Education:

B.A. in Mathematics, Applied Statistics, University of Michigan-Dearborn (2023)

M.S. in Applied and Computational Mathematics, University of Michigan-Dearborn (2023)

Current/Upcoming Job(s):

Currently, I am working as a research assistant on a couple projects for Professor Li and Professor Wong. I am currently applying to statistics doctoral programs and applying for a job/internship to assume soon.

Biography: 

In 2019, I enrolled in UM-Dearborn and with the initial intention of double majoring in Mathematics and Economics. However, after taking more courses in mathematics and statistics, I ended up double majoring in Mathematics and Applied Statistics, with a minor in Computer and Information Science as I am also interested in the coding and computing aspect of applied mathematics. I felt the ACM program was a natural extension of my undergraduate studies and graduated and decided to extend my studies to obtain a master’s degree. The faculty and staff in the Department of Mathematics and Statistics have been incredibly welcoming and supportive, and they have been extremely influential to my growth!

Why I Chose the ACM Program:

Because there was a 4+1 option for students pursuing a Mathematics undergraduate degree, I decided to pursue the ACM master’s degree as well. Also, as I began to consider graduate school, the lesser financial burden and convenience of staying within the same university and department was undeniable. The department is very supportive, and the program also allowed me gain invaluable research experience.

Masters Project Summary:   

Under Professor Fiore, I applied topological data analysis to simulated protein folding pathways transformed using time-lagged independent component analysis (TICA). The project focused on offering exposition on TICA, a dimension reduction technique, and applying TICA to random walks to determine if TICA improves binary classification accuracy. We used persistence landscapes (generated using the alpha complex) and tested a variety of classifiers before determining that TICA did not aid in classification.

Education:

B.S in Software Engineering, University of Michigan – Dearborn (2014)

M.S. in Applied and Computational Mathematics, University of Michigan – Dearborn (2023)

Current/Upcoming Job(s):

I am currently a Software Development Manager at Above the Treeline. However, with the completion of this program I will likely spend time deciding what comes next in my career.

Biography: 

I graduated from UM – Dearborn with a degree in Software Engineering and took my first job at Marathon Petroleum. I would spend some time there before moving back to Michigan and working for Above the Treeline, a small company in the book industry. Currently as a manager I spend time helping my team members and company priorities while developing software needed by the industry. As I have spent the last few years in my job, I developed the urge to further explore mathematics and find a way to integrate it with my career in software development.

Why I Chose the ACM Program:

I enjoyed my time at Dearborn as an undergraduate and recalled enjoying my math classes and I found the Professors in the department to be top-notch not only in teaching, but in being mentors to students in general. This coupled with wanting to learn the practical applications of math it was an easy decision to enroll in this program.

Masters Project Summary:   

Under the guidance of Dr. Aditya Viswanathan, we investigated the possibility of blindly recovering a signal when knowing only the magnitude of the measured signal. This was done using the Discrete Fourier transform and other properties of Linear Systems. Given a signal and a mask we used a technique of Alternating Projects to demonstrate that in certain circumstances we could get reasonably accurate recovery results in one dimension regardless of if the mask was known or not. When extended to two dimensions the results were less promising when using smaller samples and iterations to recover. There is further work to explore if a stronger computer with more samples and iterations can perform better.

Education:  

B.S. Computer and Information Science, University of Michigan – Dearborn

M.S. Applied and Computational Mathematics, University of Michigan – Dearborn

Current/Upcoming Job(s):  

Platform Software Engineer – Ford Motor Company

Math Instructor – A2PSA

CTO – Ensighter Group

Biography: 

Hello! My name is Abbass and my passion lies in finding efficient solutions to real word problems by utilizing mathematical techniques. Mathematics is all about efficiency and ultimately finding the most optimal solution to a problem.

Why I Chose the ACM Program: 

I chose the ACM program because of my deep interest in broadening my mathematical horizon. It all started after completing multi-variable calculus and asking the question “What comes next?” and taking real analysis during my undergraduate degree, that an interest in mathematics was instilled. I stumbled across the ACM program and the program mission and aim aligned with my view plus the opportunity to work on mathematical research as part of this program was a selling point that I could not simply just pass. Looking back at the experience and invaluable advice I received from the University of Michigan – Dearborn Math staff, I can confidently say that the ACM program was worth it!

Master's Project Summary: 

The masters project that I worked on for the completion of my ACM degree was “Using Fourier Series and Machine Learning to Classify 1D Signals” under Professor Viswanathan. Essentially, the motivation for this masters project was to investigate the feasibility of using Fourier series approximations as a substitute for grid-point data in machine learning applications. To come to a conclusion I utilized a feed-forward neural network architecture and generated several signal data sets to be used for this investigation. Supplying a greater number of Fourier coefficients led to similar accuracy as the grid-point data and correlated with my initial assumption. It was very interesting to find that supplying more information such as the concentration factor (Fourier space “filter” that identify where a jump occurs in the original function f ) did not produce better result which led to the conclusion that it could be a limitation of the chosen feed forward model and can be the motivation for another venture to be undergone.

Education:  

B.S. in Mathematics, University of Michigan – Dearborn (2022)

M.S. in Applied and Computational Mathematics, University of Michigan – Dearborn (2023)

Current/Upcoming Job(s):  

Currently, I work as a pharmacy technician in Detroit while also substitute teaching and tutoring. Additionally, I am interviewing for opportunities as a college instructor and considering positions with the NSA.

