Prashant Dhakal
Open to R&D, process engineering, and manufacturing analytics roles

Prashant Dhakal Ph.D. Candidate

-> Industrial Engineer

Industrial & Systems Engineering Ph.D. candidate at Texas A&M University working across advanced manufacturing, AI hardware materials, machine learning, and uncertainty-aware digital twins.

Get in touch Resume Academic CV
01

About.

I build experimental and computational workflows that turn sparse process data into engineering decisions.

My research spans low-power neuromorphic nanocomposites, physics-informed laser powder bed fusion quality prediction, Bayesian digital twins for experimental prioritization, and low-energy ceramic additive manufacturing. I combine materials processing, device characterization, statistical modeling, and optimization for R&D, process engineering, manufacturing analytics, and digital manufacturing work.

At Texas A&M University, I work as a Graduate Research Assistant advised by Dr. Shiren Wang and also serve as Managing Editor for the Journal of Neuromorphic Intelligence.

02

Expertise.

Manufacturing & Process Engineering

LPBF parameter screening, additive manufacturing, process optimization, first-pass yield improvement, ceramic composites, and energy impact analysis.

AI Hardware & Advanced Materials

Neuromorphic devices, CNT/PDMS and ZnO/PVP nanocomposites, flexible electronics, memristive behavior, and low-power synaptic primitives.

Machine Learning & Digital Twins

Bayesian inference, uncertainty quantification, physics-informed ML, few-shot learning, training-free classifiers, clustering, and t-SNE.

Characterization & Experimental Design

SEM, TEM, electrical characterization, bending and cyclic reliability testing, polymer processing, nanocomposite synthesis, and validation.

Programming & Analytics

Python, R, SQL, MATLAB, Jupyter Notebook, RStudio, Minitab, Tableau, Power BI, SolidWorks, and Microsoft Office Suite.

Leadership & Technical Communication

Journal operations, peer-review coordination, teaching assistance, student mentoring, manuscript preparation, and cross-disciplinary collaboration.

03

Experience & Education.

  1. Aug 2021 - Present Current

    Graduate Research Assistant

    Texas A&M University - Industrial & Systems Engineering

    • Developed neuromorphic nanocomposite materials for energy-efficient AI hardware.
    • Built physics-informed ML workflows for LPBF quality prediction across unseen alloys.
    • Created Bayesian digital twin pipelines for sparse-data optimization and experimental prioritization.
    • Demonstrated low-energy additive manufacturing routes for complex ceramic composites.
  2. 2024 - Present

    Managing Editor

    Journal of Neuromorphic Intelligence

    • Helped launch and operate an open-access journal focused on neuromorphic computing and AI materials.
    • Improved editorial workflows, reducing manuscript processing time by approximately 30%.
    • Coordinated peer review, reviewer communication, and special-issue planning.
  3. Expected Dec 2026

    Ph.D., Industrial & Systems Engineering

    Texas A&M University

  4. Aug 2025

    M.S., Industrial Engineering

    Texas A&M University

  5. May 2021

    B.S., Mechanical Engineering

    University of Mississippi

04

Projects.

AI hardware

Bioinspired Neuromorphic Nanocomposites

Low-cost flexible CNT/PDMS and ZnO/PVP nanocomposites for durable, heterostimuli-modulated devices that emulate synaptic behavior.

Switching power
1.40 x 10-10 W
Learning gain
1,000x
Reliability
>104 cycles
View project Manufacturing ML

Physics-Informed Few-Shot LPBF Prediction

PIKNN, a training-free classifier in an 8-D physics-constrained feature space for rapid cross-material quality screening.

Dataset
1,579 builds
Materials
6 alloys
Improvement
+18.3 pp
View project Digital twins

Bayesian Digital Twin for Sparse Data

A probabilistic calibration and risk-aware optimization workflow for experimental prioritization under noisy, limited observations.

Method
Bayesian UQ
Use case
Tumor-on-chip
Exposure reduction
~31%
View project Sustainable AM

Energy-Efficient Ceramic Additive Manufacturing

Rapid fabrication of complex ceramic composites including gyroid heat exchangers for extreme-environment thermal management.

Energy reduction
>100x
CO2 reduction
Up to 1,000x
Output
Ceramic gyroids
View project
05

Selected Publications.

Google Scholar
06

Teaching & Service.

Teaching Assistant

Supported Modern Manufacturing Methods for Engineering Design, Facilities Design and Material Handling, and Engineering Economy at Texas A&M University.

Mentoring

Mentored undergraduate and graduate students progressing to United Airlines and graduate study at Texas A&M University.

Professional Service

Journal peer reviewer for Scientific Reports and member of IISE and SME professional communities.

07

Hobbies.

Beyond the lab

Outside the lab, I bring the same consistency and energy to training that I bring to research. Running and strength work keep me focused, resilient, and grounded through long goals that demand steady progress.

Prashant after a running event
Prashant outdoors during marathon training
Running

Austin Marathon 2026

I ran the Austin Marathon in 2026, a good reminder that long projects and long races reward the same habits: patience, consistency, and pacing.

Prashant strength training
Strength

Lifting

I lift religiously. It keeps me disciplined, grounded, and ready for the next demanding thing.

08

Let's connect.

I am interested in roles and collaborations across advanced manufacturing, AI hardware materials, manufacturing analytics, process optimization, and digital twins.

pdhakal321@gmail.com
LinkedIn /in/dhakalp
GitHub @Dark-Matter98
Google Scholar Prashant Dhakal
Resume Resume
CV Academic version