Prof. Rama Chellappa

Prof. Rama Chellappa is a Bloomberg Distinguished Professor with joint appointments in the Departments of Electrical and Computer Engineering and the Biomedical Engineering (School of Medicine) at the Johns Hopkins University (JHU). Prior to joining JHU in August 2020, he was a Distinguished University Professor and a Minta Martin Professor of Engineering at the University of Maryland (UMD), College Park, MD. He received the B.E. (Hons.) degree in Electronics and Communication Engineering from the University of Madras, India in 1975 and the M.E. (with Distinction) degree from the Indian Institute of Science, Bangalore, India in 1977. He received the M.S.E.E. and Ph.D. Degrees in Electrical Engineering from Purdue University, West Lafayette, IN, in 1978 and 1981 respectively. During 1981-1991, he was a faculty member in the department of EE-Systems at University of Southern California (USC). During 1991-2020, at UMD, he was a Professor of Electrical and Computer Engineering (ECE) and an affiliate Professor of Computer Science at University of Maryland (UMD), College Park. He was also affiliated with the Center for Automation Research, the Institute for Advanced Computer Studies (Permanent Member) and the Applied Mathematics and Scientific Computing Program. His current research interests are computer vision, machine learning, artificial intelligence with applications in face recognition, 3D modeling from video, image and video-based recognition of objects, events and activities, medical imaging, domain adaptation and generalization.

Cheng Peng

Cheng Peng (https://sites.google.com/view/cheng-peng) is a post-doctoral fellow at the Johns Hopkins University and a member of the Artificial Intelligence for Engineering and Medicine (AIEM) Lab, advised by Prof. Rama Chellappa. He obtained his PhD in Computer Science from the Johns Hopkins University and his master’s and bachelor’s degrees in Electrical Engineering from the University of Maryland, College Park. Cheng’s research focuses on 3D computational imaging and its application in the natural and medical image domains. He has published several works in 3D image reconstruction, super-resolution, semantic segmentation, and view synthesis in primer conferences such as CVPR, MICCAI, AAAI, MedIA, MIDL, etc. A common theme in his work is to incorporate imaging physics and domain adaptation techniques to ensure algorithm robustness in non-ideal acquisitions.

Abhay Yadav

Abhay Yadav is an Assistant Research Scientist at Johns Hopkins University and a member of the Artificial Intelligence for Engineering and Medicine (AIEM) Lab, advised by Prof. Rama Chellappa. Prior to joining the AIEM Lab, he worked as an Applied Scientist – AI/ML at Comcast AI Lab, focusing on practical problems in Computer Vision, Recommender Systems, and NLP. He earned his PhD and Master’s in Computer Science from the University of Maryland, College Park, where he specialized in efficient and automated training methods for deep networks targeting computer vision applications. Additionally, he holds an M.E. (with Distinction) degree from the Indian Institute of Science, Bangalore, India. He has published papers in prestigious conferences such as ECCV, NeurIPS, ICLR, ICASSP, ICPR, AISTATS, BMVC, and LREC-COLING. Visit his Google Scholar profile for detailed publications.

His research interests include Large Scale Machine Learning and Deep Learning, Generative AI, Transformers, Large Language Models (LLM), Recommender Systems, Knowledge Graph Embeddings, Computer Vision, CNN, Graph Neural Networks, and Multi-Modal Deep Learning. His current focus is on the intersection of 3D image reconstruction and NLP.

Ram Prabhakar

Ram Prabhakar is a Postdoctoral Research Fellow at Johns Hopkins University working with Prof. Rama Chellappa. His research focus lies in computer vision, machine learning and image processing. He received his Ph.D. from Indian Institute of Science in 2022 where he worked with Prof. R. Venkatesh Babu in the Video Analytics Lab. Before coming to IISc, Dr. Prabhakar graduated from Anna University with B.E (ECE) in 2010 and NIT Rourkela with M.Tech in 2014. Dr. Prabhakar’s Ph.D. research focused on developing deep learning based computational photography techniques for improving high dynamic range imaging in unconstrained scenarios.

Maitreya Suin

Maitreya Suin is a Postdoctoral Research Fellow at the AIEM lab at Johns Hopkins University. He received his M.S. and Ph.D. degrees in 2022 from IIT Madras, where he primarily worked on building adaptive neural networks for image and video restoration tasks. Before that, he received his B.Tech. degree in ECE from the IEM Kolkata in 2016. He is currently working with Prof. Rama Chellappa on computer vision problems.

