CV

Education

• Ph.D. in Computer Science and Engineering
  • University of Nevada, Reno; GPA 3.957; May 2020
• M.S. in Computer Science and Engineering
  • University of Nevada, Reno; GPA 3.977; Dec 2017
• B.S. in Applied Mathematics
  • University of Nevada, Reno; Magna Cum Laude; GPA 3.961; Dec 2014

Ph.D. Dissertation

• Publication: Janelle Blankenburg, “Generalized Task Structure Learning for Collaborative Multi-Robot/Human-Robot Task Allocation”, University of Nevada, Reno, NV, May 2020
• Description: End-to-end system that allows multi-robot/human-robot teams to learn and execute complex, hierarchical tasks collaboratively through human demonstration and machine learning techniques. Demonstrated the system through manipulation tasks using a human and a team of two humanoid robots (a Baxter and a PR2). Languages/Tools Used: C++, Python, Robot Operating System (ROS), MoveIt!.

Master’s Thesis

• Publication: Janelle Blankenburg, “A Distributed Control Architecture for Collaborative Multi-Robot Task Allocation”, University of Nevada, Reno, NV, Dec 2017
• Description: Addressed the problem of task allocation for multi-robot systems that perform tasks with complex,hierarchical representations which contain different types of ordering constraints and multiple paths of execution.Demonstrated the architecture on a team of two humanoid robots (a Baxter and a PR2). Languages/Tools Used: C++,Python, Robot Operating System (ROS), MoveIt!.

Academic and Professional Experience

• Lead Data Scientist/Engineer - Bently Nevada (a Baker Hughes business), Minden, NV - Nov 2020 - Current
  • Anomaly and Failure Mode Detection: Development of machine learning-based analytics for detecting anomalies and identifying faults in machinery diagnostics data.
  • Distributed Data Infrastructure: Led team in development of a distributed data cluster and data pipeline for extracting, storing, and querying machinery diagnostics data for analytic applications and business insights.
• Graduate Research Fellow - Robotics Research Lab, University of Nevada, Reno - Dec 2014 - June 2020
  • Generalized Task Structure Learning: Developed an end-to-end system to learn generalized manipulation tasks for collaborative multi-robot teams using human demonstration and machine learning.
  • Task Learning and Fault Recovery Using Verbal Instruction: Extended previously developed task allocation architecture to enable robots to learn the structure of complex manipulation tasks and ask for human assistance to recover from detected faults during task execution.
  • Human-Robot/Multi-Robot Task Allocation: Extended a distributed task allocation architecture from the single-robot domain to the multi-robot and human-robot domains to enable collaboration on manipulation tasks.
• Software Engineering Intern - Sierra Nevada Corporation (SNC), Sparks, NV - Jan 2016 - March 2018
  • Obstacle Detection: Developed mathematical-based algorithms and sensor fusion methods for obstacle detection in degraded visual environments.
  • Software Maintenance Led efforts in organizing, optimizing, and maintaining a department-wide software library for and geographic and unit of measure conversions.
• Graduate Research Fellow - Nevada Space Grant Consortium (NVSGC) (NASA/EPSCoR) - Aug 2016 - May 2017
  • UAV Detect and Avoid: Development and comparison of detect and avoid algorithms for UAV via reinforcement learning techniques, e.g. Q-Learning, Asynchronous Advantage Actor Critic, and Guided Policy Search.
• Undergraduate Research Assistant - Robotics Research Lab, University of Nevada, Reno - Aug 2014 - Dec 2014
  • UAV Detect and Avoid: Developed obstacle detection and localization software via supervised machine learning techniques, e.g. Faster R-CNN and k-Nearest Neighbors.
  • UAV Rotor Failsafe During Motor Loss: Extended failsafe algorithm for stabilization and control of UAV platform in the case of motor loss.

Non-Dissertation Projects

• GPU-Accelerated PRM for Autonomous Navigation: Developed a GPU-accelerated version of the Probabilistic Roadmap (PRM) planner which sped up planner up to 78x in simulated navigation tasks; Languages/Tools Used: C++, Python, CUDA.
• HRI Study of Intelligence and Animacy in Robots Performing False-Belief Tasks: Mentored undergraduate student in performing an HRI study evaluating how a NAO robot demonstrating a Theory of Mind (ToM) influenced human perception of the robot’s social intelligence and animacy; Languages/Tools Used: Python.
• Technical Paper Recommendation System: Combined deep-learning based semantic analysis and complex network theory to recommend technical papers that are semantically similar to a user’s query; Languages/Tools Used; Languages/Tools Used: Python, Gensim, Gephi.
• Object Classification: Developed an object classification algorithm which utilized a pre-trained neural network as a feature extractor for classifying unseen object classes; Languages/Tools Used: Python, Torch, Model Zoo, Scikit-Learn.
• Clothing Trend Prediction: Developed a machine learning algorithm to predict clothing trends across several cities for any given day of the year; Lanuages/Tools Used: Python, Scikit-Learn, SciPy.
• NASA UTM Interface Testing: Assisted in testing of Nevada’s interface with NASA’s Unmanned Traffic Management (UTM) system through drone flights; Languages/Tools Used: Python, Q-Ground Control.
• NASA Beyond-Line-of-Sight Drone Testing: Visual observer for Nevada’s drone testing using NASA’s Unmanned Traffic Management (UTM) system for beyond-line-of-sight drone flights; Languages/Tools Used: N/A.