Biography: 

Growing up in Dearborn, I embarked on a journey that has been marked by unexpected twists and invaluable lessons. Initially driven by the dream of becoming an optometrist, my path took an unforeseen detour when I failed Calculus 1, with a dismal 4% on the final exam. However, this setback turned out to be a blessing in disguise. It was during my second attempt at the course, under the guidance of an incredible instructor, that my true passion for mathematics was ignited. This mentor's unwavering belief in me and their infectious enthusiasm convinced me to pursue a new direction. As I delved deeper into the world of mathematics, I discovered the beauty of its versatility, particularly in applied courses like Introduction to Cryptography and Fourier and Boundary Series. I am forever grateful to my family and the friends I have made for inspiring me and shaping my journey towards a fulfilling mathematical pursuit.

Why I Chose the ACM Program: 

The ACM 4+1 program at the University of Michigan - Dearborn was a natural choice for me as I was already planning to pursue a Master's degree. The program's time and cost savings, along with its proximity to my home despite the COVID pandemic, made it an ideal fit. Additionally, the Mathematics department at Dearborn has consistently provided me with knowledgeable and supportive professors, inspiring my passion for the subject. I am confident that the ACM program at Dearborn will equip anyone with the advanced skills and expertise needed to succeed in the field.

Master's Project Summary: 

I want to express my gratitude to Professor Pohkrel for his valuable guidance throughout my project. I'm really proud of what I've accomplished. My project focuses on something called Joinpoint regression, which is a statistical technique that allows us to analyze data with different linear trends. In this case, I used it to examine leukemia incidence and mortality rates. Overall, this project shed light on the changing patterns of leukemia incidence and mortality, highlighting both encouraging and concerning trends. It was an exciting journey, and I'm thrilled to have been able to explore and interpret the data in this way.

Education:  

BSc in Mathematics, Catholic University of Eastern Africa - Nairobi, Kenya (2020)

M.S. in Applied and Computational Mathematics, University of Michigan – Dearborn (2022)

Current/Upcoming Job(s):  

Currently looking for research and analysis opportunities. 

Biography: 

I was born and raised in Kenya. In High School, my teachers highlighted how well I did in Math as it was flowing knowledge for me. I’d also grown up hearing how Math was the basis of everything and wanted to find out why this was so; so I enrolled in BSc. in Mathematics program. Here, I realized my passion in Applied Mathematics and especially in the area of Numerical Analysis. I decided to undertake a Masters given the Pandemic was still in full effect and I wanted to learn how to practice Mathematics in our world thus I pursued the ACM program.

Why I Chose the ACM Program: 

I was interested in learning practical ways to implement what I’d been learning during my undergraduate studies. I chose the ACM program because it offered an in depth look at areas of Mathematics I was interested in. UMDearborn also accorded me financial aid which as an international student, lessened my financial burden.

Master's Project Summary: 

Under the guidance of Professor Yulia Hristova and Professor Aditya Viswanathan, I studied the use of the Gerchberg-Saxton algorithm to solve the 1D Phase Problem. Phase retrieval is the algorithmic solution to the phase problem and involves the reconstruction of signals from magnitude-only (or phaseless) measurements. We used the algorithm to help us reconstruct a signal of interest (SOI) from an observed signal with added noise. We also studied the use of masks and how different masks aided in the successful reconstruction of the observed signal.

Education:  

Bachelor’s Degree – Civil Engineering, Michigan Technological University, 1994

Bachelor’s Degree – Mathematics, Michigan Technological University, 1994

Master’s Degree – Mechanical Engineering, University of Michigan – Ann Arbor, 2001

Master’s Degree – Applied and Computational Mathematics, University of Michigan – Dearborn, 2023

Current/Upcoming Job(s):  

Ford Motor Company, Quality Supervisor

Why I Chose the ACM Program: 

Math has always been my favorite thing to study.  Once my kids were (mostly) grown, I pursued the master’s program at UM-Dearborn.  I chose the ACM program because it was close to my job and Ford would pay for it.  I realize that sounds unglamorous…but it is the truth.

Master's Project Summary: 

I worked with Professor Kim to write a model for the propagation of 2 diseases (i.e. similar Covid variants) within the same population.  We included some stochastic elements to the model as well.

Education:  

B.S. in Mathematics, University of Michigan – Dearborn (2022)

M.S. in Applied and Computational Mathematics, University of Michigan – Dearborn (2023)

Current/Upcoming Job(s):  

I am in the process of getting a job at the U.S. Department of Defense where I will utilize the mathematical skills I’ve learned in the ACM. 

Biography: 

I started my education at the University of Michigan-Dearborn in Fall 2019. I got my B.S. in Mathematics at the University of Michigan-Dearborn in the Winter 2022. I was made aware of the 4+1 ACM program and got in during Fall 2021. I received my M.S. in Applied and Computational Mathematics.

Why I Chose the ACM Program: 

I have a passion for mathematics and wanted to pursue it even deeper than a bachelor’s degree in mathematics. I feel that the ACM program has allowed me the opportunity to do this with challenge and guidance needed. Overall, I feel it was worth it and I hope to push further and learn even more than I know now!

Master's Project Summary: 

Under Professor Fiore’s guidance, we introduced, explained and applied a dimensionality reduction technique known as time-lagged independent component analysis (TICA) and applied it to a concept from topological data analysis known as an Euler characteristic curve. The main goal was to combine these concepts to aid in the classification of a family of bivariate normal random walks with differing covariance matrices. We chose to either perform TICA (in a variety of ways) or not do TICA, then find the Euler characteristic curve with the α-complex, then use the Euler characteristic curve, and a label for each family of random walks to classify them. We found that found that, overall, TICA did not aid with the classification with each random walk.

