Lab Director
Aggelos Katsaggelos
Aggelos Katsaggelos is Professor and Joseph Cummings Chair in the ECE Department at Northwestern University. He also runs the Image and Video Processing Laboratory (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
Henry Chopp
Henry Chopp is a postdoctoral researcher working in the Image and Video Processing Lab (IVPL) at Northwestern University. He received his bachelor’s degree in electrical engineering at Northwestern University. His research interests are in compressed sensing, data fusion, and machine learning. He is currently working with The Center for Scientific Studies of the Arts on subsampling and reconstruction of paintings using data fusion techniques, as well as rate-distortion optimization for object tracking.
Personal Website: Visit Henry’s Homepage
Asami Odate
Asami is a postdoctoral fellow and a member of the Image and Video Processing Lab at Northwestern University. She received her Ph.D. in Chemistry from Brown University in 2023, working on ultrafast dynamics of gas-phase molecules using Rydberg spectroscopy and X-ray scattering experiments. Prior to Brown, Asami completed her B.A. at Barnard College of Columbia University, during which she had the opportunity to work on pigment characterization of Henri Matisse’s cut-out works at the MoMA and the Metropolitan Museum of Art. The project sparked her interest in the intersection of arts and science, particularly in light-matter interaction of artists’ materials. Her current project attempts to reinvent polarized light microscopy (PLM), a tried-and-tested tool for material identification in the museum laboratory, by incorporating single-shot imaging capabilities coupled with deep learning to improve the efficiency and consistency of the characterization process. When she is not in the lab, Asami can often be found in a dance studio or café.
Personal Website: Visit Asami’s Homepage
Doctoral Students
Yunan Wu
Yunan Wu started her Ph.D. at the Image and Video Processing Lab (IVPL) in 2020 after completing her master studies in Biomedical Engineering at Northwestern University (NU) from 2018 to 2020. Yunan Wu received her bachelor’s degree of Biomedical Engineering from Southern Medical University (SMU), China, from 2014-2018. Her master thesis was using geometric Deep Learning on brain morphology to predict composite score of fluid intelligence and her undergraduate thesis is comparing 1D Convolutional Neural Networks (CNNs) with 2D CNNs in detecting ventricular fibrillation. Her research interests are in artificial intelligence healthcare, machine learning, deep learning and Computer Vision. Now she is working on projects related to Covid-19 diagnosis, Attention-based multiple instance learning, graph-based CNNs and head CT hemorrhage detections.
Personal Website: Visit Yunan’s Homepage
Shamal Lalvani
Shamal is a PhD student in Electrical Engineering at IVPL. Shamal’s primary research interest is the application of machine learning techniques and stochastic processes to neuroscience and mental health problems using models of decision making. Shamal’s PhD is funded from a grant from the Office of Naval Research (PI’s: Hans Breiter and Aggelos Katsaggelos), where he works on the application of computational behavior to preventing violence and suicidality. Some of Shamal’s other projects involve crowdsourcing, drift-diffusion modeling, sparse matrix factorization and track interpolation for binary star systems.
Personal Website: Visit Shamal’s Homepage
Hui Lin
Hui is currently working on medical image segmentation based on deep learning, such as left atrium wall segmentation and myocardial scar qualification of LGE MRI and coronary artery disease diagnosis of x-ray angiography. She received her master’s degree in mechanical engineering in 2019 and her bachelor’s degree in material processing and control engineering in 2016 from Huazhong University of Science and Technology (HUST). She likes exercises, like playing badminton and frisbee, strength training, and jogging. She is learning piano and crocheting.
Personal Website: Visit Hui’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
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 first year PhD student in Northwestern University’s Department of Electrical and Computer Engineering, co-advised by Professor Aggelos Katsaggelos and Professor Lee Cooper. Broadly, Lawrence is interested in machine learning methods development for biomedical applications, working in the Image and Video Processing Lab (IVPL) led by Professor Katsaggelos, as well as the Feinberg School of Medicine’s Computational and Integrative Pathology Group led by Professor Cooper. Prior to beginning his Ph.D., Lawrence worked at Columbia University’s Mailman School of Public Health as a senior programmer in the Department of Environmental Health Sciences, developing machine learning algorithms for use in environmental epidemiology. 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
Deanna Dimonte
Deanna received her B.S. in Electrical Engineering from Purdue with a minor in Math in 2017. There she did work simulating view factor with applications for thermophotovoltaics. Her research interest in computer vision was forged when she studied abroad for a semester at the University of Padova in 2016 where she followed a graduate computer vision course and developed a simple visual immersive system from fisheye lens photographs. She joined IVPL in Fall 2019 and is currently pursuing a Ph.D. in Electrical Engineering at Northwestern.
Xijun Wang
Xijun Wang is a Ph.D. student in the EECS Department working in the Image and Video Processing Lab (IVPL) at Northwestern University. She received her Bachelor’s degree from Yingcai Honors College of University of Electronic Science and Technology of China (UESTC). Her research interests lie in machine learning and deep learning, particularly focusing on computer vision tasks such as image/video generation, video restoration, image/activity classification, and temporal action localization. Currently, she is working on projects related to video restoration and generative models, including GANs, diffusion models, and VAEs.
Xinyi Wu
Xinyi Wu received the B.S. degree in computer science and technology from Nanjing University, Jinling College, Nanjing, China in 2017 and the M.S. degree in computer science from Northwestern University, Evanston, USA, in 2019. She joined the Image and Video Processing Laboratory (IVPL) led by Prof. Katsaggelos at Northwestern University in summer 2018, where she is currently pursuing the Ph.D. degree in electrical engineering. Her research at IVPL is centered on the use of deep learning models for various video generation tasks, with focus on the problems regarding video restoration and multimedia synchronization.
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
Charis Apostolidis
Charis joined the lab in 2022. He received a Master’s degree in mechanical engineering from Cardiff University, where he also completed a research internship working on activity recognition in video. He later spent time in industry, working in areas including robotics and cancer genomics, before returning to academia. Generally, Charis is interested in applying machine learning methods to medical problems. A project he is currently working on involves applying deep learning to seismocardiography (SCG) signals to detect aortic valve stenosis and predict various related metrics.
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
Peng Kang
Peng Kang is currently the final year Ph.D. candidate in the department of Computer Science at Northwestern University. His supervisor is Prof. Oliver Cossairt. And he works closely with Prof. Aggelos Katsaggelos. Prior to his Ph.D. study at Northwestern, he was a research assistant and obtained a research-based master at School of Computer Science of McGill University, under the supervision of Prof. Xue (Steve) Liu. Before that, he completed his bachelor’s degree in software engineering at Sun Yat-sen University. He has a broad interest in artificial intelligence and its applications. Previously, his research focused on 2nd generation neural networks – ANNs, including numerical analysis and their applications in recommender systems and computer vision. His current research focuses on 3rd generation neural networks – SNNs and their event-driven neuromorphic applications in vision, audio, and robotic learning. He believes building SNNs with lessons from ANNs can lead us to energy-efficient human-like artificial intelligence. He published papers on premier conferences and journals, like KDD, WSDM, WACV, ICIP, IJCNN, TNNLS, and Frontiers in Neuroscience.
Personal Website: Visit Peng’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.