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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.

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Postdoctoral Researchers

 

Santiago Lopez-Tapia

I am Santiago.

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Doctoral Students

 

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.

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Emanuel (Manny) Azcona

Emanuel is a Ph.D. candidate in Electrical Engineering and a senior member of the Image and Video Processing Lab (IVPL) at Northwestern University (NU), where he has also received an M.S. in Electrical Engineering. Prior to NU, he attended New York University (NYU), where he received his B.S. in Electrical Engineering, along with minors in Integrated Digital Media and Computer Science. His primary research interests are in graph representation learning for medical imaging, graph signal processing, and predictive modeling of human decision-making using heterogeneous multipartite graphs. Some of his prior work has analyzed 3D surface mesh representations of the human brain structures (cortical ribbon and subcortical nuclei) and utilized spectral graph neural networks (GNN) models for the in-vivo classification of Alzheimer’s disease (AD). In addition, he has also developed conditional generative GNN models that have been shown to generate brain structures whose shape may vary based on AD diagnosis. He is currently developing a hybrid AI framework that integrates latent cognitive features (such as loss aversion) from a behavioral framework known as Relative Preference Theory (RPT) and heterogeneous GNNs to predict human expressed behavior and/or decision-making.

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ProjectsAlzheimer’s Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes

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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.

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Srutarshi Banerjee

Srutarshi is a Ph.D. candidate in ECE Department working in the Image and Video Processing Lab (IVPL) at Northwestern University. His research interests include image and signal processing, computer vision, machine learning as well system level implementation of these algorithms. He received his Bachelors in Electrical Engineering (with Honors) from Jadavpur University, Kolkata, India with a focus in Control Systems. He further pursued his Masters of Technology in Instrumentation from Indian Institute of Technology, Kharagpur, India. After his Masters, he worked for a couple of years as a Research Scientist in Bhabha Atomic Research Centre, Mumbai, India on Electron Particle Accelerators developing Control Systems and Beam Instrumentation Modules. He is currently developing reconfigurable adaptive imaging architectures to dynamically acquire videos for strategic applications.

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Projects: An Adaptive Video Acquisition Scheme for Object Tracking

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Semih Barutcu

Semih Barutcu received his B.Sc. in Electrical & Electronics Engineering at Bogazici University – Istanbul together with a Minor Degree in Business Administration & Management. In 2018, he received his M.S. in Electrical Engineering and Computer Science at Northwestern University. He is currently pursuing his Ph.D. at Northwestern University’s Electrical Engineering Department and working in the Image and Video Processing Lab (IVPL). His research interests are in computational imaging, inverse problems, deep learning, and computer vision. His primary projects include Deep Generative and Image Priors on X-ray Ptychography Physics-Based Deep Image Priors on Limited-Angle Computed Tomography, Deep Image Classification for Covid-19 Chest X-Rays, and direct coupling of X-ray Ptychography and Tomography for 3D object recovery.

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Projects:  X-ray Ptychography with Deep Generative and Image Priors, Limited-Angle Computed Tomography with Physics-Based Deep Image Priors, DeepCovidXR: Covid-19 Classification from Chest X-Rays, Simultaneous 3D X-Ray Ptycho-Tomography Reconstruction, Acquisition Speed Improvement in X-Ray Ptychography

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Henry Chopp

Henry Chopp is a Ph.D. student in the EECS Department working in the Image and Video Processing Lab (IVPL) at Northwestern University. He received his bachelor’s degree in electrical engineering also 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 rate-distortion optimization for object tracking.

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Projects: An Adaptive Video Acquisition Scheme for Object Tracking

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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.

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Shamal Lalvani

Shamal is a PhD student in the image and video processing lab. Shamal’s interests are in neuroscience and pattern recognition. Shamal’s main application interest is in medical problems, particularly neuroimaging and mental health. Some of Shamal’s projects involve automatic detection of Hemorrhage in Head CT Data, using neuro-imaging and behavioral data to predict addiction/mental health and destructive behaviors with Gaussian Processes, as well as analytical approximations to neural networks without stochastic gradient descent. After his PhD, Shamal aspires to pursue a research career in the field of Computational Psychiatry.

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Projects: Emergent Findings on Head CT , Predicting COVID and Mental Health Conditions from Computational Behavioral Measures

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Hui Lin

Hui is currently working on image segmentation based on deep learning for myocardical scar qualification. She received her Master’s degree in Mechanical Engineering 2019 and Bachelor’s degree in material processing and control engineering 2016 from Huazhong University of Science and Technology (HUST). She likes exercises, like playing badminton, frisbee and jogging.

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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 is interested in image processing and computer vision techniques. She is currently working on deep learning for video super-resolution. Before that, Xijun received her Bachelor’s degree from Yingcai Honors College of University of Electronic Science and Technology of China (UESTC).

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Projects: Video Super-Resolution

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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.

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Projects: Video Super-Resolution

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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  in Biomedical Engineering from Southern Medical University (SMU), China, from 2014-2018. Her master thesis is 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, Attention-based multiple instance learning, graph-based CNNs and head CT.

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Projects: Emergent Findings on Head CT , Geometric Deep Learning on Fluid Intelligence Prediction

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Master’s Students

 

Harkirat Gill

Harkirat Gill is a student in the Masters of Artificial Intelligence program and received his B.S. from Benedictine University where he majored in computer science and mathematics. His interest is in deep learning and its applications in computer vision. In past research, he has explored methods of defending deep vision models against adversarial attacks. His current work aims to create better video super resolution models using the attention based transformer architecture.

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Renpin Luo

Renpin is a current Masters student in Computer Science with specialization in Artificial Intelligence at Northwestern University. He graduated from Stevens Institute of Technology in the summer of 2020, and he focused on the study of computer engineering. Presently, his research focus on Transformer-based architecture for super resolution video led by Prof. Aggelos Katsaggelos.

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Undergraduate Students

 

Siyuan Chai

Siyuan (Sam) Chai is an undergraduate in Computer Science at Northwestern. He has broad interests across high-performance computing, machine learning, and operating system. His work in IVPL focused on AI in medical imaging. He’s also working on system research in OS and HPC with Prof. Dinda

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Amil DravidAmil Dravid

Amil Dravid is an undergraduate computer science student at the McCormick School of Engineering and Applied Sciences (Class of 2023). His research interests include deep learning, machine learning, computer vision, generative models, and medical imaging.

ProjectsAlzheimer’s Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes

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PublicationsView Amil’s Works with IVPL | View Amil’s Work outside IVPL