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<h3 class="profile-title">Boris Ivanovic</h3>
<p class="profile-description">Research Manager @ NVIDIA</p>
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<h4 class="widget-title">Experience</h4>
<ul>
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<h5><b><span class="blue-grey">June 2023 - Present</span></b></h5>
<h5 class="life-item-title"><b>Senior Research Scientist and Manager</b></h5>
<h5>NVIDIA Research - Santa Clara, CA - USA</h5>
<ul>
<li>Researching behavior modeling, simulation, and end-to-end autonomy in NVIDIA’s <a href="https://research.nvidia.com/labs/avg/" target="_blank">Autonomous Vehicle Research Group</a>.</li>
</ul>
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<h5><b><span class="blue-grey">January 2022 - June 2023</span></b></h5>
<h5 class="life-item-title"><b>Research Scientist</b></h5>
<h5>NVIDIA Research - Santa Clara, CA - USA</h5>
<ul>
<li>Developed novel agent behavior models for use in autonomy stacks and simulation in NVIDIA's <a href="https://research.nvidia.com/labs/avg/" target="_blank">Autonomous Vehicle Research Group</a>.</li>
</ul>
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<h5><b><span class="blue-grey">March 2021 - September 2021</span></b></h5>
<h5 class="life-item-title"><b>Research Scientist Intern</b></h5>
<h5>NVIDIA Research - Santa Clara, CA - USA</h5>
<ul>
<li>Worked in the <a href="https://nvr-avg.github.io/" target="_blank">Autonomous Vehicle Research Group</a> on novel trajectory forecasting methods and their integration within the autonomy stack.</li>
</ul>
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</li>
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<img src="img/tri.jpg">
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<h5><b><span class="blue-grey">June 2020 - September 2020</span></b></h5>
<h5 class="life-item-title"><b>Research Scientist Intern</b></h5>
<h5>Toyota Research Institute - Los Altos, CA - USA</h5>
<ul>
<li>Worked with the Head of Machine Learning Research, <a href="https://scholar.google.fr/citations?user=2StUgf4AAAAJ&hl=en" target="_blank">Adrien Gaidon</a>, on novel trajectory forecasting methods.</li>
</ul>
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<img src="img/amzn.png">
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<h5><b><span class="blue-grey">June 2017 - September 2017</span></b></h5>
<h5 class="life-item-title"><b>Prime Air SDE Intern</b></h5>
<h5>Amazon.com - Seattle, WA - USA</h5>
<ul>
<li>Worked with Principal Research Scientist <a class="amazon-orange-underline" href="https://scholar.google.com/citations?user=fBQkrXEAAAAJ&hl=en" target="_blank">Ishay Kamon</a> in the Autonomy team.</li>
<li>Designed and implemented a novel state-of-the-art deep learning approach for a specific computer vision task within the team, outperforming existing models by 10x.</li>
<li>The project was completed successfully and a full-time Research Scientist return offer was extended.</li>
</ul>
</div>
</div>
</li>
<div class="li-separator"></div>
<li>
<div class="life-item">
<div class="life-item-img">
<img src="img/stanford.png">
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<div class="life-item-content">
<h5><b><span class="blue-grey">April 2017 - June 2017</span></b></h5>
<h5 class="life-item-title"><b>CS231A Course Assistant</b></h5>
<h5>Stanford University - Stanford, CA - USA</h5>
<ul>
<li>Assisted with many aspects of running <a href="http://web.stanford.edu/class/cs231a/" target="_blank">CS231A: Computer Vision From 3D Reconstruction to Recognition</a>, taught by Professor <a href="http://cvgl.stanford.edu/silvio/" target="_blank">Silvio Savarese</a>.</li>
</ul>
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</li>
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<h5><b><span class="blue-grey">January 2017 - June 2017</span></b></h5>
<h5 class="life-item-title"><b>Independent Research Project</b></h5>
