Deep Pujara

Ph.D. Researcher in Electrical and Computer Engineering

Arizona State University | SenSIP Lab

Deep Learning · Edge AI · Solar Energy Systems · Embedded ML

11 IEEE Publications 2 Times Skyworks Intern NSF Researcher Conference Reviewer Public Speaker
Deep Pujara

Research & Publications

Advancing deep learning and edge AI for intelligent embedded systems

11*
Peer-Reviewed
IEEE Publications
4+
Years Research
Graduate Level
20+
Presentations
International
2
Peer Reviewer
IEEE & Elsevier

Featured Publications

Infrared Computer Vision for Utility-Scale Photovoltaic Array Inspection

IEEE IISA 2024

D. Ramirez, D. Pujara, C. Tepedelenlioglu, D. Srinivasan, A. Spanias

2024 15th International Conference on Information, Intelligence, Systems & Applications (IISA)

Key Innovation: Developed a computer vision system for automated thermal inspection of utility-scale solar arrays, enabling efficient fault identification through infrared imaging analysis.
View Publication →

WIP: Building a Research Experience for Undergraduates in Quantum Machine Learning

IEEE FIE 2024

J. Larson, D. Pujara, D. Ramirez, L. Miller, T. Patel, N. Babar, A. Spanias

2024 Frontiers in Education (FIE)

Key Innovation: Established a structured REU program framework integrating quantum computing concepts with machine learning, providing undergraduate students with hands-on quantum algorithm development experience.
View Publication →

Design of a New Photovoltaic Intelligent Monitoring and Control Device

IEEE IISA 2023

D. Pujara, D. Ramirez, C. Tepedelenlioglu, D. Srinivasan, A. Spanias

2023 14th International Conference on Information, Intelligence, Systems & Applications (IISA)

Key Innovation: Designed a comprehensive hardware prototype integrating voltage, current, temperature, and irradiance sensors with 1-second data transmission capability for continuous PV system monitoring.
View Publication →

Conference Review

Solar Energy Journal

Solar Energy Journal

Elsevier

Role: Manuscript Reviewer

Solar Energy and Machine Learning

IEEE Access

IEEE Access

IEEE

Role: Manuscript Reviewer

Machine Learning and Signal Processing

IEEE Transactions

IEEE Transactions on Energy Conversion

IEEE

Role: Manuscript Reviewer

Power Systems and Energy Conversion

IEEE FIE

IEEE Frontiers in Education (FIE) 2025

IEEE

Role: Conference Reviewer

Engineering Education Research

IEEE AIMV

IEEE AIMV 2025

IEEE

Role: Conference Reviewer

Artificial Intelligence and Machine Vision

Professional Experience

Industry and academic research positions

Jan 2024 – Present

Graduate Research Associate - Ph.D. Research

SenSIP Lab, Arizona State University

Tempe, Arizona, USA

  • Designing a transformer-based embedded ML architecture for real-time PV fault detection optimized for resource-constrained embedded devices using image-based datasets.
  • Conducted topology reconfiguration research on 3×3 solar array to optimize power output under varying shading conditions.
  • Developed compact embedded ML algorithm utilizing pruning, quantization-aware training, and 8-bit post-training quantization for efficient topology classification.
Transformers Embedded ML Model Compression Edge AI
Sep 2021 – Dec 2023

Graduate Research Associate - Master's Research

SenSIP Lab, Arizona State University

Tempe, Arizona, USA

  • Deployed optimized embedded ML algorithm on Arduino Nano BLE 33 using TensorFlow and TensorFlow Lite Micro, achieving 86% test accuracy for real-time solar fault detection.
  • Designed monitoring device hardware integrating voltage, current, temperature, and irradiance sensors with 1-second transmission rate and high data accuracy.
  • Reduced ML model size by 87% through advanced compression while maintaining real-time performance on edge devices.
TensorFlow Lite Arduino Model Quantization IoT
May 2025 – Aug 2025

AI Speech and Signal Processing Intern

Skyworks Solutions

Hillsboro, Oregon, USA

  • Built cycle-accurate Python simulator for systolic array accelerator with parameterizable matrix dimensions and dataflow configurations.
  • Led software-hardware co-design conducting memory hierarchy analysis, profiling SRAM/DRAM access patterns, and optimizing tiling strategies.
  • Deployed multiple audio noise-separation ML models on Skyworks custom embedded hardware (SoC/ASIC) with detailed power measurement analysis.
Python Hardware Co-Design Systolic Arrays Performance Modeling
May 2023 – Aug 2023

