi Guo
Jiaqi Guo obtained his bachelor’s degree from the University of Electronic Science and Technology of China (UESTC) in 2021. In 2022, he completed his master’s degree in electrical engineering from Northwestern University. Currently, Jiaqi is pursuing a PhD (start from 2023 Win) in Electrical Engineering at Northwestern University and is a member of the Image and Video Processing Lab (IVPL). His research interests center on developing machine learning methods for biostat/medical applications, image enhancement and geometrical deep learning on graphs.
Personal Website: Visit Jiaqi’s Homepage
Philipp Srivastava
Philipp is a PhD student working with the Image and Video Processing Lab (IVPL) on POSYDON, a next-generation single and binary-star population synthesis code incorporating full stellar structure and evolution modeling. Outside of the project his research interests include solving computer vision and signal processing problems using the latest deep learning techniques. He earned his B.S in Computer Science with a minor in Mathematics from Denison University in 2021.
Patrick Koller
Patrick Koller returned to Northwestern in September 2024, eighteen months after completing his master’s thesis visit in the same lab, to begin a PhD in Electrical and Computer Engineering in the AI in Multimedia Image and Video Processing Lab (AIM-IVPL) led by Professor Katsaggelos. He earned a bachelor’s in Electrical Engineering from the Zurich University of Applied Sciences [https://www.zhaw.ch/en/engineering] and a master’s in Data Science from the Eastern Switzerland University of Applied Sciences [https://www.ost.ch/en/] (OST), completing both degrees while working in industry.
Patrick’s research belongs to the SkAI Institute [https://skai-institute.org/] pillar “AI-Accelerated Simulations with Multiscale Astrophysics.” He designs physics-informed neural surrogates and neural operators that embed the governing differential equations of astrophysical flows directly into the training objective. By enforcing conservation laws and boundary conditions alongside sparse simulation or observational data, these networks yield physically consistent solutions orders of magnitude faster than classical solvers and often more accurate than purely data-driven models, enabling rapid parameter sweeps, uncertainty quantification, and real-time exploration from stellar interiors to galaxy clusters.
Alongside his academic pursuits, Patrick has accumulated more than a decade of parallel industry experience, most recently as a data scientist at Kistler AG [https://www.kistler.com/INT/en/], the global leader in dynamic measurement technology for pressure, force, torque, and acceleration. Experience that still drives his commitment to translating theoretical advances into deployable solutions. Beyond the lab, the Swiss native explores Chicago’s blues venues, plays electric guitar, and stays active through cycling, distance running, and martial arts.
Personal Website: Visit Patrick’s Homepage
Mingzhen Li
Mingzhen is a Ph.D. student in the Department of Computer Science at Northwestern University, co-advised by Professor Aggelos K. Katsaggelos and Professor Daniel Kim. His research focuses on computer vision, MRI imaging applications, inverse problems, and foundation models. He is a member of the Image and Video Processing Laboratory (IVPL) led by Professor Katsaggelos, as well as the Kim Cardiovascular MRI Research Group at Northwestern’s Feinberg School of Medicine, led by Professor Kim. Mingzhen received his Bachelor of Science degree with a double major in Computer Science and Mathematics from Washington University in St. Louis in 2024.
Personal Website: Visit Mingzhen’s Homepage
Shinjan Dutta
Shinjan is a PhD candidate in the Electrical Engineering department and a member of the Image and Video Processing Lab at Northwestern University (NU). He received his MS in Electrical Engineering from Northwestern University in 2021. Prior to Northwestern, Shinjan received his Bachelor in Technology degree in Mechanical Engineering from Manipal Institute of Technology, Karnataka, India, in 2019. He discovered his interest in Computer Vision while working on his capstone project on humanoid robots at Indian Institute of Space Science and Technology, during B.Tech. He worked on using deep learning and computer vision to detect Covid 19 on chest X-Ray images during the height of the pandemic. The model achieved better performance than 5 thoracic radiologists from Northwestern Hospital. He is currently working in collaboration with Argonne National Labs and Lawrene Berkley National Lab (UC Berkley) to help use computer vision to understand 3D structures of atoms of different materials and which crystal systems they belong to.
Personal Website: Visit Shinjan’s Homepage
Amit Adate
Amit Adate started his Ph.D. at the Image and Video Processing Lab (IVPL) in 2020 after completing an MS in Computer Science with a specialization in Artificial Intelligence at Northwestern University. He received his bachelors degree in computer science from Vellore Institute of Technology (VIT), India, in 2018. He is primarily interested in deep learning, with applications in computer vision. Currently, his projects are related to Medical Imaging and Activity Recognition.
Personal Website: Visit Amit’s Homepage
Master’s Students
Saumya Pailwan
Saumya is a Master’s student in Computer Science at Northwestern University, currently working with the Image and Video Processing Lab (IVPL) on a registration problem involving brainstem regions in glioblastoma patients. Her research interests include deep learning, with a focus on computer vision and generative modeling. Prior to her graduate studies, she worked for a year as a Software Engineer at a Silicon Valley startup, where she contributed to the development of real-time AI systems. Saumya completed her Bachelor’s in Technology in Computer Science with a minor in Artificial Intelligence and Machine Learning from Mumbai, India.
Personal Website: Visit Saumya’s Homepage