EXPERIENCES

Electrical Engineer Applied Materials, San Jose, CA Jan 2023 – Present

· Developed a regression-based classifier to predict if Silicon Process chamber qualifies vacuum pressure.

· Developed & deployed plasma sensor circuit in a PVD chamber & utilized OpenCV to detect plasma leak.

· Designed wire harness & wiring schematics in Zuken E3S, created BOM and did obsolescence qualification of parts. Machine Learning Engineer Stretchyo, Milpitas, CA Jan 2022 – Dec 2022

· Designed circuits of custom testbed for fitness wrist band to track hand movements, measure vital body signs.

· Deployed Bayesian state estimation algorithm to estimate footsteps, learn gait, detect hand gestures.

· Developed & deployed scalable machine learning models using Keras, and TensorFlow.

· Designed multiple learning pipelines encompassing preprocessing, feature extraction, model training, and evaluation.

· Explored deep learning techniques, including recurrent neural networks (RNN) for sequence data analysis. Computer Vision Engineer Sazelo Networks, Nepal Jul 2021 – Dec 2021

· Undertook tasks which including extraction, transformation, loading processes and database access using SQL.

· Created face dataset & manually labelled it; trained 3x3 kernel on supervisory dataset;

· Implemented traditional approaches such as Random Forests and SVM to solve classification & regression problems.

· Deployed 4-layer Convolutional Neural Network for image data analysis and face recognition. Graduate Student Researcher UC Riverside PI - Dr. Jay Farrell Jul 2019 – Jun 2021

· Extended robust regressions: LTS, Huber, Tukey M-Estimator to linear Bayesian state estimation with outlier measurements. (Novel)

· Achieved low compute time for RAPS estimation using branch & bound optimization. (Novel)

· Evaluated positioning accuracy using robust estimations in Multi DGNSS; using RAPS, M-Estimator, EKF in Precise Point Positioning.

· Publication: Using PPP Information to Implement a Global Real-Time Virtual Network DGNSS Approach. 2022. IEEE TVT. ENGINEERING PROJECTS

Visual Odometry using Monocular Camera on KITTI Dataset Sep 2022 – Nov 2022

· Exercised ORB/FAST for feature tracking; computed Essential matrix for non-linear estimation of camera poses.

· Simulated rover localization in Gazebo, used Unscented Kalman Filter for fusion of camera & IMU measurements. Lidar based Road-Object Segmentation using LiDAR Pointcloud for Autonomous Driving Jul 2022 – Sep 2022

· Utilized SqueezeSeg for fast, accurate segmentation in a simulation using DNN, recurrent CRF (focus on car category). Dynamic Modeling, Control, Trajectory Planning & Navigation of Small-scale Unmanned Aerial Systems (UAS) Apr 2019 – Jun 2019

· Implemented quadrotor dynamics, PD controller model in Gazebo with ROS1, achieved motion planning & pose estimation.

· Achieved trajectory tracking using Sliding Mode Control on Bitcraze quadrotor, used OptiTrack for true positioning. Face Recognition Using Machine Learning Apr 2020 – Jun 2020

· Executed PCA & dimensionality reduction to get principal Eigenfaces, trained binary-tree struct SVM learning model.

· Did Nearest Neighbor search to find closest image, implemented histogram-oriented gradient to extract features. TEACHING EXPERIENCES

· TA’d grad courses (UCR): State Parameter Estimation, Linear Controls; held discussions, created quizzes and exams. RELEVANT COURSEWORKS

Natural Language Processing, Deep Learning, Reinforcement Learning, Advanced Computer Vision, Data Management, State & Parameter Estimation, Convex Optimization, Nonlinear Controls, Advanced Robotics, Mechanical Design, CAD/CAM. ASHIM NEUPANE +1-202-***-**** Milpitas, CA

ad3oj0@r.postjobfree.com

linkedin.com/in/ashimneupane

github.com/ashimneu

MS, Electrical Engineering (Mar 2021)

University of California, Riverside, CA (UC-HBCU Fellowship)

BS, Mechanical Engineering (May 2017)

Howard University, DC (Full-Ride Scholarship)

LQR, MPC, H-infinity, Adaptive

ROS2, Gazebo, MoveIt, OpenCV, SLAM, VISLAM

Reinforcement, DNN, CNN, RNN, Random Forest, SVM

CloudCompare, INS, GNSS, PPP, Ublox, Ucenter

PyTorch, TensorFlow, CUDA

MATLAB, Python, C++, R, Ubuntu, SQL

Siemens NX, Solid Works, FEA, ANSYS, 3D Printing, Machine Shop

SciPy, NumPy, Pandas, SKLearn

Git, SVN, RapidMiner,

TECHNICAL SKILLS

MS, Data Science (Dec 2023)

University of the Cumberlands, KY

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