Ji Young Byun

Ji Young Byun is pursuing a Ph.D. degree with the Department of Biomedical Engineering, Johns Hopkins University. She received B.S. and M.S. in Bio and Brain Engineering from the Korea Advanced Institute of Science and Technology. Her research interests include medical image analysis.

Shravan Chaudhari

Shravan Chaudhari is a first year PhD student in the department of Computer Science at Johns Hopkins University. Previously he completed his MS in Computer Science from New York University (Courant Institute of Mathematical Sciences). He received his bachelor’s degree in Electronics & Instrumentation engineering from Birla Institute of Technology and Science Pilani (Goa Campus). He is co-advised by Prof. Rama Chellappa and Prof. Suchi Saria. His current research focuses on developing trustworthy and safe AI by tackling distribution shift in machine learning and dealing with out-of-distribution data.

Ime Essien

Ime Essien is a first year Phd student in Biomedical Engineering program as a Vivien Thomas Scholar and GEM Fellow. He studies under Dr. Rama Chellappa focusing on machine learning and medicine. He received a B.Sc. and M.Eng. degrees in electrical engineering from Morgan State University as a Martin Jenkins Scholar. His research interests include bioinformatics, machine learning, and high performance computing.

Yuxiang Guo

Yuxiang Guo is a first-year Ph.D. student in the Department of Electrical Computer Engineering, Johns Hopkins University. Before that, he receives an M.S at Northwestern University and a B.E at the University of Electronic and Technology of China. His research area currently focuses on computer vision and machine learning. His advisor is Dr. Rama Chellappa.

Ayush Gupta

Ayush Gupta is a PhD student in the Department of Computer Science from Johns Hopkins University. Previously, he received his B.E. degree in Computer Science in 2022 from Birla Institute of Technology and Science, Pilani, India, where he worked as an undergraduate researcher at the ADAPT Lab. His primary research interests include computer vision and its applications in security and biometrics.

Namitha Guruprasad

Namitha Guruprasad is a first-year PhD student in the Department of Electrical and Computer Engineering at The Johns Hopkins University (JHU). Previously, she completed her MSc in Computing Science in 2023 from University of Alberta, Canada, where she worked as a Graduate Research Assistant with her thesis focusing on computer vision and cancer research. She received her Bachelor’s (BE) degree in Computer Science and Engineering in 2020 from Visvesvaraya Technological University (VTU), India, with her research work in image and video processing and data science. Namitha’s primary research interests include computer vision and machine learning and their applications in several domains, including healthcare.

Carl Harris

Carl Harris is a first-year Ph.D. student in the Department of Biomedical Engineering, Johns Hopkins University. Previously, he received his bachelor’s degree in mathematics and neuroscience from Dartmouth College and spent two years conducting machine learning research at the NIH. His research focus is machine learning and healthcare.

Siyuan Huang

Siyuan Huang is a PhD student in the AIEM lab, Department of Electrical and Computing Engineering, Johns Hopkins University. He previously was a Graduate Research Assistant at Tsinghua Laboratory of Brain and Intelligence, Tsinghua University. Before that, he was an Associate Researcher at Alternative Computing Group, National Institute of Standards and Technology. He received a Master’s degree in Computer Science at George Washington University. His current research area is computer vision. His supervisor is Prof. Rama Chellappa.

Xijun Liu

Anita Madani

Anita Madani is a first-year PhD student in Electrical and Computer Engineering at Johns Hopkins University. She earned her Bachelor’s degree in Electrical Engineering from Sharif University of Technology. Her research focuses on computer vision, machine learning, and their applications in engineering, healthcare, and related fields.

Laura McDaniel

Daniel Olshvang

Daniel Olshvang is a Ph.D. student in the department of Biomedical Engineering, Johns Hopkins University. He received his B.Sc. in Biomedical Engineering at the Technion – Israel Institute of Technology, and has spent several years working in the biomedical industry and leading product development. His research interests include machine learning and its implications on medicine and biomedical data science.

Basudha Pal

I am a PhD student in the Electrical and Computer Engineering department at Johns Hopkins. I am interested in working at the intersection of deep learning and medicine, both medical imaging and computational biology. Previously I received my B.Tech degree in Electronics and Communication Engineering from Manipal Academy of Higher Education in India where I worked on Localization of magnetocardiographic sources using probabilistic approaches. I have also had the privilege of working on computer assisted radiology at ÉTS Montréal as a MITACS GRI Scholar.