Broadcast Application Engineering Intern

Skyworks Solutions

Austin, Texas, USA

  • Engineered USB to SPI bridge hardware (Rev 2.0) using OrCAD with 4 chip select and reset lines, ensuring backward compatibility.
  • Built driver code in C++ enabling efficient USB-SPI communication with enhanced performance compared to Rev 1.0.
C++ OrCAD Hardware Design USB-SPI Protocol
Jan 2021 – May 2021

Student Research Intern

Indian Space Research Organization (ISRO)

Ahmedabad, India

  • Surveyed multiple research papers and analyzed different approaches on the blind carrier frequency, bandwidth identification, and cyclic spectrum methods for a better understanding of the problem statement.
  • Developed an algorithm to blindly identify the value of carrier frequency, bandwidth, and modulation scheme in 0 dB or higher SNR value with an accuracy of ±1 kHz in carrier frequency and bandwidth.
  • Created two MATLAB-based applications (one for modulated signal generation and the other one for feature estimation) to improve the user experience.
Signal Processing Wireless communications MATLAB
June 2020 – Aug 2020

Student Research Intern

Universidad Publica de Navarra

Pamplona, Spain (Virtual)

  • Designed Radio Link Budget Calculator for Terrestrial and Satellite Communication to calculate atmospheric losses including losses due to the absorption by atoms most likely oxygen and water vapor in the air.
  • Developed a MATLAB-based algorithm to translate near-field radiation patterns into far-field radiation patterns using interpolation and probe correction methods.
Antennas MATLAB

Teaching & Mentorship

Educating the next generation of engineers

100+
Students Supported
15+
Undergraduate Researchers Mentored
4
Years Experience
Aug 2025 – Present

Graduate Teaching Associate

EEE 598 – Deep Learning & EEE 515 – Computer Vision

Arizona State University

  • Lead weekly lectures and labs teaching graduate students end-to-end deep learning workflows using PyTorch on GPU infrastructure.
  • Cover comprehensive deep learning topics: perceptron/backprop, MLPs, CNNs, RNNs, Transformers/ViT, GANs, diffusion models.
  • Mentor students through complete ML pipelines including data augmentation, training loops, hyperparameter tuning on ASU SOL supercomputer.
  • Guide experiments on Intel Gaudi 2 AI Accelerator, enabling performance comparison with NVIDIA A100 GPUs.
PyTorch Deep Learning Computer Vision GPUs
Jan 2023 – May 2025

Graduate Teaching Associate

EEE 407 – Digital Signal Processing

Arizona State University

  • Supported 200+ students in understanding core DSP concepts: FFT, digital filters, sampling theory.
  • Conducted 2-3 interactive sessions per semester, facilitating practical problem-solving.
  • Developed supplementary materials connecting theoretical concepts to industry applications.
MATLAB Signal Processing FFT Filter Design
2022 – 2025

NSF REU/RET Mentor

Research Experience Programs

SenSIP Lab, Arizona State University

  • Mentored 15+ undergraduate researchers through NSF-funded REU and RET programs.
  • Provided foundational training in MATLAB, Python, and machine learning for quantum computing research.
  • Guided students through complete research lifecycle from literature review to publication-quality results.
  • Helped students secure graduate school admissions and research positions.
Research Mentorship Python MATLAB
2021 – 2022

Graduate Grader

Digital Signal Processing (EEE 407)

School of ECEE, Arizona State University

  • Grading the assignments and Homework of the undergraduate-graduate course Digital Signal Processing.
MATLAB Signal Processing FFT Filter Design

Education

Doctor of Philosophy in Electrical and Computer Engineering

Jan 2024 – Present

Arizona State University, Tempe, Arizona

GPA: 3.83/4.00

Specialization: Deep Learning, Edge AI, Solar Energy Systems, Signal Processing, and Embedded Machine Learning

Master of Science in Electrical Engineering

Aug 2021 – Dec 2023

Arizona State University, Tempe, Arizona

GPA: 3.82/4.00

Specialization: Signal Processing, Machine Learning, and Solar Energy Systems

Bachelor of Technology in Electronics and Communication Engineering

Aug 2017 – May 2021

Nirma University, Ahmedabad, Gujarat, India

GPA: 8.11/10.00

Honors & Awards

Recognition for academic excellence and research contributions

Smart India Hackathon 2020
Winner

Smart India Hackathon 2020

Indian Space Research Organization (ISRO)

Led team to top 6 placement among 50+ teams competing on ISRO problem statements. Successfully developed innovative solution for space communication applications.

