I am currently a PhD student working under the supervision of Dr. Margrit Betke and Dr. Stan Sclaroff with the Image and Video Computing research group at Boston University's Department of Computer Science. I attained a Master of Science degree in Computer Science from Boston University in 2014, and a Bachelor of Arts degree from Connecticut College in 2012 where I majored in Computer Science and Architectural Studies and completed a certificate program in Arts and Technology. I have had the opportunity to intern at Disney Research (Summer 2015) and Adobe Creative Technologies Lab (Summer 2016).
My broad research interests lie in computer vision, machine learning, and human computer interaction. Particularly, I am interested in the analysis of spatio-temporal human signals. In my spare time, I do freelance work in art and photography. Some of my work can be seen at ajjenjoshi.com.
DEEPTWEEN: A DATA-DRIVEN APPROACH TO AUTOMATIC INBETWEENING IN HANDDRAWN ANIMATION (current)
Ajjen Joshi, Linda Tickle-Degnen, Sarah Gunnery, Terry Ellis, Margrit Betke
PREDICTING ACTIVE FACIAL EXPRESSIVITY IN PEOPLE WITH PARKINSON'S DISEASE
International Conference on Pervasive Technologies Related to Assistive Environments (PETRA), 2016. Oral.
Ajjen Joshi, Camille Monnier, Margrit Betke, Stan Sclaroff
COMPARING RANDOM FOREST APPROACHES TO SEGMENTING AND CLASSIFYING GESTURES
Elsevier Image and Vision Computing (IMAVIS), 2016.
Ajjen Joshi, Bridget Baird, Ozgur Izmirli
DEVELOPING A TOOL FOR DANCE MOTION SYNTHESIS
Connecticut College Biennial Symposium on Arts and Technology, 2012. Oral.
Built a prototype of a gesture recognition system trained to recognize gestures performed by using a glove equipped with various sensors during my internship at Disney research.
#Python, scikit-learn, IMU data
Created projections for a rendition of the futurist opera: Victory Over the Sun. Wrote scripts creating generative animations and used the Kinect to record and animate dancers.
A prototype of a hands-free eye typing system (created by a 2-person team). Designed for people with motor impairments, users typed words using their eyegaze with a wearable eye-tracker.
#Python, scikit-learn, pupil-labs eyetracker, Video
A ray tracer with support for quadric surfaces (spheres, ellipsoids, cylinders, boxes), 5 directional light sources, lighting models with ambient, diffuse and specular terms, as well as effects caused by shadows, reflections and refractions.
An openCV app (created by a 2-person team) that allowed users to play an 8-key paper piano. Computer vision algorithms were user to detect keys, segment user hands and determine which keys were being pressed.
A web app written using the LAMP (Linux, Apache, MySQL, PHP) stack that allowed users to select food available in a student run kitchen and place an order for pickup or delivery.
"Ajjen was the best teaching fellow I have had at BU thus far. He is very knowledgeable in all things computer vision and was helpful when explaining topics." -CS585 student, Fall 2014
"Ajjen is extremely qualified for this position and he clearly demonstrated it by helping students outside of class with projects he is not familiar with. He is extremely helpful and definitely deserves a good recommendation." -CS108 student, Fall 2013