Technology Skills

• Comfortable: Python, C/C++, SQL, MATLAB, Robot Operating System (ROS), Git
• Familiar: Scikit-Learn, NumPy, Pandas, SciPy, CUDA, Hadoop, Apache Drill, PyTorch, TensorFlow, Gazebo

Publications

• Refereed Journal Articles
  • S. Pourya Hoseini A., Janelle Blankenburg, Mircea Nicolescu, Monica Nicolescu, David Feil-Seifer. “Active Eye-in-Hand Data Management to Improve the Robotic Object.” Computers, 2019. Article chosen as issue cover.

• Refereed Conference Proceedings
  • Janelle Blankenburg, Mariya Zagainova*, Stephen Michael Simmons*, Gabrielle Talavera*, Monica Nicolescu, David Feil-Seifer. “Human-Robot Collaboration and Dialogue for Fault Recovery on Hierarchical Tasks.” In International Conference on Social Robotics (ICSR), Golden, Colorado, USA, Nov 2020.
  • Andrew Palmer, Chris Peterson*, Janelle Blankenburg, David Feil-Seifer, Monica Nicolescu. “Simple Camera-to-2D-LiDAR Calibration Method for General Use.” In International Symposium on Visual Computing (ISVC), July 2020.
  • Janelle Blankenburg, Richard Kelley, David Feil-Seifer, Rui Wu, Lee Barford, Fred Harris. “Towards GPU-Accelerated PRM for Autonomous Navigation.” In International Conference on Information Technology: New Generations (ITNG), Las Vegas, Nevada, USA, April 2020.
  • Elif E. Bas, Mohamed Moustafa, David Feil-Seifer, Janelle Blankenburg. “Using a Machine Learning Approach for Computational Substructure in Real-Time Hybrid Simulation.” In IMAC-XXXVIII Conference and Exposition, Houston, TX, Feb 2020. Society for Experimental Mechanics (SEM).
  • Bashira Akter Anima, Janelle Blankenburg, Mariya Zagainova*, S. Pourya Hoseini A., Muhammed Tawfiq Chowdhury, David Feil-Seifer, Monica Nicolescu, and Mircea Nicolescu. “Collaborative Human-Robot Hierarchical Task Execution with an Activation Spreading Architecture.” In International Conference on Social Robotics (ICSR), Madrid, Spain, Nov 2019. Best Paper Award Finalist
  • Monica Nicolescu, Natalie Arnold*, Janelle Blankenburg, David Feil-Seifer, Santosh Balajee Banisetty, Mircea Nicolescu, Andrew Palmer, Thor Monteverde. “Learning of Complex-Structured Tasks from Verbal Instruction.” In IEEE-RAS International Conference on Humanoid Robots (Humanoids), Toronto, Canada, Oct 2019.
  • S. Pourya Hoseini A., Janelle Blankenburg, Mircea Nicolescu, Monica Nicolescu, and David Feil-Seifer. “An Active Robotic Vision System with a Pair of Moving and Stationary Cameras.” In International Symposium on Visual Computing (ISVC), Lake Tahoe, USA, Oct 2019.
  • Stephanie Sturgeon*, Andrew Palmer, Janelle Blankenburg, David Feil-Seifer. “Perception of Social Intelligence in Robots Performing False-Belief Tasks.” In IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), New Delhi, India, Oct 2019.
  • Janelle Blankenburg, Santosh Balajee Banisetty, Seyed P. Hoseini, Luke Fraser, David Feil-Seifer, Monica Nicolescu, and Mircea Nicolescu. “A Distributed Control Architecture for Collaborative Multi-Robot Task Allocation.” In International Conference on Humanoid Robots (Humanoids), Birmingham, UK, Nov 2017.

