Dynamic PhD student at McGill University with expertise in deep learning, machine learning, and data mining to analyze animal behaviors in blind mice and sighted mice. Proficient in R, Python, and advanced statistical modeling and algorithms, complemented by strong problem-solving skills. Successfully passed the Ph.D. Candidacy exam, demonstrating commitment to research excellence and innovation in behavioral neuroscience and vision neuroscience.
Employed deep learning and machine learning techniques to analyze animal behaviors in various contexts.
Conducted data mining and modeling for multiple behaviors, including approaching, mating, and fleeing.
Utilized R coding to perform resampling statistics on ethogram data of mice.
Passed the Ph.D. candidacy exam in Fall 2024.
Utilized deep learning techniques to analyze animal behaviors, including aggression and social interactions.
Executed genotyping for mice and conducted resident-intruder aggression tests with c-FOS immunohistochemistry.
Demonstrated proficiency in confocal microscopy, DNA extraction, and PCR methodologies.
Conducted experiments involving Cre-dependent viruses and DREADDs for behavioral studies.
Analyzed study data by constructing and executing various resampling statistical models using R.
Finalizing the master's thesis based on comprehensive research findings from this study.
Independently designed and authored survey protocol informed by large-scale data analysis.
Screened patients with epilepsy-related anxiety and depression using EPIC system.
Entered data of patients with epilepsy-associated anxiety and depression into theREDCap database.
Conducted advanced statistical analyses on all study data to derive meaningful insights.
Completed master's thesis and published two research papers based on study findings.
Designed and authored research protocol for the project independently.
Collected data from 7 patients with familial amyotrophic lateral sclerosis, administering acupuncture on Yangming meridian acupoints.
Obtained 14 blood samples and 14 interosseous muscle samples from 7 patients pre- and post-treatment.
Compared forearm muscle electromyography results of 7 patients to assess acupuncture's effectiveness on familial amyotrophic lateral sclerosis.
Collected 60 cases of essential hypertension and 60 cases of migraine.
Treated 30 patients with essential hypertension using acupuncture techniques.
Acupunctured acupoints for relief in 26 patients with migraine.
Collected 20 migraine cases without aura, obtaining 40 pre- and post-treatment blood samples.
Conducted evaluations using 80 VAS and MSQ for 20 patients before and after treatment.
Executed gene expression profile experiments, extracted leukocyte total RNA, and analyzed samples via agarose gel electrophoresis.
Performed data analysis, acquired chip images, conducted bi-clustering, and classified differentially expressed genes.
Independently published seven core papers in Chinese language periodicals.
Certificate: Passed the National Medical Licensing Examination with high marks and acquired the certificate (Certificate No: 141421022000337)
Laboratory Skills: Various and diverse Molecular Biological Technologies and Behavioral Neuroscience Technologies including DREADDs and Widefield calcium imaging
Computer Software and Database: Big data, data mining, modeling, SPSS, SAS, Python, Machine Learning, Deep Learning, Reinforcement Learning, SAM, R, MATLAB, GraphPad Prism 9, Illumina Bead Chip Reader, Illumina Bead Studio Application, Cluster 30, Gene Ontology, Bio Carta, PubMed and KEGG PATHWAY
Richard H. Tomlinson Doctoral Fellowships, McGill University 2022-2025
NEUR MS Scholarship, Wake Forest University Graduate School 2018-2020
Third-class Scholarship, Ningxia Medical University Oct. 2011
First to Second-class Scholarship, Tianjin University of Traditional Chinese Medicine 2006-2008