Education:  

B.S. in Mathematics, University of Michigan – Dearborn (2022)

M.S. in Applied and Computational Mathematics, University of Michigan – Dearborn (2023)

Current/Upcoming Job(s):  

I am currently working as a long term substitute teacher as I apply to jobs. I hope to eventually work at a college/university to teach prerequisite math courses.

Biography: 

I grew up in Dearborn Heights, Michigan and I stayed in Dearborn for my entire college career. Growing up, Math was always my favorite subject. I took every chance I had to tutor in the subject, when I would substitute teach I would always try to get math classes, and I loved helping my friends out with their math homework. However, when I got to college, it seemed like an intimidating major. I came in as a Biology major and quickly realized it wasn’t for me. After a year and a half of switching through majors and struggling to choose something I was interested in, I finally decided to try out mathematics in Winter of 2020. I felt behind in my major but I knew it was what I enjoyed doing so I stuck with it. In Fall of 2021 I learned about the ACM program and immediately knew I wanted to be part of it. This program made me feel like I was not behind anymore and I had a small group of people I belonged with.

Why I Chose the ACM Program: 

When I heard about this program it piqued my interest because of the courses it included and its quick pace.This was an opportunity to be part of something as challenging as it is rewarding. This program helped me apply so many concepts I have learned and see math in a way I was never able to before.

Master's Project Summary: 

The purpose of my project was to analyze students' demographics at The University of Michigan-Dearborn. By looking at the High Schools they attended, their GPA’s, Exam scores, and performance in math courses. I was able to create tables and graphs, as well as perform calculations to gain a deeper understanding of these students' performance in their mathematics courses and gather as much information as I could about what to expect from future students in regards to their more advanced math courses. For this project, I did not just look at students High

school demographics and information. I was also able to look at the distribution of their grades in math courses each semester as well, to see how their performance changes every semester as they go higher in course level. I was also able to conclude the likelihood of students performing a certain way in their classes both in general for all students and for Math/engineering majors.

Education:  

B.S. in Pure Mathematics, University of Michigan – Ann Arbor (2020)

M.S. in Applied and Computational Mathematics, University of Michigan – Dearborn (2022)

Current/Upcoming Job(s):  

I am currently an Institutional Research Analyst for Monroe County Community College. I develop surveys and analyze data for reports and college use. I have recently begun automating currently manual processes using code and implementing predictive methods that I learned during my time in the ACM program.

Biography: 

I began my undergraduate studies at the University of Michigan Ann Arbor in Computer Science Engineering but soon found that my passion lay in the mathematics department. I graduated with my Bachelor of Science in Pure Mathematics with a minor in Physics in 2020 - during the height of the COVID-19 pandemic. Despite most of my experience being virtual, I was welcomed into the ACM program at the University of Michigan Dearborn with open arms! The support and knowledge that my professors provided helped me get a full-time job at Monroe County Community College as a Math Navigator while I was in school. Shortly after that, I was promoted to an Institutional Research Analyst and have really enjoyed my work so far! Outside of work, I love hanging out with my family and friends in my free time, playing with my puppy Maizie, and mentoring Jefferson High School’s FIRST robotics team, TEAM 240 TEMPEST.

Why I Chose the ACM Program: 

A “hidden gem” at the University of Michigan Dearborn, I chose the ACM program because of the experienced faculty and small program size. Despite most of my education being during the COVID-19 pandemic, I had the wonderful experience of getting to know most of my professors one-on-one. I learned a great deal from this program and am excited to keep growing.

Master's Project Summary: 

Under the guidance of Professor Zhao, I was asked to analyze ten years of University of Michigan Dearborn student data and report my results. I’m thankful to have taken on the project, which allowed me to apply my math and statistics knowledge while utilizing the programming skills I learned while attending the University of Michigan.

Go Blue!

Education

B.S in Mathematics from Michigan State University

M.S. in Applied and Computational Mathematics from University of Michigan – Dearborn

Current(Upcoming) Jobs

Business Development Manager / Product Owner at Ford Motor Company where I define the business and go-to-market strategy for Fleet Management solutions in order to support our commercial customers.

Biography

I am originally from the Lansing, MI area where I graduated from Grand Ledge in 2009.  My wife Kayla and I have 2 daughters, Adelynn and Khloe, and have a third daughter on the way due in December 2021.  We enjoy spending time outside, spending time on or near the water, playing golf, and cheering on our Spartans.  I come from a long line of math enthusiasts.  My grandfather was an engineer in the Navy and designed the new docks after Pearl Harbor, both my father and uncle studied mathematics and statistics in college, and my aunt is a Mathematics Professor at the University of Southern California.  I started as an engineering major at MSU, but quickly changed my major to mathematics during my Freshman year after my (aforementioned) aunt introduced me to the vast career opportunities with a math degree.  Immediately after my undergrad I worked as a data analyst in the political domain where I maintained the organization’s SQL database, built voter scores, and projected voter turnout.  I received an offer from Ford Motor Company in the spring of 2015, and have been at Ford ever since.  I have had a few roles in my 6 years at Ford, starting as a data engineer in the Global Data Insights & Analytics (GDIA) skill team supporting connected vehicle and mobility initiatives.  In 2018, I rotated onto a small business unit called GoRide Health as a data engineer and product owner.  At the end of 2019, I moved back into GDIA as a data scientist within the connectivity analytics team focusing on prognostics (predictive analytics) for retail customers.  I moved into my current leadership and business development role in the spring of 2020 where my team is responsible for delivering Fleet Management solutions for commercial customers.

