Alvalen Shafel

About Me

A brief introduction my journey as a aspiring physicist.

Who Am I?

Alvalens
Alvalens
Alvalens

Castaly Fan

I am currently a Physics PhD candidate specializing in high-energy experimental physics, with a focus on neutrino physics and searches for physics beyond the Standard Model.

My primary research involves the SBND (Short-Baseline Near Detector) experiment at Fermilab, where I develop and apply machine-learning-based algorithms — in particular the SPINE (Scalable Particle Imaging with Neural Embeddings) framework developed by SLAC — to achieve high-precision 3D reconstruction of particle trajectories in liquid argon time-projection chambers.

Beyond my core work in neutrino experiments, I maintain strong interests in cosmology, quantum computing, and other emerging technologies at the interface of fundamental physics and computation.

Since childhood, I have aspired to make meaningful contributions to human civilization and the future of our species — and today, each step in this scientific journey feels like steady progress toward realizing that dream.

Education & Honors

Overview of my academic background and recognitions.

Education

2022Present

University of Florida

Ph.D. Candidate, Physics

Accumulative GPA: 3.89

Focusing on high-energy experimental neutrino physics and beyond Standard Model searches.

20182022

Rutgers University

B.S., Physics (Minor: Astronomy)

Graduated with Departmental Honors in Physics (Sep 2021).

Honors & Awards

Key recognitions during my academic career.

2025

URA Visiting Scholar Program Award

Universities Research Association

Oct 2025
  • Project: University of Florida SBND ν_e Cross Section Analysis and PDS Calibration Effort.
  • Granted $4,945 to support research at Fermilab. Upcoming on-site work is planned for Spring 2026.
2024

URA Visiting Scholar Program Award

Universities Research Association

Apr 2024
  • Project: University of Florida SBND PDS and Machine Learning Effort.
  • Granted $8,000 to support research at Fermilab. LED calibration device for PMT timing calibration at SBND was installed and done with the first test successfully.

IHEPA Fellowship

Institute of High Energy Physics and Astrophysics, University of Florida

Mar 2024
  • Received $15,000+ to facilitate research at Fermilab in Summer 2024.

Research & Professional Experience

Sep 2023
Start
Present
End
Gainesville, Florida, USA
Location

University of Florida

Research AssistantPhD Research

Mentor: Dr. Heather Ray

Core member of the UF Neutrino Group working on the Short-Baseline Near Detector (SBND) at Fermilab.

  • 1. Analyzing electron neutrino selection efficiency
  • 2. Performing Bethe-Bloch simulation and energy reconstruction
  • 3. Utilizing SPINE (ML-based particle imaging framework developed by SLAC)
  • 4. Establishing LED calibration system for SBND PMT calibration
Machine LearningSPINE FrameworkNeutrino PhysicsPythonData AnalysisSimulation
May 2023
Start
Aug 2023
End
Gainesville, Florida, USA
Location

University of Florida

Research AssistantSummer Research

Mentor: Dr. Neil Sullivan

Experimental condensed matter physics project on single-molecule magnets.

  • 1. Detected magnetoelectric effects in single-molecule magnets
  • 2. Designed and optimized a Tunnel Diode Oscillator (TDO) detector
  • 3. Achieved ultra-high frequency stability (~216 MHz, std dev ~300 Hz) in superfluid helium environment
Experimental PhysicsLow-Temperature TechniquesInstrumentationData Acquisition
Sep 2020
Start
Sep 2021
End
Rutgers University, USA
Location

Aresty Research Center

Undergraduate Research AssistantUndergraduate Research

Mentor: Dr. Larry Zamick

Theoretical nuclear physics – quantum mechanics with matrices.

  • 1. Developed new quantum number for symmetric patterns in wavefunctions
  • 2. Studied odd-even staggering in strong coupling regime (11×11 pentadiagonal matrix)
  • 3. Calculated electromagnetic transition rates using symbolic computation
Quantum MechanicsNuclear PhysicsMathematicaSymbolic Computation

Research Skills & Expertise

Core competencies in theoretical physics, experimental methods, and computational tools supporting high-energy and neutrino research.

Theoretical Backgrounds

Core concepts in high-energy physics, gravity, and the early universe

Experimental & Computational Expertise

Data analysis, simulation, and ML-driven reconstruction in worldwide experiments

Programming & Productivity Tools

Development environment, documentation, and scientific communication

Core Competencies

Machine Learning / Deep LearningData Analysis & Statistics3D Event ReconstructionSignal ProcessingQuantum Computing (Qiskit)PMT & Photon DetectionBasic Electronics & Instrumentation

Supporting Tools & Software

ROOT / CERN librariesSPINE (ML-based imaging)TensorFlow / PyTorchJupyter / Google ColabMonte Carlo SimulationsDigitize & Image ProcessingPMT R&D & CalibrationIBM Qiskit

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