andrey pak
Graduate Teaching Assistant at Georgia Institute of Technology
graduate research assistant
third year robotics phd student georgia institute technology multidisciplinary background computer science , robotics aerospace engineering currently looking forward research internship opportunity field . research experience include multi-target detection tracking using classical approach well deep convolutional neural network . hobby photography , hiking aviation .
Georgia Institute of Technology
https://www.linkedin.com/company/georgia-institute-of-technology
Teaching Assistant for senior Dynamics and Control lab (AE4610). Teaching assistant responsibilities include conducting lectures, supervising laboratory classes and grading reports.

Research on latent state estimation for autonomous driving.

Parallel research is focused on multiple object detection and tracking for LIDAR data using deep convolutional neural networks.

2nd place in ArgoAI Argoverse 3D Tracking Competition - results presented at CVPR2020 Autonomous Driving Workshop.
Greater Atlanta Area
https://media-exp1.licdn.com/dms/image/C4E0BAQFuhLQoh5_7yA/company-logo_100_100/0/1640110531895?e=1655942400&v=beta&t=t6hv3VkTbxBHi3miWHi47DnWfnM2XkyFZLiRy8WZdnI
Graduate Teaching Assistant
Georgia Institute of Technology
https://www.linkedin.com/company/georgia-institute-of-technology
Research focused on observability, detection and tracking of orbiting objects via Doppler observables. Additional responsibilities include operation, maintenance, calibration and backbone database development for Georgia Tech Space Object Research Telescope (GT-SORT). As a side opportunity, created the official LaTeX template for Advanced Maui Optical and Space Surveillance (AMOS) Conference.
Greater Atlanta Area
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Graduate Research Assistant
Scale AI
https://www.linkedin.com/company/scaleai
San Francisco, California, United States
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Machine Learning Research Engineer Intern
Google Summer of Code
https://www.linkedin.com/company/google-summer-of-code-2019
Google Summer of Code 2020 project: "Doppler-based Orbit Determination Using Network of Low-Cost Ground Stations". Proposed and implemented an initial orbit determination algorithm for state estimation by fusing Doppler measurements from multiple stations.
Atlanta, Georgia, United States
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Participant
Universidad de Chile
https://www.linkedin.com/company/uchile
Research project on Space Object Detection and Tracking within a Finite Set Statistics Framework. 

Analyzed the performance of several multi-target tracking filters for Chilbolton Advanced Meteorological Radar (CAMRa). Designed Beta-Gaussian Mixture Joint Target Detection and Tracking (JoTT) filter, robust JoTT filter (team member), enabling online real-time estimation of unknown clutter parameters and target's detection statistics.

Southern Office of Aerospace Research and Development, Grant No. FA9550-15-1-0069.
Santiago, Chile
https://media-exp1.licdn.com/dms/image/C4E0BAQHLMd1B2RlLsA/company-logo_100_100/0/1637328412537?e=1655942400&v=beta&t=BVdARQnshHxL-Xl6pV8XakSieTtN7Pj7jUFp5t4ytRY
Research Assistant
Heriot-Watt University
https://www.linkedin.com/company/heriot-watt-university
Futher work on thesis project. Improved CAMRa measurement processing routine.
Edinburgh, United Kingdom
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Post-graduate Intern
PhD
Current research is focused on multiple object detection and tracking for LIDAR data using deep convolutional neural networks - implementing and evaluating the Uber’s ATG Fast and Furious paper on detection, tracking and motion forecasting using DCNN. The objective is to evaluate the proposed system using several open LIDAR datasets as well as to compare end-to-end DCNN detection and tracking vs. network-based detection combined conventional tracking algorithms.

Deep Learning class project devoted to snake species identification.
Robotics
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Georgia Institute of Technology
https://www.linkedin.com/school/georgia-institute-of-technology/
Master of Science - MS
Master's degree in Aerospace Engineering with Minor in Math earned alongside PhD track.

Studies included orbital mechanics, satellite orbit determination, optimization and linear control. Final project in optimization class was focused on optimizing satellite constellation coverage using genetic algorithms.
Aerospace Engineering
https://media-exp1.licdn.com/dms/image/C4E0BAQFuhLQoh5_7yA/company-logo_100_100/0/1640110531895?e=1655942400&v=beta&t=t6hv3VkTbxBHi3miWHi47DnWfnM2XkyFZLiRy8WZdnI
Georgia Institute of Technology
https://www.linkedin.com/school/georgia-institute-of-technology/
Master of Science (MSc)
Third and fourth semester of the Erasmus Mundus Master Course in Computer Vision and Robotics.

The highlights of the third semester included multi-target tracking and information fusion, advanced image processing as well as group robotics project.

MSc. Thesis: "Space Debris Tracking" - Chilbolton Advanced Meteorological Radar data processing for the orbital object state estimation within the Random Finite Sets framework. Supervisor: Dr. Daniel Clark.