Why choose the ACM program?

My plan after undergrad was always to find some stability in my career and begin working on my master’s degree in mathematics or statistics.  Once I started at Ford, UofM – Dearborn was an easy choice given the convenience of campus being around the corner from my office.  So it was less choosing the ACM program as that was always my plan, but more finding the right fit from the university perspective.  The added benefit was the evening classes that fit my work / life schedule perfectly, and the small number of students in the program that allowed for more direct interaction with the faculty.  Completing the degree is one of my proudest accomplishments, and I recognize how lucky I was that all the pieces came together to allow me to fit working on a graduate degree into a growing family at home and my career at Ford. 

Summary of Master's Project

Under the guidance of Professor Aditya Viswanathan, we worked on a Phase Retrieval problem using multiple methods and approaches to validate our results.  Phase Retrieval refers to the problem of recovering a (typically complex-valued) quantity of interest from magnitude-only (or phaseless) measurements.  In this project, we considered the solution of such a discrete, one-dimensional Fourier-based phase retrieval problem using a two-step reconstruction procedure.  First, we linearized the phaseless (non-linear) measurement model using a technique known as lifting to obtain relative phase difference information.  Thereafter, we solved an angular synchronization problem to obtain the desired individual phase information from such relative phase estimates. Moreover, we empirically analyzed the effects of noise in this phase retrieval process which is crucial in modeling real world problems.  We then analyzed the performance of the above two-step reconstruction procedure when the measurements were corrupted by either Gaussian or Poisson distributed measurement errors. We studied the statistical properties of both the intermediate and recovered solution, then provided two equivalent models for analyzing the behavior of the reconstruction algorithm in the presence of Poisson noise.

Education:  B.S. in Mathematics, University of Michigan – Dearborn (2009)

                    M.S. in Applied and Computational Mathematics, University of Michigan – Dearborn (2021)

Current/Upcoming Job(s):  Currently, I’m a Senior Strategist for DTE Energy, working in the Gas Strategy & Planning organization.  Responsibilities include being the benchmarking lead for the gas organization, creating presentations for senior leadership on key projects, and supporting the organization’s annual planning cycle (both short term and long-term planning).

Biography: I started my undergraduate studies at the University of Michigan – Dearborn in 2004, as a Computer Science major.  During my sophomore year, I realized my passion was in Mathematics, and switched my major.  In my senior year of my undergraduate studies, I accepted a co-op position in the Customer Research & Information (CR&I) group at DTE Energy.  Shortly, after graduation, I accepted a full-time position in the CR&I group as an Associate Research Analyst.  I worked in this group for eight years, progressing in my career from an Associate Research Analyst to a Principal Research Analyst.  I accepted a position as Senior Strategist in the Gas Strategy & Planning organization in 2016.  In my free time, I enjoy spending time with my family, running, playing billiards, and watching sports.

Why I Chose the ACM Program: The reputation of the University of Michigan – Dearborn Mathematics Department is great.  I wanted to open opportunities to advance my career to a leadership position in a group focused on analytics. 

Masters Project Summary: Under the guidance of Professor Remski, I studied SIR (susceptible, infected, recovered) models and applied this modeling technique to the COVID-19 pandemic.  I utilized the initial exponential infection growth rate and an estimate for the final susceptible population proportion to estimate the parameters of spread and recovery.  Then additional modifications were added, including parameters to account for the administration of a vaccine and possible mutation or re-infection.  The case data from Michigan was utilized, separating the analysis between high population density areas and low population density areas.  My project concluded with looking at a projection of when the pandemic could expect to end.

Education: B.S. in Computational Mathematics, Michigan State University (2001), M.S. in Applied and Computational Mathematics, University of Michigan - Dearborn (2021).

Current/Upcoming Job(s): I am currently a Senior Export Compliance Manager at STTAS, a UPS Company. Upcoming job: To Be Determined.

Biography: I grew up in Livonia, Michigan, and throughout my schooling, math was a subject I naturally grasped and did well in. I considered going into Engineering for my undergraduate degree, but I decided to proceed with a major in applied and computational mathematics because I was more passionate about math. After graduation I processed mortgages for a couple of years, then I fell into trade/export compliance because of my analytical skills and my ability to work in databases. I never really knew what I wanted to be "when I grow up," and trade compliance made a fine career; however, it is not what I wanted to do for the rest of my life.

Why I Chose the ACM Program: In searching for jobs that would be interesting and fulfilling, I found that a Masters degree in Mathematics was often a requirement in job postings. I looked at other universities in the Detroit area, and the availability of evening classes drew me to U of M - Dearborn so I could continue to work full time while going to school. I met with Professor Remski and she said that I was an ideal candidate for the ACM program. In proceeding with the program, I appreciated that the class sizes were small, and the professors were all extremely knowledgeable and accessible.

Masters Project Summary: Under the guidance of Professor Gengxin Li and with data from Professor Claudia Walters, the Director of the Environmental Interpretive Center (EIC) at U of M - Dearborn, I assessed the correlation between percentage of tree canopy coverage and various socioeconomic factors in Wayne County, Michigan. The topic for this project stemmed from the virtual panel discussion on urban forests "Making Cities More Livable with Trees" hosted by the UMD EIC on October 28, 2020: https://www.youtube.com/watch?v=2_rbrkRNuno

Biography: I was born and grew up in a small town called Rajkot in India. My family migrated to Maryland-USA in 2009. I always wanted to be an engineer and decided to focus my career on oil and gas industry. I am passionate and proud about working in energy industry.

