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lex fridman skip to content lex fridman research scientist at mit host of lex fridman podcast menu lex fridman menu menu lex fridman podcast contact lex x twitter youtube lex fridman podcast research lectures research interests human ai interaction robotics and machine learning podcast interests history philosophy physics biology chemistry engineering ai robotics programming music film art sports psychology neuroscience geopolitics business economics religion and astronomy beyond the above i also enjoy playing guitar piano link is a video of me playing comfortably numb by pink floyd training competing in jiu jitsu judo link is a video of me receiving my jiu jitsu black belt contact me to contact me please check out the contact page connect x youtube linkedin instagram tiktok facebook reddit telegram research publications google scholar mit advanced vehicle technology study large scale naturalistic study of human interaction with automation website paper cite bibtex scholar summary large scale real world ai assisted driving data collection study to understand how human ai interaction in driving can be safe and enjoyable the emphasis is on computer vision based analysis of driver behavior in the context of automation use active authentication on mobile devices paper cite bibtex scholar summary an approach for verifying the identity of a smartphone user with with four biometric modalities we evaluate the approach by collecting real world behavioral biometrics data from smartphones of 200 subjects over a period of at least 30 days arguing machines human supervision of black box ai systems that make life critical decisions paper cite bibtex scholar summary framework for providing human supervision of a black box ai system that makes life critical decisions we demonstrate this approach on two applications 1 image classification and 2 real world data of ai assisted steering in tesla vehicles deeptraffic reinforcement learning system for multi agent dense traffic navigation paper cite bibtex scholar summary traffic simulation and optimization with deep reinforcement learning primary goal is to make the hands on study of deep rl accessible to thousands of students educators and researchers cognitive load estimation in the wild paper cite bibtex scholar summary winner of the chi 2018 honorable mention award we propose two novel vision based methods for cognitive load estimation and evaluate them on a large scale dataset collected under real world driving conditions what can be predicted from 6 seconds of driver glances paper cite bibtex scholar summary winner of the chi 2017 best paper award we consider a dataset of real world on road driving to explore the predictive power of driver glances clera a unified model for joint cognitive load and eye region analysis in the wild paper cite bibtex scholar summary unification of cognitive load estimation and eye region analysis landmark pupil blink detection in a single deep learning framework using shared feature extraction with task specific heads introduces localized feature tracking to model cognitive load from tracked eye region features over time and mask localized regressor for sub pixel precise keypoint detection achieving 66 58 accuracy on real world driving cognitive load classification while running at 38 fps with joint eye analysis learning human identity from motion patterns paper cite bibtex scholar summary dense clockwork rnns learn shift invariant representations from smartphone imu data for passive biometric authentication fixing temporal aliasing in cwrnns while modeling multi scale kinematics achieves 20 eer on 1500 user dataset of natural prehensile movements captured in the wild driver gaze region estimation without use of eye movement paper cite bibtex scholar summary we propose a simplification of the general gaze estimation task by framing it as a gaze region estimation task in the driving context thereby making it amenable to machine learning approaches we go on to describe and evaluate one such learning based approach a fast foveated fully convolutional network model for human peripheral vision paper cite bibtex scholar summary generative neural network is trained to simulate human peripheral vision degradation 21 000x faster than existing behaviorally validated texture synthesis models 4 2 hours 0 7 seconds per image enabling real time visualization of what observers see when fixating different locations the network learns to replicate crowding and acuity loss effects from the texture tiling model while preserving statistical accuracy for hci design applications semi automated annotation of discrete states in large video datasets paper cite bibtex scholar summary semi automated video annotation framework reduces per frame labeling to detecting state transitions modeled with a hidden markov model on 16m driver gaze frames it cuts manual work by up to 84 while maintaining 91 99 accuracy driver frustration detection from audio and video in the wild paper cite bibtex scholar summary a method for detecting driver frustration from both video and audio streams