• Non-Refereed Conference Posters
  • Taylor Boyd*, Mariya Zagainova*, Janelle Blankenburg, Monica Nicolescu, and David Feil-Seifer. “Hierarchical Task Learning Through Human Demonstration,” Poster Paper in Proceedings of the University of Nevada, Reno Summer Undergraduate Research Symposium. Reno, NV. August, 2019.
  • Eloisa Burton*, Janelle Blankenburg, Monica Nicolescu, and David Feil-Seifer. “Simultaneous Task Collaboration Architecture,” Poster Paper in Proceedings of the University of Nevada, Reno Summer Undergraduate Research Symposium. Reno, NV. August, 2019.
  • Natalie Arnold*, Andrew Palmer, Janelle Blankenburg, Monica Nicolescu, and David Feil-Seifer. “Extracting Spatial Relations from Natural Language Instruction,” Poster Paper in Proceedings of the University of Nevada, Reno Summer Undergraduate Research Symposium. Reno, NV. August, 2018.
  • S. Michael Simmons*, Andrew Palmer, Janelle Blankenburg, David Feil-Seifer, and Monica Nicolescu. “Multi-Robot Systems Overcoming the Unexpected through Dialog,” Poster Paper in Proceedings of the University of Nevada, Reno Summer Undergraduate Research Symposium. Reno, NV. August, 2018.
  • Maya Cratsley, Janelle Blankenburg, and David Feil-Seifer. “Understanding Role-Appropriate Capacities for Robots,” Poster Paper in Proceedings of the University of Nevada, Reno Summer Undergraduate Research Symposium. Reno, NV. August, 2018.
  • AnaLisa Honour*, Janelle Blankenburg, Andrew Palmer, and David Feil-Seifer. “The Impact of Robot Criticism on Human-Robot Interaction,” Poster Paper in Proceedings of the University of Nevada, Reno Summer Undergraduate Research Symposium. Reno, NV. August, 2018.
  • Stephanie Sturgeon*, Andrew Palmer, Janelle Blankenburg, and David Feil-Seifer. “Perception of Intelligence and Animacy in Robots Performing False-Belief Tasks,” Poster Paper in Proceedings of the University of Nevada, Reno Summer Undergraduate Research Symposium. Reno, NV. August, 2018.
  • Janelle Blankenburg, Richard Kelley, and David Feil-Seifer. “Failsafe Algorithms for Stabilization and Control of UAS Platforms,” Poster Paper in Proceedings of the NASA EPSCoR and Space Grant Consortium Annual Meeting. Las Vegas, NV. April, 2015.

*: Undergraduate co-author

Invited Talks (Exculding Conference Talks)

• Generalized Task Learning for Human-Robot Collaboration: University of Texas Arlington, April 2020
• Generalized Task Learning for Human-Robot Collaboration: University of Louisville, March 2020
• Generalized Task Learning for Human-Robot Collaboration: University of South Carolina, March 2020
• Generalized Task Learning for Human-Robot Collaboration: University of Massachusetts Lowell, Feb 2020
• Robot Operating System (ROS) Tutorial: University of Nevada, Reno - Research Experience for Undergraduates (REU) Site, July 2019 (Approx. 15 students)

Honors and Awards

• International Conference on Social Robotics (ICSR) Best Paper Award Finalist: “Collaborative Human-Robot Hierarchical Task Execution with an Activation Spreading Architecture”, Nov 2019.
• Kanako Miura Award: IEEE RAS Technical Committee on Humanoid Robotics, Oct 2019
• Graduate Student Association Travel Award: University of Nevada, Reno, Oct 2019
• UNR College of Engineering Differential Fees Graduate Research Fellowship: University of Nevada, Reno, Aug 2017 - May 2018
• Nevada Space Grant Fellowship: NVSGC (NASA/EPSCoR), Aug 2016-May 2017
• Westfall Scholar: University of Nevada, Reno, Dec 2014
  • Highest GPA of graduating undergraduate students in Department of Mathematics and Statistics
• Nevada Space Grant Scholarship: NVSGC (NASA/EPSCoR), Aug 2014-May 2015

Grant Participation

• Grant Preparation Experience
  • Quori @ UNR: An Assistance, Collaboration, and Service Research Platform For Human-Robot Interaction In the Wild, 2019. Quori CRI Competitive Competition. $2,500 (equipment). co-PI: Monica Nicolescu, Kostas Alexis, Hung La, Alireza Tavakkoli, and Yantao Shen; Role: Helped draft a significant portion of the proposal
• Researcher on Funded Projects
  • Designing Collaborator Robots for Highly-Dynamic Multi-Human, Multi-Robot Teams, 2016-2019. Office of Naval Research (ONR). $656,511. PI: Monica Nicolescu, co-PIs: David Feil-Seifer, Mircea Nicolescu; Role: Lead graduate researcher on multi-person graduate/undergraduate team
  • DURIP: Humanoid Platforms for Human-Robot Collaboration, 2014-2015. Office of Naval Research (ONR). $312,500. PI: Monica Nicolescu. co-PIs: David Feil-Seifer, Mircea Nicolescu; Role: Research performed on both Baxter and PR2 robots
  • REU Site: Collaborative Human-Robot Interaction, 2018-2020. National Science Foundation (NSF). $360,000. PI: David Feil-Seifer, co-PI: Shamik Sengupta. award #IIS-1757929; Role: Graduate mentor for 7 undergraduate students over 2 summers