On my free time, I love to explore and travel new places. I also love to do outdoor stuff (biking, hiking, kayaking, camping). I am a vegetarian and don’t do fishing or hunting.

Why I Chose the ACM Program: I wanted to advance my understanding in complex technical subjects and expand my knowledge beyond the petroleum industry and applied to any industry setting or discipline. My past and current work involved with many computational and statistic modeling application. Also having exposure to advance mathematics and statistics concepts can be beneficial to any future career development. ACM program fitted perfectly with my aspirational goals to advance my knowledge whilst I continuously progress my current career as petroleum engineer. (Offering of evening classes was a major deal in able to complete this program)

Masters Project Summary:   Under the guidance of Aditya Viswanatham, I studied techniques to solve ill-posed inverse problems – such as those which appear in de-blurring applications – using basic principles from linear algebra. More specifically, I studied the use of various regularization techniques (such as truncated Singular value decomposition (SVD),Tikhonov regularization, and total variation minimization) to numerically solve such ill-posed problems.  These techniques were applied to the efficient solution of a phaseless imaging problem –a challenging inverse problem which arises in certain molecular imaging applications, and one which requires the recovery of (a typically complex) quantity of interest from magnitude-only measurements.

Education: B.S. in Finance, North China Electric Power University (2019), M.S. in Applied and Computational Mathematics. University of Michigan-Dearborn (2020) 

Current/Upcoming Job(s):  I plan to get into a PhD program in Statistics in the Fall 2021 semester.

Biography: I grew up in a small county in southern China. In my senior year, I won a scholarship to come to UMDearborn for an exchange program. Coming here, every day is full of challenges, everything is completely different from before, but I have also learned a lot. Under the guidance of the professors here, I grow more clear about my future direction. Later, I gave up my qualification to go to a graduate school in China and chose the ACM master program.

Why I Chose the ACM Program: Since I was young, I always heard people saying that girls could not learn math and science well. But as a girl I was not convinced. I paid special attention to mathematics and science subjects, so I have been very good at mathematics since childhood. Maybe because you like what you are good at, I like mathematics more and more. I like its beautiful and concise logic. My undergraduate major is finance, because I think it is very related to mathematics and I can use my advantages in this area. But in fact, I found that in my undergraduate studies, most of the classes were around basic definition of Finance. And the mathematics and computer knowledge I have been exposed to was not enough to support me in quantitative finance. Then I discovered this project in Dearborn. I am very interested in many statistical and modeling courses included in this project, and this project includes two cognate courses that I can freely choose the field I want to learn. I can take this opportunity to take some CIS courses. And during the exchange program in my senior year, I found the professors here were very helpful and responsible. They gave me a lot of help and hope. Their passion strengthened my decision to choose this project.

Masters Project Summary:  In the project, I used both statistics and data science methods to analyze the enrollment data of the freshmen cohorts of 2010, 2011, 2012 and 2013. My work focused on students’ cumulative GPA and 6-year (18 terms) graduation rates. Students' graduation rates for each pre-admission grade class showed that medium achievement students had the highest graduation rate in the University of Michigan Dearborn (UMD). Besides, I used linear mixed-effects models to investigate academic outcomes and logistic regression to analyze graduation status for students admitted in UMD between 2010 and 2013.

Education: B.S.E. in Nuclear Engineering and Radiological Sciences, University of Michigan - Ann Arbor (2007), minor in Mathematics. 

M.S. in Applied and Computational Mathematics, University of Michigan - Dearborn (2020).

Current/Upcoming Job(s): I am an engineer at the US Army Futures Command, Combat Capabilities Development Command - Ground Vehicle Systems Center (GVSC). I was awarded the Department of Defense - Science, Mathematics, and Research for Transformation (SMART) Scholar Fellowship for four years starting in August 2020. I will remain an employee for GVSC while being a full-time student in the Applied Mathematics doctoral program at Michigan State University in the Fall 2020 term.

Biography: I grew up in Canton, MI. After graduating from Michigan, I worked as an engineer for Knolls Atomic Power Laboratory (KAPL) in Schenectady, NY in the radiation shielding group on concept studies for future submarine class shielding. In 2011, I moved to Cleveland, OH and worked as a consultant at Newry Corp., a boutique consulting firm that advises materials and technology companies. In 2013, I returned to Southeastern Michigan and started working at my current job.

Outside of school and work, I volunteer with Last Day Dog Rescue offering a foster home for dogs. Over the last seven years I have fostered over 15 dogs.

Why I Chose the ACM Program: The ACM Program was exactly what I needed as both a working professional and an engineer looking to explore my interest in math. As a working professional, evening courses made the degree very approachable from a scheduling perspective. I was initially hesitant about pursuing my math interest especially after the academic gap while working. But after speaking with Prof. Remski and Prof. Lachance at the graduate open-house in 2017, I felt very comfortable applying to the program and felt that it would give me the opportunity to decide if I wanted to focus on math going forward in my academic and professional career.

Masters Project Summary: Under Prof. Michael Dabkowski, I studied convergence rates to equilibria of the Becker-Doring equations, which describe the coagulation and fragmentation of particle clusters in condensing vapors.

Education:  B.S. in Mathematics, University of Michigan-Dearborn (2012), B.A. in Psychology, University of Michigan-Dearborn (2012), M.S. in Applied and Computational Mathematics. University of Michigan-Dearborn (2020)

Current/Upcoming Job(s): I currently work at AAA Life Insurance Company in our Actuarial & Data Analytics department. I am on the Data Analytics team in the Analytics Delivery division. Not only do I analyze our company’s data in order to assist in making strategic business decisions,  but I also get to support other analysts by ensuring our data is easily usable and accessible, defined thoroughly, and secure (by working with IT Security) for our analysts to use. 