Best Master Thesis Award.
Computer Vision and Robotics
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Heriot-Watt University
https://www.linkedin.com/school/heriot-watt-university/
Master of Science (MSc)
Second semester of the Erasmus Mundus Master Course in Computer Vision and Robotics. 

The curriculum covered fundamental approaches to robot autonomy and navigation, introduced concepts of SLAM and Bayesian filtering. Other courses included scene segmentation and advanced image analysis. Considerable amount of hands-on lab experience.
Computer Vision and Robotics
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Universitat de Girona
https://www.linkedin.com/school/universitat-de-girona/
Master of Science (MS)
First semester of the Erasmus Mundus Master Course in Computer Vision and Robotics (VIBOT). 

Introductory courses covered basic concepts of image and signal processing, sensors as well as medical imaging. Practical lab work was mainly focused on industrial image processing, 3D-scanning and reconstruction.
Computer Vision
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Université de Bourgogne
https://www.linkedin.com/school/universit%C3%A9-de-bourgogne/
Bachelor of Science (B.Sc.)
Participation in the preparation for the ABU Asia-Pacific Robot Contest 2013. Member of the IITU robotics laboratory.
Computer Science and Software Engineering
International Information Technologies University
iCarnegie Global Scholars Program
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Carnegie Mellon University
https://www.linkedin.com/school/carnegie-mellon-university/
An increased concern in space situational awareness has resulted from the rise in space debris and its threat to future space missions. For safety reasons, it is critically important to populate and maintain a catalog of orbiting objects. To detect and track space debris, telescopes and radars are typically used, resulting in multiple point measurements, which have to be processed in order to discriminate detections from clutter. Such processes are often based on Bayesian filtering. Conventional filters, such as the Kalman filter, cannot be directly applied to cluttered data problems because a multitarget estimate is required and/or multiple measurements are received. The recently introduced random finite set theory provides an elegant framework within which such problems can be naturally expressed and solved. This paper presents the application of several variations of the random finite-set-based joint target detection and tracking filter, which is a single-target multiple measurement-based filter, for processing radar measurements. Robust versions of this filter are presented to further account for unknown and possible time-varying detection statistics. The presented filters have the capability of differentiating a target from clutter measurements within real datasets as well estimating target probabilities of detection and radar clutter rates.
Robust Joint Target Detection and Tracking for Space Situational Awareness
American Institute of Aeronautics and Astronautics
https://arc.aiaa.org/doi/abs/10.2514/1.G002231
Recently, the growing number of inactive Resident Space Objects (RSOs), or space debris, has provoked increased interest in the field of Space Situational Awareness (SSA) and various investigations of new methods for orbital object tracking. In comparison with conventional tracking scenarios, state estimation of an orbiting object entails additional challenges, such as orbit determination and orbital state and covariance propagation in the presence of highly non-linear system dynamics. The sensors which are available for detecting and tracking space debris are prone to multiple clutter measurements. Added to this problem, is the fact that it is unknown whether or not a space debris type target is present within such sensor measurements. Under these circumstances, traditional single-target filtering solutions such as Kalman Filters fail to produce useful trajectory estimates.  The recent Random Finite Set (RFS) based Finite Set Statistical (FISST) framework has yielded filters which are more appropriate for such situations. The RFS based Joint Target Detection and Tracking (JoTT) filter, also known as the Bernoulli filter, is a single target, multiple measurements filter  capable  of  dealing  with  cluttered  and  time-varying  backgrounds  as  well  as  modeling  target  appearance  and disappearance in the scene.  Therefore, this paper presents the application of the Gaussian mixture-based JoTT filter for processing measurements from Chilbolton Advanced Meteorological Radar (CAMRa) which contain both defunct and operational satellites.  The CAMRa is a fully-steerable radar located in southern England, which was recently modified to be used as a tracking asset in the European Space Agency SSA program.  The experiments conducted show promising results regarding the capability of such filters in processing cluttered radar data.