William Paul

William Paul is a Ph.D. student in the department of Computer Science (CS) at Johns Hopkins University. He also holds a position as a researcher in the Artificial Intelligence group at the Johns Hopkins Applied Physics Laboratory (APL), where he develops machine learning techniques for various application areas including computer vision and robotics. William earned his BA degree in Computer Science, Statistics, and Applied Mathematics from UC Berkeley.

Shraman Pramanick

Shraman is a fourth year Ph.D. student in the Department of Electrical and Computer Engineering at Johns Hopkins University, Baltimore, USA, under the supervision of Professor Rama Chellappa. His research focuses on applications of deep learning and computer vision to multimodal learning (vision + X), egocentric vision and video-language pre-training. For more details, please visit his homepage.

Tawsifur Rahman

Tawsifur Rahman is a PhD student in Biomedical Engineering at Johns Hopkins University and working with computational pathology on whole slide imaging. He worked as a research assistant in the machine learning group at Qatar University for about 2 years. Moreover, he received his M.Sc. degree in Biomedical Engineering from the University of Dhaka (Bangladesh) as an ICT research fellow from Information Communication &Technology (ICT) ministry of Bangladesh. His research interests include medical image analysis, big clinical data processing, computer vision, and deep learning.

Arun Reddy

Arun Reddy is a Ph.D. student in the department of Electrical & Computer Engineering (ECE) at Johns Hopkins University. He also holds a position as a research engineer in the Artificial Intelligence group at the Johns Hopkins Applied Physics Laboratory (APL), where he develops machine learning techniques for various application areas including machine vision, NLP and wireless signal processing. Arun earned his MSE degree from Johns Hopkins University and AB and BE degrees from Dartmouth College.

Lucia Rhode

Lucia Rhode is a first-year PhD student in the ECE department of JHU working with Professor Rama Chellappa. She received her BE in Electrical Engineering from the Cooper Union for the Advancement of Science and Art, where she previously worked on projects related to Computer Vision, Pose Estimation, and Exoskeletons.

Aniket Roy

Aniket is a Ph.D student in the department of Computer Science, Johns Hopkins University. Previously he received the M.S. degree in research from the Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur. His primary research interests include computer vision, machine learning and digital forensics.

Samuel Schmidgall

Samuel Schmidgall is a PhD student in the Department of Electrical and Computer Engineering at Johns Hopkins University. Previously, he received his B.S. degree in Computer Science in 2021 from George Mason University. From 2019 to 2023 he was a scientist at NRL working on low-energy AI for space robotics. His primary research interests include computer vision and vision-guided robotics.

Ketul Shah

I am interested in working at the intersection of computer vision, machine learning and computer graphics. I have worked on projects related to multimodal activity detection, generative models for 3D shapes, photorealistic image synthesis, among others. I obtained a MS in ECE from University of Maryland, College Park and previously completed my Dual Degree in Electrical Engineering (with a minor in Operations Research) from IIT Madras, where I worked at the Computational Imaging Lab under Prof. Kaushik Mitra.

Zhimin Shao

Zhimin Shao is a first-year Ph.D. student in the Department of Electrical and Computer Engineering at Johns Hopkins University. Before that, she obtained her master’s and bachelor’s degrees from Tsinghua University. Her research area currently focuses on medical image analysis. Her advisor is Dr. Rama Chellappa.

Vineet R. Shenoy

Vineet is a currently a research assistant working with Professor Rama Chellappa. His research interests include computer vision and signal processing. He is originally from West Windsor, New Jersey and completed his undergraduate work at Rutgers University – New Brunswick.

Tyler Skow

Tyler Skow is a first-year Ph.D. student in the Department of Computer Science, Johns Hopkins University. Previously, he received his bachelor’s degree in computer science from Princeton University. His research focus is adversarial machine learning.

Michael Sprintson

Michael Sprintson is a first year PhD student in Electrical Engineering and graduated from Rice University with a BS in Electrical Engineering and BA in Computer Science.

Zhaoyang Wang

Zhaoyang is a PhD student under the supervision of Prof. Rama Chellappa in the Department of Computer Science at Johns Hopkins University. Previously, he received an MRes degree from Imperial College London. His primary research areas are Gait Recognition, Geometric Deep Learning, 3D Shape Reconstruction and Medical Image Analysis.

Guoyizhe Wei

Guoyizhe Wei is a Ph.D. student in the Department of Electrical Computer Engineering, Johns Hopkins University. Before that, she receives an M.S at Tsinghua University and a B.E at Xi’an Jiaotong University. Her research area currently focuses on computer vision and federated learning. Her advisor is Dr. Rama Chellappa.

Gina Wong