Biography:  I was told when going into undergraduate studies that I should become an Engineer because I liked Math. After some time, I learned that Math can be used in so many parts of business, economics, and computer science that I decided to go forth in a purely Mathematics program. When I started at my first job out of college, I absolutely loved it! I was learning basic SQL and other coding programs to pull data from tables and run analyses on this data. I soon went on to apply at my current company since my former job ceased to challenge me on a daily basis. I learn new things every day, and stay current with different trainings, conferences, and our awesome book club. 

Why I Chose the ACM Program:  Obviously the location and convenience of night classes were a huge win since I wanted to continue working while going through the program. I really loved my undergraduate experience at U of M Dearborn, and I was excited to have some of the same professors that I had in undergrad. The small class sizes are very nice since you get to know your classmates and professors by the end of the program. I also really liked that they incorporated some of the statistical programming languages that I had heard of and even sometimes used in my career.

Masters Project Summary:   I studied a complex mathematical model for honeybee populations in a colony that gets infected by Nosema ceranae, a virus that has been linked to premature honeybee deaths. I then furthered the mathematical model for the colony by simulating different outcomes when antibiotics were administered to the hive after infection.

Education: M.Sc. Applied & Computational Mathematics 

Current/Upcoming Job(s): Systems Engineer Diesel Engines – Ford Motor Company

Biography: Born – 1986 at Tiko town in Cameroon (West Africa). Came to the US in 2012. B.Sc. Electrical Engineering from Idaho State University in May 2017.

Why I Chose the ACM Program: I want to have a more quantitatively analytical mindset and approach to tasks face at work. Also, I want to change my career into Data Science and Machine Learning. UM Dearborn is known for a good Mathematics Department.

Masters Project Summary:   My project was on the reconstruction of finite dimensional complex vectors (signals) from the magnitudes of their inverse (windowed) Fourier transforms. This phaseless signal recovery problem arises in important applications such as x-ray crystallography and (Fourier) ptychographic imaging. Careful application of discrete Fourier analysis in conjunction with the solution of a special eigenvector problem to yield a fast and efficient (FFT-time) phase retrieval algorithm was used quite extensively.

Pros about the Program

-  All the teachers I came across where very accommodating to the busy schedule of Graduate students who had jobs. 

-  All the Professors where very and I mean really knowledgeable in the subject matter.

-  Curriculum is really wide so you can gain extensive knowledge in any particular field you really want to go into.

Cons about the Program

-  The way the prerequisites are structured, it is possible (Like I did) to go through the program to completion without taking a single Statistics class. That I believe should not a possibility. It doesn’t make sense to have an M.Sc. in Applied Math and not have a single stats class under your belt the whole program. My thoughts.

-  Having software skills from such a program is extremely important in the real world to show you went through such a program. The STATS 435 data analysis class is not a prerequisite. A class on software for Data Analysis should be made a prerequisite in my opinion. That was one of the most important class I took.

- Some semester they will put the time for some very important Math classes in the morning which was not very accommodating for us Graduate students.

Education: B.S. in Biomedical Engineering, Johns Hopkins University (2014), M.A.T. in Mathematics (6-12), Lee University (2017), M.S. in Applied and Computational Mathematics, University of Michigan-Dearborn (2019)

Current Job: I have worked as a math tutor and office assistant in the Math Learning Center at UM-Dearborn for the past year and a half. In the Fall 2019 semester, I will begin a Ph.D. program in Applied Mathematics at Michigan State University while working as a Teaching Assistant.

Biography: I chose to study biomedical engineering for my undergraduate degree because I thought it was the perfect intersection of all of my interests. I soon found out that what really intrigued me were the mathematical modeling and simulation aspects of engineering, and I changed my focus accordingly. After college, I taught high school math for three years while earning a Master of Arts in Teaching. I discovered a passion for teaching but missed working closely with the mathematics I had used in college. Since then, thanks in no small part to the wonderful mathematics faculty at UM-Dearborn, I have realized that my ultimate career goal is to be a mathematics professor at a university.

Why I Chose the ACM Program: I initially only planned to apply to take a couple of applied math courses at UM-Dearborn to help strengthen my mathematical and computational background and make me a better candidate for jobs in applied mathematics and engineering. However, during the application process, Professor Joan Remski reached out to me and suggested that I go ahead and enroll in the ACM program. The program seemed like a great fit with my background and interests, so I did! The ACM program has allowed me to explore different areas of mathematics and its applications, and all of my professors have been great. I have received so much support both in and out of the classroom, and I have been able to tailor my degree based on my particular interests and goals. This program has been the perfect stepping stone between my undergraduate engineering degree and my upcoming doctoral program.

Masters Project Summary: Under the guidance of Professor Yulia Hristova, I created MATLAB programs to simulate a filtered back projection-type reconstruction method using circular means for thermoacoustic and photoacoustic tomography. We also studied the effects of different types of noise on this reconstruction method, as well as potential filters to reduce noise in reconstructed images. 

Education: B.A. in Physics and Spanish, Wittenberg University (2015), M.S. in Applied and Computational Mathematics, University of Michigan, Dearborn (2019) 

Current Job: Customer Experience Data Scientist. I work on analyzing feedback from customers to determine which areas of customer interaction would yield the greatest improvement in satisfaction.

Biography: I’ve always enjoyed understanding how things work.  With math as the universal language, studying physics and then mathematics made sense to me. In my free time I like playing hockey, studying foreign languages, and traveling. My goal is to eventually visit every country, going to the areas that most tourists typically don’t visit. 

