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GeneExpert
A foundation model for bulk RNA-Seq gene expression data. More to come once it's published.
Featured in UBC's “Meet our Students” Series
Excited to be highlighted in the UBC Graduate School's Meet our Students series.
Why I Stopped Expecting a Big Crash?
On a log scale, the S&P 500 looks a lot more linear than the headlines suggest. Here's what that tells me, and what it doesn't.
Start with Why
Start with Why: How Great Leaders Inspire Everyone to Take Action — Simon Sinek
Why getting the purpose right from the start matters more than any amount of data, motivation or competition.
Ikigai
Ikigai: The Japanese Secret to a Long and Happy Life — Héctor García and Francesc Miralles
What the longest-living people can teach us about purpose, flow, and doing one thing at a time.
A Vancouver AI Community I've Been Learning From
If you're curious about AI and want to meet others who are too, VAM! might be worth checking out.
Learning Finance with MIT's Finance Theory I
I'm halfway through MIT's free Finance Theory I course and loving it. Here's why you should watch it too.
Notes on Being a Man
Notes on Being a Man — Scott Galloway
Less a manual for me than a window into Scott Galloway and how he sees life.
Greenlights
Greenlights — Matthew McConaughey
Matthew McConaughey's memoir about life's red lights, yellow lights and greenlights.
Friends, Lovers, and the Big Terrible Thing
Friends, Lovers, and the Big Terrible Thing: A Memoir — Matthew Perry
Matthew Perry's candid memoir about fame, Friends, and his long struggle with addiction.
Atomic Habits
Atomic Habits: An Easy & Proven Way to Build Good Habits & Break Bad Ones — James Clear
Not much new if you've read others on the subject, but if this is your first book on habits, it's a must-read.
Born a Crime
Born a Crime: Stories from a South African Childhood — Trevor Noah
One of the first biographies I read, full of Trevor Noah's childhood stories.
The Psychology of Money
The Psychology of Money — Morgan Housel
A book I really enjoyed reading and learned a lot from.
Goal-Oriented Autonomous Driving with Large Language Models
Bringing LLMs into an end-to-end driving pipeline to give it a goal and focus its attention on what matters in the scene.
Depth Estimation with Online Calibration for Autonomous Driving
Monocular and stereo depth estimation, with camera calibration and absolute scale recovered on the fly.
Urban Driving with a Model-Based Reinforcement Learning Agent
A Dreamer-inspired agent that learns to drive in a simulator and keeps adapting to the driver for a more comfortable ride.
Prediction and Planning for Robotics and Autonomous Driving
A comprehensive study of end-to-end and modular autonomous driving pipelines.
Multi-Pedestrian Trajectory Prediction from the Ego Vehicle
Predicting where pedestrians will go, modelling both individual and social behaviour.
Efficient 2D Object Detection for Production Line Inspection
A family of fast RetinaNet-style detectors for industrial inspection, extended to reading text.
I am a machine learning researcher whose work spans machine vision, autonomous driving, and computational biology. My background combines academic research with industry experience, and I work at the intersection of these fields, which are becoming more closely connected every day.
My path in computer science began in 2010, when I enrolled in the Software Engineering program at Isfahan University in Iran. After graduating in 2014, I moved to Canada to pursue a master’s degree in computer science at Concordia University. There, I worked with Dr. Sudhir P. Mudur and Dr. Charalambos Poullis in the Immersive and Creative Technologies Lab, where I deepened my expertise in computer vision.
After my master’s, I joined Matrox Electronic Systems as a software designer, at a time when deep learning was first moving from research into industry. Over four years, I applied it to real machine vision problems, from segmentation to inspection, and led a team in prototyping machine learning solutions for use in the field. In 2021, I moved to Vancouver to join Huawei Technologies, where I worked on autonomous driving across perception, prediction, and planning.
Over time, I became interested in biology and how AI could help us better understand biological systems and human health. In 2024, I returned to academia to pursue a PhD in Bioinformatics at the University of British Columbia, under the supervision of Dr. Ali Bashashati at the AIMLab. My research brings my machine learning background to questions in human biology, starting with foundation models for gene expression data.
My journey is still unfolding, and I try to keep this website up to date as it does. Thanks for stopping by!
Behnam Maneshgar
Vancouver, BC, Canada
behnam@maneshgar.com
PhD in Bioinformatics
Master’s in Computer Science
B.Eng. in Software Engineering
University of British Columbia · AIMLab
Research in bioinformatics under the supervision of Dr. Ali Bashashati.
Huawei Technologies Canada
Applied research in perception and planning algorithms for autonomous vehicles.
Matrox Electronic Systems
Research and development of deep learning solutions for the machine vision industry.
Concordia University · ICT Lab
Master’s thesis at the Immersive and Creative Technologies (ICT) Lab.
Concordia University
University of Isfahan · Software Security Lab
Bachelor internship at the Software Security Lab.
AIMLab, University of British Columbia
Huawei Technologies Canada
Huawei Technologies Canada
Elastic 3D Space is an international research project, based at Concordia University in Montréal, exploring stereoscopy, 3D video and encompassing virtual and augmented reality. Growing over the last two years, with projects in the UK and Australia, Elastic 3D Space explores the potential future for stereoscopy (the technology behind VR and 3D cinema) through projected and electronic screen based methods.
3D Space, Stereoscopy
Computer graphics research and teaching at Concordia University, where I worked as a teaching assistant for the Computer Graphics and Computer Vision courses.
Computer Graphics, Concordia University
Leading developer of component-level solutions for machine vision, image analysis, medical imaging, and video surveillance.
Imaging
Our vision and mission is to bring digital to every person, home and organization for a fully connected, intelligent world.
Artificial Intelligence
The Artificial Intelligence in Medicine Lab at the University of British Columbia works at the interface of computation, engineering and medicine. I am a PhD student in the lab, supervised by Dr. Ali Bashashati.
AI in Medicine, Computational Pathology
The Immersive and Creative Technologies Lab was founded in late 2011 and since its establishment it has been focusing on fundamental and applied research in specific areas of Computer Science. In particular researchers at the lab are focused in the areas of computer vision, computer graphics, virtual augmented reality and creative technologies, and their application in a wide range of fields.
Computer Vision, Computer Graphics
Sepehr Shimi is a Chemical based Company founded in 1982. Its principal products lies on Liquid Paraffin, Slack Wax and Polyvinyl Acetate.
Oil, Paraffin, ISO RecycleSend me a message below, or email behnam@maneshgar.com.