View Article →
Best Paper Award - ACECAT Conference
2nd Best Paper

Best Paper Award

ACECAT Conference

Received 2nd Best Paper Award for "Blind Scrambling Code Identification for Synchronous and Self-synchronous Scrambler" at the Advancement in Communication, Electronics, Computer, and Automation Technology conference.

View Paper (Page 75) →
Renew Challenge 2023 Winner
Winner

Renew Challenge 2023

12th Arizona Student Energy Conference

Our team of 6 members won the Renew Challenge, demonstrating innovative approaches to renewable energy solutions and sustainable technology.

Certificate Information →
Renew Challenge 2024 Winner
Winner

Renew Challenge 2024

13th Arizona Student Energy Conference

Successfully defended title, winning the Renew Challenge for the second consecutive year with advanced renewable energy project proposal presentation.

SenSIP Certificate of Excellence
Certificate

SenSIP Certificate of Excellence

Arizona State University

Recognized for finishing up the braground and application-oriented training in Sensors, Signal, and Information Processing research.

Presentations & Talks

Technical presentations at conferences, universities, and industry events

Adani Foundation Talk

How Humans Taught Machines to Think

Adani University, Ahmedabad, India

Expert session on the evolution of AI and its applications in modern computing

Nirma University Alumni Talk

Introduction to Generative Pre-trained Transformers

Nirma University, Ahmedabad, Gujarat, India

Presented transformers architecture background, fundamentals and applications to students and faculty

PV Array Topology Optimization

PV Array Topology Optimization

SenSIP Industry Consortium

Research presentation on the use of embedded ML for PV topology optimization

AI Architecture Teaching

Deep Learning (EEE 598) Class Sessions

Arizona State University, Tempe, Arizona

14 classes explaining different DL architectures and their applications

Skyworks Presentation

Summer 2025 Internship at Skyworks

Skyworks Solutions, Hillsboro, Oregon

Built a cycle-accurate Python simulator for systolic array accelerator

Applied Solar Energy Research

Applied Solar Energy Research

REU & RET Programs @ SenSIP ASU

Demonstrated PhD research at ASU Research Park

Solar Energy Journal Reviewer

Peer Review Service

Solar Energy Journal

Began reviewing manuscripts for Elsevier journal

Topology Reconfiguration

Topology Reconfiguration with Embedded ML

UKIM–ASU Workshop

Presented my research work at a collaborative workshop with Ss. Cyril and Methodius University, Skopje, Macedonia.

CISE REU PI Workshop

Enhancing REU Experience

CISE REU PI Workshop

Represented the ASU-SenSIP REU site to discuss strategies for REU student engagement and pathways to graduate studies.

Embedded ML Demo

Embedded ML for Solar Monitoring

ITESM Delegation

Demonstrated our custom PV monitoring hardware to visiting professors from Tecnológico de Monterrey.

IEEE ICPS 2024

Real-time PV Fault Detection

IEEE ICPS Conference 2024

Conference presentation on embedded ML

Arizona Student Energy Conference

Real-time PV Fault Detection

Arizona Student Energy Conference - 2024

Presented work on applying embedded ML for the immediate detection of faults in solar panels

Skyworks 2023

Summer 2023 Internship

Skyworks Solutions, Austin, Texas

Engineered a custom PCB and C++ driver solution for USB to SPI bridge

SenSIP Consortium 2023

PV Monitoring Device Implementation

SenSIP Industry Consortium

Outlined the design and implementation of a the photovoltaic monitoring device

AZSEC 2023

Real-time PV Monitoring System

Arizona Student Energy Conference - 2023

Presented the design of a new intelligent device for monitoring and controlling photovoltaic systems

AZ Solar Conference

Research Experience for Teachers (RET)

SenSIP Lab, ASU, Tempe, Arizona

Mentored K-12 teachers in the basics of MATLAB, Python, and Machine Learning

IoT Smart Grids

REU & IRES Programs

SenSIP Lab, ASU, Tempe, Arizona

Guided undergraduate students in the REU and IRES programs through the fundamentals of MATLAB and Python for their research projects.