captured during the driver s interaction with an in vehicle voice based navigation system an interesting observation smiles are more common in unsatisfied vs satisfied interactions owl and lizard patterns of head pose and eye pose in driver gaze classification paper cite bibtex scholar summary monocular driver gaze classification achieves 94 6 accuracy using head eye pose vs 89 2 with head pose alone on 6 region classification owlness metric dh dh dp reveals users with eye dominant gaze strategies benefit most from pupil detection while head movers show minimal improvement crowdsourced assessment of external vehicle to pedestrian displays paper cite bibtex scholar summary 30 external vehicle to pedestrian display concepts for autonomous vehicles were evaluated simple minimalist displays performed best automated synchronization of driving data using vibration and steering events paper cite bibtex scholar summary a method for automated synchronization of vehicle sensors using accelerometer telemetry audio and dense optical flow from three video sensors decision fusion for multimodal active authentication paper cite bibtex summary continuous authentication via behavioral biometrics fuses 10 svm based sensors mouse dynamics keystroke timing stylometry with varying window sizes domain visit patterns using chair varshney optimal decision rule on 19 user office dataset achieves far 0 00122 frr 0 00218 with stylometry contributing more error reduction than web browsing patterns in the multimodal fusion multi modal decision fusion for continuous authentication paper cite bibtex summary decision fusion of 12 behavioral biometric sensors keystroke dynamics mouse movement stylometry for continuous authentication system is be robust to partial spoofing observations on sum user rate for cellular downlink paper cite bibtex summary cellular downlink performance is analyzed using an expected spatial capacity metric based on sinr driven user association results show counter intuitive effects clustered transmitter placement and shared channel use can yield higher sum rates than evenly spaced deployments or slot scheduling communication based motion planning paper cite bibtex summary mobile agents navigating obstacle laden terrain optimize movement timing along predetermined paths to minimize network disconnections formulated as minimizing average strongly connected components cooperative uniform cost search achieves optimality at o βn² 2 nt_max while distributed noncooperative planning scales to o cβn³ 2 t_max achieving near optimal 80 128 connectivity improvements distributed path planning for connectivity under uncertainty by ant colony optimization paper cite bibtex summary distributed path planning via ant colony optimization minimizes time averaged connected components under incomplete knowledge of jamming zones using pheromone tables updated by utility functions combining distance to goal nearest neighbor and learned no comm zone probability estimates robust optimal power control for ad hoc networks paper cite bibtex summary robust power control for ad hoc networks minimizes total transmit power while penalizing expected sinr violations under uncertain channels fading shadowing noise achieves better feasibility optimality tradeoff than deterministic methods using outdated channel state information oman a mobile ad hoc network design system paper cite bibtex summary oman integrates cross layer resource allocation for mobile ad hoc networks into a unified optimization framework solving power control under channel uncertainty scheduling with directional antennas and relay node movement planning simultaneously the system provides both api and gui interfaces for jointly optimizing network resources across phy mac and mobility layers rather than treating each layer s optimization problems in isolation cross layer multicommodity capacity expansion on ad hoc wireless networks of cognitive radios paper cite bibtex summary joint optimization of power constellation size scheduling and flow across phy mac net layers in cognitive radio networks achieves higher throughput than modular layer by layer design cross layer resource allocation yields 20 140 performance gains over conventional layered approaches on the joint impact of bias and power control on downlink spectral efficiency in cellular networks paper cite bibtex summary cell biasing and downlink power control are jointly optimized to improve cellular network spectral efficiency joint control shows significant improvements in mean variance and throughput fairness tradeoffs over using either control alone path planning for network performance paper cite bibtex summary decentralized a search computes pareto optimal paths for manet nodes balancing minimum time navigation against six network performance metrics connected components link density multicommodity flow achieving up to 5x performance improvement with zero travel time penalty nodes incorporate real time network feedback to dynamically adjust trajectories enabling significant connectivity gains in sparse networks where traditional formation control fails proudly powered by wordpress