As a doctoral researcher, I'm currently pursuing exciting opportunities in a number of cities. Please let me know if you have questions about my educational or professional background, experiences, or passions.
Texas A&M University - Corpus Christi
January 2018 - December 2019
B.S. in Electrical Engineering
Minor: Mathematics
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January 2020 - December 2022
M.S. in Computer Science
Concentration: Programming and Software
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January 2023 - current
PhD in Geospatial Computer Science
Texas A&M University - Corpus Christi
January 2019 - December 2019
Grader
Under/course:
Dr. Cosmina Nicula - Circuits Analysis I
Digital Systems
Dr. Pablo Rangel - Electrical Systems Design
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January 2020- June 2022
Teachers Assistant
Under/course:
Dr. Mehrubeoglu - Sensors and Systems
Dr. Jose Baca - Control Systems I
Dr. Aref Mazloum - Engineering Measurements
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July 2022- current
Research Assistant
Under:
Dr. Pablo Rangel
Dr. Chen Pan
Dr. Jose Baca (current committee chair)
Publications:
M.S. Thesis - Energy Harvesting Self-Powered and Self-Healing Topology using LoRa
Abstract:
In order to prolong the operating lifetime, designs and optimization over the Low-Power Wide-Area Networks (LPWAN) in IoT applications are gaining a lot of attention as a choice for communications in future real-time monitoring systems due to the low-power, long-range, and low-cost features. For traditional battery-powered edge devices, the main research/design focus is on reducing energy consumption and improving energy efficiency in general. These conventional low-power techniques employed in new communications protocols are gaining a lot of attention. In orthogonal, there are simultaneously emerging self-sustaining energy harvesting systems for energy extraction and conservation to alternatively prolong node lifetime. With considerations such as cost, longevity, and potential environmental hazards, energy harvesting has been gaining a lot of popularity for addressing the high costs, limited sustainability, and environmental concerns as one of the best battery substitutes. Since energy harvesters can extract various kinds of energy from ambient energy sources such as solar, wind, and kinetic, battery-less operations of many small wireless sensors are enabled. Consequently, energy harvesters are becoming increasingly popular as power sources for IoT edge devices. However, due to the unpredictability of the duty cycle caused by the unstable power supply, ongoing communication can be interrupted resulting in data corruption and inevitable re-transmission. Additionally, It can take a huge amount of time and energy for two devices to establish a connection with the list of probable discrepancies in communication like risking the loss of integrity from collisions of packets in overlapping periods of active radios in the same channel, periods of overhearing, periods of over-broadcasting, etc. With energy harvesting systems’ already limited energy, these problems make the rising hardware solutions for power conservation useless without efficient design for minimizing the possibilities of energy-waste periods. What’s even more challenging is that even after the initial connection, the volatile time data of the clock modules on embedded IoT devices can be drifted with the passage of time by the unstable power supply or be corrupted completely by frequent power outages. As a result, the embedded IoT devices will lose synchronization with each other. Since a synchronized timeline is required so that both transmitter and receiver can turn on their radio simultaneously for communication. After losing time synchronization, both the transmitter and receiver need a huge amount of time and energy to build a wireless connection for transmitting data under energy-harvesting scenarios. Such efforts can be more tremendous when considering receivers such as network gateway need to hop around different channels to collect data based on the schedule. Those challenges render existing communication protocols ineffective. In order to design sustainable systems operating with limited and unstable supply power constraints, appropriate protocols must be designed for efficient energy usage to retain the scarce energy as much as possible. This thesis proposes algorithms for a rapid-healing topology using LoRa for adapting into energy harvesting scenarios from minimizing collisions through unique multi-spreading factors and multi-frequency channel allocations. The algorithm further minimizes over-broadcasting from EH nodes through designated scheduled communications with the gateway and reduces energy consumed from recovering nodes requesting to heal back to the network through consistent in-duty-cycle periods of time for heal-listening in the initialization and healing channel. This approach essentially also provides a lot of time for transmitter nodes to harvest more energy through longer deep-sleep states in idle unscheduled communication while providing rapid healing. Operating under the LoRaWAN, experimentation will be conducted with a testbed consisting of each embedded LoRa node being managed by a central gateway for network configuration and data communication. A series of experiments will be conducted to evaluate the proposed initialization and healing algorithms in terms of time and energy consumption at different run-time phases. This is done to assist in deriving a mathematical model to describe the relationship for required capacitance for an energy harvesting LoRa node to confidently initialize and stay in scheduled sustaining sleeping and sensing routine cycles as well as to support the necessary network healing process.
Accessible in: Energy Harvesting Self-Powered and Self-Healing Topology Using Lora - ProQuest
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Conference proceeding published at International Symposium of Quality Electronic Design 2023 -
ISSAC: An Self-organizing and Self-healing MAC Design for Intermittent Communication Systems
Abstract:
Recent advancements in Internet of Things (IoT) technology draws attention to Energy Harvesting (EH) systems as a promising energy-efficient solution to the limited sustainability in IoT edge devices. However, due to the weak and unstable nature of the ambient energy source, EH nodes are vulnerable to frequent power outages. Consequently, such outages will, unfortunately, reset the volatile time module onboard, which results in synchronization problems. To enable intermittent communication under energy harvesting scenarios with limited and unstable power supply, instead of merely minimizing the occurrence of a power outage, this work will also enable a smart and swift "self-healing" MAC protocol for desynchronized EH IoT devices to synchronize its timeline with the rest of the network for communication. To demonstrate the effectiveness, we will take the popular Long-range Wide Area Network (LoRaWAN) communication protocol as the backbone for upgrading, testing, and evaluation. The experiments conducted on LoRa Nodes demonstrate the effectiveness of the proposed techniques.
DOI: https://doi.org/10.1109/ISQED57927.2023.10129347
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Conference proceeding published at Great Lakes Symposium on Very Large Scale Integration (GLSVLSI) 2024 -
MARS: MAximizing throughput for MPPT-based self-sustaining LoRa Systems
Abstract:
Due to the insufficient transient amount of energy supplied from ambient energy sources and constrained amount of energy storage in super-capacitors, energy harvesting (EH) nodes are limited with operations and vulnerable to frequent faults due to energy scarcity. Consequently, such faults will reduce reliability and energy utility due to data collisions, lost data, or idle listening. To address these challenges, this work implements a novelty task scheduling scheme to minimize energy waste and maximize throughput under these scenarios and constraints. To demonstrate the effectiveness, we use a green test bed using LoRa nodes for evaluation.
DOI: https://doi.org/10.1145/3649476.3658722
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Presentations:
Poster presented at Design Automation Conference 2023
Poster:
Will be attached soon
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Presented at the Great Lakes Symposium on Very Large Scale Integration (GLSVLSI) 2024
Title: "MARS: MAximizing throughput for MPPT-based self-sustaining LoRa Systems"
Date: June 12, 2024
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Presented at the 2024 Symposium for Student Innovation, Research, and Creative Activities
Title: "Reconfigurable Sensing Modules for Coastal Monitoring: Energy Efficient and Battery-less Autonomous Wireless Sensor Networks"
Date: April 26, 2024
Presented at the 2025 Symposium for Student Innovation, Research, and Creative Activities
Title: "Autonomous Self-Maintaining Energy Harvesting Sensing Networks with a Dynamic Gateway for Coastal Monitoring"
Date: April 25, 2025
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Presented at the 11th Annual MSGSO Student Research Symposium
Title: "Reconfigurable Sensing Modules for Coastal Monitoring: Energy Efficient and Environmentally Sustainable Autonomous Wireless Sensor Networks"
Date: October 20, 2023
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