Why I Chose the ACM Program: I eventually want to go for my PhD. My employer offered to assist with this program, so it was a simple choice for me. Combining that with the fact that campus was a 5 minute drive for me and the classes started after work, I couldn’t get enrolled fast enough.

Masters Project Summary: My Master’s project was about X-ray Computed Tomography. I looked at how the images from CT scans are created from the data collected. I explored different errors that might occur within the data and their effect on the final reconstructed image.

Education: B.S. in Mathematics, University of Michigan-Dearborn (2015), M.S. in Applied and Computational Mathematics, University of Michigan-Dearborn (2019).

Current Job(s): I am currently an Office Assistant at the Math Learning Center at UMD as well as a part time Assistant Manager at my family business, “Horizon Tec USA LLC, Dearborn”, where I assist in researching and developing marketing opportunities as well as implementing sale plans.

Why I chose the ACM Program: “Life is good for only two things, discovering mathematics and teaching mathematics.” By. Simeon-Denis Poisson. Math has been my strongest and most favorite subject throughout my school years. Having taken a diverse array of mathematical subjects and working at UMD as a math tutor and mentor, cemented the fact that I wanted to abide by Poisson’s way of life and pursue a higher career in the field of Mathematics. 

Masters Project Summary: My project was titled “Eigenvalues of Markov Matrix in the Master Equation.” In this project, we study Asymmetric Simple Exclusion Process (ASEP), which is a continuous time stochastic process where particles jump independently and randomly to a neighboring vacant with two different jumping rates. We derived the Master Equation and found the eigenvalues of the Master Equation considering one-, two-, and three-dimensional models and compared the eigenvalues of each case, allowing us to determine the relationship between each dimension. 

Education: B.S. in Electrical Engineering, University of Detroit Mercy (2013), M.S. in Applied and Computational Mathematics, University of Michigan, Dearborn (2018)

Current Job: Controls Engineer, Ford Motor Company – Electric Powertrain Department. My team works on software-in-the-loop modeling, which involves crating a physically accurate simulated vehicle environment where new controls software can be tested/proved out thoroughly without the use of actual test vehicles. Interested in moving to a more data science, AI, machine learning or software development oriented role next!

Biography: I’m an infinitely curious person who enjoys traveling, learning new things and being outside. I love climbing and spend as much of my free time as possible on rock or ice, training indoors at the local gym, or planning climbing trips. One of my life’s goals is to take part in a real mountaineering expedition. I also enjoy reading sci fi/fantasy books, doing yoga, discovering good music, and learning languages: my first was Spanish and I’ve been working on German for the past 8 years (learned English at some point in between haha).

I love hiking, camping and visiting new places, exploring different foods and cultures in the process. Over the past few years, I’ve also become very interested in applications of math in data science and machine learning, so, I work on building my programming skills and crafting my personal website whenever I get the chance.

Why I Chose the ACM Program: Although I initially chose to do engineering for my undergrad degree, I have always been fascinated by math and how it can be used to describe or model almost anything that occurs in the natural world. After working as an engineer for a year, I missed school, and studying math, and thought that I would perhaps be happier finding a job where I could just…do more math.

The ACM program allowed me to do just that, keep learning what I was interested in, while working full time. I loved the small, in-person classes and found the math department at this university to be amazing, supportive, and incredibly knowledgeable. In the end, the ACM program and the skills I’ve learned through it have helped me figure out the direction I’d like to take my career in and prepared me to do so.

Masters Project Summary: My master’s project was focused on stochastic modeling of traffic flow, under the guidance of Dr. Frank Massey. Specifically, I studied the use of M/G/C/C queueing networks to model unidirectional, uninterrupted flow of vehicular traffic on a road segment (node) with a finite capacity. I studied the effect of simulated traffic jams on exponential and linear single node models and implemented an extension of the models to simulate traffic flow through a network of road segments.  I also developed a method using Dijkstra’s algorithm and constrained optimization techniques to optimize routes through the network, and re-direct vehicles traveling through the network to alleviate congestion through blocked nodes.

Education: Bachelor of Science in Biomedical Engineering from Osmania University, Hyderabad, 2000. Master of Science in Computer Science from University of Kansas, Lawrence, 2002.  

Master of Science in Applied and Computational Mathematics from University of Michigan, Dearborn, 2017.

Current Job(s): Senior Manager in Cyber Risk Services and Analytics at Deloitte & Touché in India with experience over 12 years. I have continued to pursue my Masters through the employment with the help of my awesome faculty for the last 12 years and am excited to finally complete my Masters project to graduate this Winter.

Why I chose the ACM Program:  I would consider two aspects here – why did I choose and why I would recommend:

-      With Biomedical engineering and Computer Science in Network engineering under my belt, I was still not content.  I always had a calling for Math, inspired by my grandfather during childhood, that went on to become a passion all my life. I used to teach high school students for competitive exams and more importantly, the logical reasoning around Math.  Hence, the pursuit for the true Math experience made me enroll for yet-another Masters and I thoroughly enjoyed the math including IMSE 510/MATH 573/582/STAT 535.

-      Though I had many credentials, I applied to the Master’s Program in Applied and Computational Math at UMD.  The program was attractive because of it’s applicability to the market vs. just the theory of professional Mathematics.  More importantly, I was further hooked due to the faculty, the location, the diversity at the University and the unique environment they provided for students to learn while going through their own personal/professional milestones. 

 My Faculty members: I would like to request that this section be added to call-out professors who made time beyond what they are required to, to empower students.

