Lambert(Guogen) Lan Email & Phone Number

Irvine, Ca, Us

Shanghai, China

In a comprehensive role, I delved into the MRI-Brady trends in China, leveraging primary data from industry leaders Abbott, Boston Scientific, and Medtronic, as well as supplementary data from companies like MicroPort. My analytical endeavors culminated in an 8-page report, which spotlighted a distinct market transition towards 3.0T MRI-Brady models. Through meticulous integration of nine clinical feedback components, I enhanced the accuracy of the data and notably forecasted a market trend transitioning from the 1.5T to 3.0T MRI-Brady models, and from non-MRI to MRI-compatible models.

Dallas, Texas, United States

In my recent research endeavor, I led the establishment of a dedicated research team focused on investigating neuron spiking activity within the hippocampus. Critical cells such as place and grid cells were central to our exploration, which play a fundamental role in spatial cognition and navigation. Under my leadership, we employed the concept of Neural Ensembles, categorizing groups of neurons based on their synchronized firing in response to distinct stimuli. To streamline our research process, I managed the MATLAB programming aspect and directed a team of five students, ensuring optimal and precise neuron analysis. Furthermore, leveraging advanced techniques like dimension reduction, we significantly enhanced our capacity to cluster and classify diverse neural responses, enabling us to delve deeper into the intricacies of neural patterns and functions. This multifaceted approach not only refined our research methodology but also yielded valuable insights into the complexities of the hippocampal region

In my previous role, I extensively employed MATLAB to deeply analyze various pattern formations, focusing predominantly on numerical simulations, including both localized and non-localized patterns. A significant part of this work involved modifying the parameters of the Swift–Hohenberg equation to derive diverse numerical outcomes. Within this extensive simulation research, a notable discovery I made was that the Fourier spectral method was markedly faster and more efficient than the finite difference approach.

During the project, my team and I devised a music recommendation software using the strengths of MATLAB and Python. We dove deep into datasets that detailed user demographics, such as age, gender, and nationality. Through hypothesis testing in MATLAB, we discerned potential disparities in music preferences between genders and identified that younger adults displayed a notable inclination towards electronic and pop genres. Our major breakthrough, however, lies in the application of machine learning techniques. Harnessing algorithms like random forest and decision trees in Python, we significantly enhanced the precision of our recommendations, cementing our understanding of the intricate ties between demographics and musical tastes. To showcase our findings, we crafted a concise five-minute presentation using LaTeX, elucidating our methodologies and insights to peers and faculty.

Irvine, California, United States

In my previous role as an educator, I was responsible for preparing and delivering meticulously structured lesson plans, which I frequently adapted based on individual student performance to ensure optimal comprehension. I fostered a collaborative learning atmosphere, taking the lead in facilitating group discussions on intricate subjects, with the Lagrange multiplier being a notable example. My ability to elucidate complex topics was regularly demonstrated in classes comprising 16 students. Moreover, the effectiveness of my pedagogical approach was affirmed by performance reviews, with an overwhelming 90% of feedback indicating that my tutorial sessions significantly benefited the students' learning experience.

Irvine, California, United States

During my tenure as a Research Assistant at the Direct Reading Program in Irvine, CA, under the esteemed guidance of Yasmeen Baki from UC Irvine, I had the unique opportunity to delve into the intricacies of knot theory alongside a dedicated team. My endeavors culminated in the design and delivery of a comprehensive Zoom presentation that shed light on the nuanced applications of this theory. Post-presentation, I actively engaged with an audience comprising three professors and six graduate students. The discussions were rich and enlightening, providing invaluable feedback, which I integrated, further solidifying my understanding of knot theory and its myriad applications

Master Of Science - Ms, Analytics, 4.0

Bachelor Of Science - Bs, Computational And Applied Mathematics, 3.857/4.0