David Han is the inaugural holder of the Bruce Eisenstein Endowed Chair and professor of electrical and computer engineering. He is an ASME Fellow and an IEEE senior member. Dr. Han received his B.S. degree from Carnegie Mellon University and M.S.E. degree from the Johns Hopkins University. He completed Ph.D. degree at the Johns Hopkins University under the supervision of Andrea Prosperetti. He has previously held positions as a research and faculty member at the Johns Hopkins University Applied Physics Laboratory, Army Research Laboratory, and the University of Maryland at College Park, and has additionally served as Distinguished IWS Chair Professor at the US Naval Academy. He spent over 11 years as program officer at the Office of Naval Research and served as its Deputy Director of Research, overseeing the Discovery and Invention portfolio of over $900 million from 2012 to 2014. He also served as Associate Director for Basic Research in Machine Intelligence and Robotics in the Office of the Assistant Secretary of Defense Research & Engineering from 2014 to 2016, helping to oversee an over $2 billion annual research portfolio. Han has authored or coauthored over 120 peer-reviewed papers, including four book chapters.
I am currently pursuing my Ph.D. degree at the Department of Electrical and Computer Engineering, Drexel University, under the supervision of Professor D. Han. I am interested in deep learning problems as well as their applications in computer vision. I am also interested in other machine learning problems like feature selection, dimensionality reduction in high-dimensional data, and ensemble learning. During my M.Sc. degree at the Polytechnic University of Milan, I have done research in the field of feature selection in highly sparse data (Single Cell Hi-C data) and Cell Stage prediction. At iMaPLe, I do research on object detection, classification, and identification using computer vision techniques.
I am an Electrical Engineer by profession and have great interest in Computer Vision, Robotics and Machine Learning. I completed my Bachelors and Masters in my home country “Pakistan”. During bachelors, I worked for differently-abled through my senior-year project, “Techno-talk” which is an American Sign Language Translator. During Masters, I performed research on Battery Management Systems for Electric Vehicles. I also performed research on Medical Imaging, Robot localizations, Drone detection, localization and targeting, and Engineering Education for young learners. Besides research, I have great interest and passion for teaching. I have taught at various universities as well as top notch college in Pakistan. At iMaPLe, I am performing research on the underwater acoustics systems wherein I am dealing with acoustic classification and detection in underwater scenarios, benefiting the naval sector.
I am pursuing a PhD in Machine Learning in the Department of Electrical and Computer Engineering at Drexel University under Dr. David Han’s supervision. My passion for sound recording and electronics has culminated in the opportunity at iMaPLe to apply ML to acoustic scene understanding. I received my BSEE from UMD and MS Applied and Computational Mathematics from The Johns Hopkins University. During my sojourn in private industry I developed hardware and firmware for several commercially successful digital telephony interface devices. I am a senior engineer at the National Institutes of Health in Bethesda, Maryland, where I manage the cyclotron section in the CC/PET Department. In my spare time I learn human and computer languages and read books. One of my goals is to become fluent in German, French, Python, and at least one other world language. My favorite novel is “Le Comte de Monte-Cristo” by Alexandre Dumas.
Visiting M.Sc. Student
I am a second-year M.S. student in the Pattern Recognition and Machine Learning Laboratory with Seongwhan Lee at Korea University. I came to Drexel University as a visiting scholar working with Prof. David Han. My research objective lies in computer vision, computer graphics, and machine learning. Through my research, I want to make it easier for people to create 3D content and interact with physical objects in a virtual environment. I am currently working on image-based 3D scene reconstruction with multiple objects. The main objective of this research is to enable complex scene understanding with only a limited number of images and achieve accurate estimations of occluded regions.
Visiting M.Sc. Student
I am a M.S. student in the Supply Chain & Value Network Analytics Lab at Korea university, visiting Drexel to perform short-term research with Prof. Han. My research interests lie primarily in reinforcement learning. During the stay at iMaPLe, I’d like to combine computer vision techniques with RL to enable computers perform better scene understanding.
I am working towards an M.Sc. degree in Machine Learning Engineering in the Department of Electrical and Computer Engineering at Drexel under the supervision of Dr. David Han. I received my B.Sc. and M.Sc. degrees in Electrical Engineering from Sadjad University. My previous research was focused on Genetic Algorithms and their application in optimizing power allocation in CDMA cellular systems. My research interests lie in machine vision, machine learning, and deep learning. As a researcher at iMaPLe, I am interested in using machine learning techniques to solve real-world computer vision problems. Apart from my academic studies, I enjoy photography, especially landscape photography in my favorite mode, black and white. Persian calligraphy is my other favorite activity in my free time.
I am A Senior at Drexel University studying B.S. in Computer Engineering and M.S. in Machine learning engineering with minor in Math and Finance. I am interested in working to improve Drone detection and Tracking utilizing intersect of different algorithm, to combat the inherit challenges the field presents. I have been working with the iMaPLe team since Spring of 2022 helping to aggregate, test and present different research paper from computer vision conferences. Additionally, working on YOLOv4 to test out different datasets and hyper tune it to work better in highly noise-based data.
I am currently in my senior year of a Bachelors in Computer Engineering in the Department of Electrical and Computer Engineering at Drexel University. My interests in machine learning gravitate towards reinforcement learning with a focus on evolutionary artificial neural networks. Throughout my research with iMaPLe, I hope to learn various machine learning techniques and gain research experience for future post-graduate research.
Quoc Thinh Vo
B.Sc./ M.Sc. Student
I am currently a B.S./ M.S. student, majoring in Computer Engineering at Drexel University. I am interested in Deep Learning, Machine Learning, Mathematical Computing and Modeling, Theoretical Computer Science, and Computational Complexity Analysis. My interests in machine learning gravitate toward feature engineering, image processing at scale algorithms, and convolutional neural networks. At iMaPLe, I do research on the acoustic scene classifications; specifically, acoustic classification and detection in underwater scenarios, working towards my master’s thesis in the field under the supervision of Dr. Han.
B.Sc./ M.Sc. Student
I’m a rising senior in Computer Engineering. In the past, I have worked on EEG signal classification and processing. I also worked on a semi-autonomous wheelchair for ALS patient with Temple research group. As a prospective engineer, I want to use my work for good. At iMAPLE, I hope to use my knowledge in Machine Learning and computer for acoustic scene understanding. In my free time, I like to play sports and cook. My goal for this year is to make rice wine from scratch and improve my tennis.
Junior High School Student
I am currently a rising junior in the West Windsor-Plainsboro school district. I am interested to learn how engineering and machine learning apply to real world settings. Through my research with iMaple, I hope to gain new skills and apply research concepts to advance the field of robotic engineering.