AZSEC 2022

Design and Implementation of Smart Monitoring Device

Arizona Student Energy Conference - 2022

Presented my work on designing and implementing a smart monitoring device for photovoltaic systems.

Technical Skills

Programming Languages

Python Python
MATLAB MATLAB
C++ C++

ML & Data Science

TensorFlow TensorFlow
PyTorch PyTorch
Scikit-learn Scikit-Learn
NumPy NumPy
Pandas Pandas
Matplotlib Matplotlib

Development Tools

VS Code VS Code
Git Git
Arduino Arduino IDE
Simulink Simulink
LaTeX LaTeX

Hardware & Embedded Systems

Arduino BLE 33 Sense Raspberry Pi Hat+ 2 NVIDIA Jetson Orin Nano ESP32 XBee S2C

Recommendations

Testimonials from colleagues and mentors

Skyworks

Spencer Hann

Senior Deep Learning Engineer

Skyworks Solutions, Inc.

"Deep was an excellent addition to our team over the Summer of 2025. We spent countless hours whiteboarding and then prototyping deep learning inference optimizations. He made substantive contributions to our platform and to the ideas we are exploring. His ability to quickly understand complex ideas and turn out prototypes was impressive."
Skyworks

Bhavikkumar Patel

Product Engineer II

Onsemi

"I had the pleasure of working with Deep in the same research lab during my master's thesis. While our projects were different, we often brainstormed together, and I was always impressed by his ability to tackle complex problems with creative solutions. He is hardworking, passionate, and an excellent researcher. I strongly recommend him for any future opportunities."
Skyworks

Alexander Kain

Sr Principal AI Systems Engineer

Skyworks Solutions, Inc.

"I found Deep to be an excellent team player, self-starter, great communicator of ideas, and precise scientific thinker about and quick implementer of highly complex ideas. He has made extremely valuable contributions to our team. I highly recommend him!"
ASU

Diego Reyes

Sr Computer Science Student

Arizona State University

"During my time as an undergraduate research intern at ASU-SenSIP, Deep Pujara was my mentor for a project in machine learning. He provided me with a solid foundation in classical machine learning, sharing his knowledge and expertise to help me quickly get up to speed on the background research. His leadership and technical guidance created a highly productive and collaborative environment. I am pleased to recommend Deep for his professionalism and dedication to fostering the growth of his mentees."
Intel

Jay Gupta

Sr Antenna Engineer

Intel Corporation

"During bachelor's program, Deep worked under my guidance for several projects, specifically in the domain of EM & antennas. I found him dedicated and sincere towards the work. I have noticed a good quality of proactiveness while working with him in collaboration. He always try to see the problem as a big picture and apply planned approach for the successful closure. I wish him a great success and happy to recommend his name for any future references."
Nirma University

Dr. Sachin Gajjar

Associate Professor

Nirma University

"My interaction with Deep has been during his BTech study at Nirma University. He did a number of academic projects with me. During the project work, Deep demonstrated the ability to work independently with great creativity and enthusiasm. Deep is well organized, diligent, and a fast learner. He is one of the most dedicated student that I've worked with and is always willing to put extra efforts in all of the work assigned to him. I wish him success for all his endeavors."
IBM

Dhruv Shah

Backend Developer

IBM

"Deep is knowledgeable, articulate, and innovative person to work with. I have known him for quite a time during our educational journey and being a colleague and friend of him, he is someone I trusted and always looked forward to work with him. I have seen him closely working on different projects and have always analyzed his ability to bring integrity, innovation and intelligence to his work and also his managing skills. I believe his overall presence positively impacted the work and the people around him."
Crest Data

Praveen Kukreja

Sr Software Engineer

Crest Data

"Deep is one of the strongest technologist I have worked with. He has a quick grasping power, excellent deep dive and troubleshooting ability. He is a fast learner and even as an undergraduate student he was involved in some really challenging and innovative projects related to communications and programming. His enthusiasm is contagious. It was a pleasure to work with him and brainstorm any new idea."

Get in Touch

Open to discussing research collaborations and opportunities in deep learning and edge AI

Location

Arizona, USA