Joint Target Detection and Tracking Filter for Chilbolton Advanced Meteorological Radar Data Processing
Advanced Maui Optical and Space Surveillance Technologies Conference
https://amostech.com/TechnicalPapers/2016/Astrodynamics/Pak.pdf
Second place in Argoverse 3D Tracking Competition:
https://evalai.cloudcv.org/web/challenges/challenge-page/453/leaderboard/1278
ArgoAI
ArgoAI Argoverse 3D Tracking Competition - 2nd place
Alliance Française Niveau B 1.3
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Autonomous Navigation for Flying Robots @ edx.org
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Machine Learning Online Course at Stanford University (https://www.coursera.org/course/ml)
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Final undergraduate project. Designed, manufactured parts and assembled a small unmanned ground vehicle. Design and drawings were completed in Autodesk Inventor, parts were manufactured in a machine shop, which included milling, water jet cutting and frame welding, Raspberry Pi/ODroid were used as an on-board computer.
Design and implementation of small unmanned ground vehicle.
Final project for AE6310 Optimization for the Design of Engineered Systems course (group). Used genetic algorithm to find optimal satellite constellation configuration given project constraints (project budget, orbit altitude, number of satellites).
Optimization of an Earth Satellite Constellation
Coursera Course Certificates
www.coursera.org
Y8WQJRU98AHR
Photography Basics and Beyond: From Smartphone to DSLR Specialization
https://www.coursera.org/account/accomplishments/specialization/Y8WQJRU98AHR
edX
s3.amazonaws.com
edX Verified Certificate for Autonomous Navigation for Flying Robots
https://s3.amazonaws.com/verify.edx.org/downloads/301df7d885d84a30afc630e10e49eb05/Certificate.pdf
https://www.linkedin.com/in/diwakar-gatech
San Francisco, CA
Diwakar Singh
Machine Learning Research Engineer at Scale AI | Georgia Tech | IIT Delhi
https://www.linkedin.com/in/sidharth-potdar
Atlanta Metropolitan Area
Sidharth Potdar
Product Operations Manager at Scale AI
https://www.linkedin.com/in/adaiba-nwasike-b46189200
Atlanta, GA
Adaiba Nwasike
Stamps President’s Scholar at Georgia Institute of Technology
https://au.linkedin.com/in/andy-iea-625a5b1a4
Springvale, VI
Andy Iea
Student at Edith Cowan University
https://www.linkedin.com/in/del14
San Mateo, CA
Dennis Lynch
Senior Software Engineer at Snowflake
https://www.linkedin.com/in/nancytrinh
San Francisco Bay Area
Nancy Trinh
Software Engineer at Snowflake
https://au.linkedin.com/in/andy--nguyen
Greater Melbourne Area
Andy Nguyen
ETL Analyst at Origin Energy
https://au.linkedin.com/in/darren-lim-0a9819171
Greater Melbourne Area
Darren Lim
Tennis Coach at Vida Tennis
https://au.linkedin.com/in/richard-ly-06ba49183
Greater Melbourne Area
Richard Ly
Graduate of Bachelor of Sport Science (Exercise Science) Student at Victoria University (VU).
https://www.linkedin.com/in/kevindnaughtonjr
New York City Metropolitan Area
Kevin Naughton
Software Engineer at Google
https://www.linkedin.com/in/saleh-hamadeh-2a28b662
San Francisco, CA
Saleh Hamadeh
Software Engineer at Scale AI
https://au.linkedin.com/in/adeeshadesilva
Melbourne, VI
Adeesha de Silva
Senior Business Intelligence Developer
https://au.linkedin.com/in/lisa-cao-168216123
Burwood East, VI
Lisa Cao
Business Analyst/UX Designer at Telstra
https://au.linkedin.com/in/tin-ta-b035b311a
Greater Melbourne Area
Tin Ta
--
https://www.linkedin.com/in/jkochevar
Greater Seattle Area
Joe Kochevar
Manager of Mechanical Engineering at Spaceflight Inc.
https://www.linkedin.com/in/sharvil-shah-a319187b
Greater Orlando
Sharvil Shah
Research Assistant at University of Central Florida
https://www.linkedin.com/in/parul-pandey
Portland, Oregon Metropolitan Area
Parul Pandey
Machine Learning Engineer at Intel Corporation
https://www.linkedin.com/in/yixinglao
Santa Clara, CA
Yixing Lao
Research Engineer at Intel Labs
https://www.linkedin.com/in/pulkital
San Francisco Bay Area
Pulkit Agrawal
Senior Machine Learning Engineer at Apple
Liked by Andrey Pak
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🔴 We're LIVE with Transform! 🔴🎟 Link in the comments for a chance for last-minute ticket! 🎟#transform21
Liked by Andrey Pak
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Process of going from World to Camera framehttps://lnkd.in/dwCQ_kM#opencv #computervision #datahacker #blog
https://www.linkedin.com/in/andrey-pak-9681aa11a
Los Angeles, CA
Andrey Pak
Quality Assurance Engineer
https://www.linkedin.com/in/andrey-pak-35836322
Washington DC-Baltimore Area
Andrey Pak
Vice President of Finance
https://kz.linkedin.com/in/andrey-pak-vic
Kazakhstan
Andrey Pak
Customer operation director – Tele2 Kazakhstan
https://jp.linkedin.com/in/andrey-pak-187ab939
Tokyo, Japan
Andrey Pak
Recruiter at Applied Intuition
https://kz.linkedin.com/in/andrey-pak-b15b7733
Kazakhstan
Andrey Pak
Engineering Manager/ Chief Digital Information Officer (CDIO)
OpenCV
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