Teaching

• Courses Created
  • CS 791 Machine Learning Applications: This course aims to introduce students to practical tools used to solve various types of machine learning problems. This course focuses on both standard machine learning techniques and deep learning methods. The applications being explored are data imputation, natural language processing, object recognition, and trajectory optimization. Students will work on a semester project in which they must apply some of the tools to a problem area of their choosing, with the expectation of a resulting conference paper. These projects will illustrate that students are able to use these methods to effectively solve modern problems; Assisted by: Dr. David Feil-Seifer, Spring 2019
• Instructor
  • CS 482/682 Artificial Intelligence: Problem solving, search, and game trees. Knowledge representation, inference, and rule-based systems. Semantic networks, frames, and planning. Introduction to machine learning, neural-nets, and genetic algorithms.; Revised Course Material, Undergraduate/Graduate level, (Approx. 65 students), Primary Instructor, Fall 2019
  • CS 791 Machine Learning Applications: Introduce students to practical tools used to solve various types of machine learning problems. Machine learning, deep learning, data imputation, natural language processing, object recognition, and trajectory optimization; New preparation of course, Graduate level, (Approx. 21 students), Co-Instructor: Dr. David Feil-Seifer, Spring 2019
• Guest Lecturer
  • Deep Reinforcement Learning CS 791: Robot Manipulators, (Approx. 15 students), Spring 2017. Presented guest lecture on deep reinforcement learning concepts and papers relevant to robotic manipulation tasks.

Research Mentorship

• Masters Students Mentored as Ph.D. Student
  • Bashira Akter Anima (Spring 2018 - Spring 2020)
  • Ashutosh Singandhupe (Fall 2016)
  • David Frank (Fall 2015 - Spring 2016)
• Undergraduates Mentored as Ph.D. Student
  • Nathaniel Rose* (Spring 2020)
  • Chris Peterson* (Summer 2019 - Spring 2020)
  • Taylor Boyd (REU, Summer 2019)
  • Eloisa Burton* (REU, Summer 2019)
  • Mariya Zagainova* (Spring 2017 - Spring 2019)
  • Gabrielle Talavera* (PREP, Spring 2019)
  • Natalie Arnold* (REU, Summer 2018)
  • S. Michael Simmons* (REU, Summer 2018)
  • Maya Cratsley (REU, Summer 2018)
  • Analisa Honour* (REU, Summer 2018)
  • Stephanie Sturgeon* (REU, Summer 2018)
  • Christopher Lewis (Spring 2017)

Community Involvement and K-12 Outreach

• Robotics Demonstrations: Led fellow lab members in discussing current research with various audiences (300+ K-12 students/college students/high school teachers), Fall 2014 - Present
• Research Experience for Undergraduates (REU) Graduate Mentor: Advised 7 undergraduates on various research projects over the course of two summers, Summer 2018-2019
• Robotics Academy of Nevada Teacher Training Workshop: Supervised 60 middle and high school teachers from urban and rural school districts across Northern Nevada in an engineering design process activity involving water filtration, Summer 2019
• Drone and Droids Summer Camp: Led two interactive lectures on coding and robotics for 25 high school students, Summer 2019
• Hour of Code: Assisted children in K-12 age group in programming tutorials, Spring 2015 - Spring 2017
• Reno Mini-Maker Faire: Lead presentations and demonstrations at booth for the Robotics Research Lab, Summer 2014/2015
• National Championship Air Races: Lead presentations and demonstrations at booth for the Robotics Research Lab, Summer 2014

Professional Activities and Academic Service

• Reviewer for Professional Conferences
  • IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)
  • IEEE International Conference on Robots and Systems (IROS)
  • ACM/IEEE International Conference on Human-Robot Interaction (HRI)
  • IEEE-RAS International Conference on Humanoid Robots (Humanoids)
  • International Conference on Social Robotics (ICSR)
• Maintainer
  • Distributed_Collaborative_Task_Tree: UNR Repository for distributed hierarchical architecture for multi-robot/human-robot collaboration

Society Memberships

• Institute of Electrial and Electronics Engineers (IEEE) - Member