<h5>Stanford University - Stanford, CA - USA</h5>
<ul>
<li>Worked in the <a href="http://cvgl.stanford.edu/" target="_blank">Computer Vision and Geometry Lab (CVGL)</a> and <a href="http://asl.stanford.edu/" target="_blank">Autonomous Systems Lab (ASL)</a> with Professors <a href="http://cvgl.stanford.edu/silvio/" target="_blank">Silvio Savarese</a> and <a href="http://web.stanford.edu/~pavone/" target="_blank">Marco Pavone</a> on making reinforcement learning more robust with control theory.</li>
<li>Tackled the problem of policy transfer in reinforcement learning, applying model-predictive control to provide safety guarantees when transferring a learned policy from one environment to another with different dynamics.</li>
<li>Our work was accepted to the International Symposium on Robotics Research (ISRR) 2017, held in Puerto Varas, Chile.</li>
</ul>
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<h5><b><span class="blue-grey">September 2016 - June 2017</span></b></h5>
<h5 class="life-item-title"><b>Research Assistant</b></h5>
<h5>Stanford University - Stanford, CA - USA</h5>
<ul>
<li>Worked in the <a href="http://snap.stanford.edu/" target="_blank">Stanford Network Analysis Project (SNAP) Lab</a> with Professor <a href="https://cs.stanford.edu/people/jure/" target="_blank">Jure Leskovec</a> on analyzing large-scale physical activity data with modern data science methods.</li>
<li>Efficiently cleaned, preprocessed, and distilled 3 TB of user physical activity data from over 2 million users of a mobile fitness app. Obtained scientific results with data visualization, statistical analyses (such as regressions and confidence metrics), and computational methods (including hierarchical bootstrapping).</li>
<li>Showed significant results relating a location’s walkability, weather, and climate to an individual’s physical activity. This work has very wide implications, as physical inactivity is a major global pandemic responsible for over 5 million deaths per year.</li>
</ul>
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<h5><b><span class="blue-grey">September 2016 - December 2016</span></b></h5>
<h5 class="life-item-title"><b>Independent Research Project</b></h5>
<h5>Stanford University - Stanford, CA - USA</h5>
<ul>
<li>Worked with Professor <a href="http://www.andrewng.org/" target="_blank">Andrew Ng</a> on neural language correction, a method of correcting grammar and spelling mistakes using deep sequence models.</li>
<li>Augmented state-of-the-art deep neural language models with subword units and experimentally verified resulting model performance.</li>
</ul>
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<h5><b><span class="blue-grey">May 2016 - August 2016</span></b></h5>
<h5 class="life-item-title"><b>Prime Air SDE Intern</b></h5>
<h5>Amazon.com - Seattle, WA - USA</h5>
<ul>
<li>Worked with former NASA Astronaut <a class="amazon-orange-underline" href="http://www.jsc.nasa.gov/Bios/htmlbios/woodward.html" target="_blank">Neil Woodward</a> in the Flight Test team.</li>
<li>Designed and built fault-tolerant, scalable software and hardware to autonomously collect and process relevant flight test data from numerous locations for internal consumption.</li>
<li>The project was completed successfully and a return offer was extended.</li>
</ul>
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<h5><b><span class="blue-grey">January 2016 - May 2016</span></b></h5>
<h5 class="life-item-title"><b>CSC411 Teaching Assistant</b></h5>
<h5>University of Toronto - Toronto, ON - Canada</h5>
<ul>
<li>Award-winning TA for the popular <a class="uoft-blue-underline" href="http://www.cs.utoronto.ca/~fidler/teaching/2015/CSC411.html" target="_blank">CSC411: Introduction to Machine Learning</a> course, taught by Professor <a class="uoft-blue-underline" href="http://www.cs.utoronto.ca/~fidler/" target="_blank">Sanja Fidler</a>.</li>
</ul>
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<h5><b><span class="blue-grey">September 2015 - May 2016</span></b></h5>
<h5 class="life-item-title"><b>Undergraduate Thesis</b></h5>
<h5>University of Toronto - Toronto, ON - Canada</h5>
<p>Worked with Professors <a class="uoft-blue-underline" href="http://www.cs.toronto.edu/~urtasun/" target="_blank">Raquel Urtasun</a> and <a class="uoft-blue-underline" href="http://www.cs.utoronto.ca/~fidler/" target="_blank">Sanja Fidler</a> to:</p>
<p><i>Create a semantically labelled 3D map of an outdoor environment from video recorded by a quadrocopter and augment that map with cartographic data (ie. from OpenStreetMap).</i></p>
<p>More specifically, the goals of the project were:
<ul>
<li>Fly a quadcopter around an outdoor environment and, from video recorded during the flight, create a 3D reconstruction of the environment. The LSD-SLAM algorithm was used for this since the cameras available to us were monocular.</li>
<li>Design and implement a data annotation framework to support and automate the labeling of collected data.</li>
<li>Label objects within the 3D representation of the environment, such as people, trees, buildings, etc... For this I formulated a CRF, incorporating cartographic data.</li>
</ul></p>
<p>Project results and reports can be viewed at <a class="uoft-blue-underline" href="https://drive.google.com/open?id=0B07dwt_Fgi11ZFNtYmhxWHBiQTA" target="_blank">this Google Drive link.</a></p>
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<h5><b><span class="blue-grey">May 2015 - August 2015</span></b></h5>
<h5 class="life-item-title"><b>Summer Research Intern</b></h5>
<h5>ETH Zurich - Zurich - Switzerland</h5>
<ul>
<li>Worked with Professor <a class="eth-blue-underline" href="http://raffaello.name/" target="_blank">Raffaello D’Andrea</a> in the <a class="eth-blue-underline" href="http://www.idsc.ethz.ch/" target="_blank">Institute for Dynamic Systems and Control</a>, specifically the <a class="eth-blue-underline" href="http://flyingmachinearena.org/" target="_blank">Flying Machine Arena</a>.</li>
<li>Removed superfluous code from an open source motor controller and implemented new features such as motor calibration, emergency safety states, and a better motor startup routine in C.</li>
<li>Simulated dynamic motor and propeller system responses in Python.</li>
<li>Technology used: STM32 C Code, Motor Controller PCB Chips, Quadrotor Flying Vehicles.</li>
</ul>
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<h5><b><span class="blue-grey">May 2014 - July 2014</span></b></h5>
<h5 class="life-item-title"><b>SDE Intern</b></h5>
<h5>Amazon.com - Seattle, WA - USA</h5>
<ul>
<li>Worked in the Demand Forecasting team creating a real-time simulation tool. The project was completed successfully and a return offer was extended.</li>
<li>Worked with Big Data, using the Hadoop framework (MapReduce, HDFS, etc.) to process large amounts of simulation data generated by a machine learning module.</li>
<li>Created a web service with Spring, designed and implemented a website UI with GWT, and used the AWS SDK to store and retrieve data from S3.</li>
<li>Gave a presentation to 100+ Amazon employees regarding my project and its design, implementation, and performance.</li>
<li>Concepts employed: Big Data, Highly Scalable Distributed Systems, and Data Mining.</li>
</ul>
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<h5><b><span class="blue-grey">May 2013 - August 2013</span></b></h5>
<h5 class="life-item-title"><b>Agile Engineer Co-op</b></h5>
<h5>Xtreme Labs (now Pivotal) - Toronto, ON - Canada</h5>
<ul>
<li>Learned Agile development methodologies and applied them to real-world projects.</li>
<li>Provided input on and developed an app that has 1,000,000+ installs.</li>
<li>Technology used: Android SDK for apps and HTML/CSS3/PHP for website development.</li>
</ul>
</div>
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</li>
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