1.     Professor Frank Massey, who enabled this second Masters to happen, based on my prior MS in Computer Science as well as customized courses based on my evolving Data Analytics experience and encouraging to continue the rest of the Masters remotely.

2.   Prof. Alan D. Wiggins, for being the first one to support remote learning of a pretty-hands-on course MATH 554 – Fourier Series and Boundary Value Problems that I truly missed being in class for, and he was kind to share the course material and class notes that were scanned and sent via email after the class.  <<call-out to the kind-student that can’t be disclosed who shared his notes.

3.  Professor Mahesh Agarwal, who ensured an intense analyses based on on-the-ground experience of crime analyses at Detroit. I was thoroughly challenged and worked hard as Prof. Mahesh was very current that made the project real and meaningful for the Detroit community.

4.  Professor Joan Remski, who championed the cause of UMD while professionally enabled completion of the graduation over almost a decade for a graduate student like me due to career-family-location changes, and allowed me to study at UMD and be an Applied Math professional at the end of 13 years.  Her continued support was the key driver for me to complete my second Masters. 

5.   Carol Ligienza, my virtual best friend, as she continued to be cordial and provide true guidance across the decade, on what needs to be done, be it the fact that I have to re-admit and pay additional fees or ensure the applications are processed remotely in time for enrollment. 

My non-mathematical passions: I am ardent pet-lover and am proud to call out that my first child, Rio, is actually a rescue from the Detroit Humane Society.  He moved back to India with us and currently basks in the weather in our balcony - I think he actually has roots in India too as he loves the sun, people and the food!  I continue to help stray dogs with food, affection and more importantly, raise awareness about humanity towards animals.  My kids help me enjoy moments of happiness that I, as an adult don’t seem to recognize/realize till I stop and experience with them.  Finally, a new passion is organic home gardening that provide a safe haven for me-time with enough oxygen and experiencing pure growth in plants. 

I cherish and am indebted to the efforts this University and faculty have made for me to complete my course work remotely, while ensuring it’s kept as challenging or more for me as with any other graduate. 

End of it, there are numerous universities, but the curriculum, faculty and the administration makes this University very unique and very much a part of me. 

Education: I completed my B.E in Computer Science & Engineering, Madurai Kamaraj University, India in 1993 and enrolled into M.S (software engineering program) in 1999 but completed M.S in Applied and Computation Mathematics, University of Michigan, Dearborn, MI.

Biography: Started out as a software engineer/programmer after under graduation and worked for companies like DaimlerChrysler, Chrysler Financial, TD Auto Finance, Nationwide Financials and now working for CardinalHealth.  (https://www.linkedin.com/in/prabasiva/)

Why I Chose the ACM Program: I have always been interested in math since I was a kid would love to apply mathematical concepts to solve real world problems that we face every day. My passion was creating and validating models with real world data and interpreting the results. The ACM program provided a variety of tool set that I can use to model a problem that I see in the industry and solve it using one or more mathematical tool from the tool box. I loved all the courses that I took in the ACM program.  My favorite courses in the program are: a) Complex Variables with Prof. Brown. B) Stochastic Processes with Prof. Massey, c) Linear Algebra, d) Matrix computation, e) Dynamical systems with Prof. Remski.

Masters Project Summary: I studied color chaos model and time frequency analysis of S&P 500 and NASDAQ indexes. I really enjoyed working on this project and learned a lot. Got an opportunity to apply new mathematical concepts in the project.  Few to name: a) Hodrick and Prescott (HP) filters, b) Matrix vector format of Fourier (and Inverse) transforms, c) Deeper understanding of joint time-frequency spectrum analysis, d) Wigner distribution, e) Correlation dimension f) Lyapunov exponent.

Education: B.A. in Public Policy from the Gerald Ford School of Public Policy at the University of Michigan (2014), M.S. in Applied and Computational Mathematics from the University of Michigan Dearborn (2017).

Biography: As an undergraduate student, I concentrated my degree on economic analysis of public policy. I chose to further my education in quantitative analysis by pursuing a master’s degree in applied mathematics. 

I found that this program was very flexible in coursework and gained significant skills in data and statistical analysis. In the program, I also gained invaluable exposure to computer programming. My graduate education helped me develop real skills and drew a more analytical career path from my undergraduate education. 

Why I chose the ACM program: This program is small and diverse. As a student, I was able to network with people from all different backgrounds, including education, engineering, and data analysis. I was also able to develop close relationships with professors. The low student-to-teacher ratios, flexible coursework, and independent research project are ideal for students seeking mentorship and career guidance.  

Master’s Project Summary: My research project explored and compared how fast Fourier transforms, the VisuShrink wavelet shrinkage algorithm, and the SureShrink wavelet shrinkage algorithm denoise different types of one-dimensional discrete signals with varying levels of noise. I found that fast Fourier transforms remove noise from smooth, continuous signals best, but fail to capture abrupt changes in information. I also found that, in general, the SureShrink algorithm outperforms the VisuShrink algorithm in reconstructing signals with sharp changes in information. When information is sparse however, the VisuShrink algorithm produces comparable results to the SureShrink algorithm and is less computationally expensive. 

Education: B.S. in Electrical Engineering, University of Arizona, Tucson, AZ (1982), M.S. in Computer Information Systems, University of Phoenix, Phoenix, AZ (2003), M.S. in Applied and Computational Mathematics, University of Michigan, Dearborn, MI (2017).

Biography: Started out as an enlisted guy in the Air Force working in an electronics field calibrating missile guidance systems. I did a lot of night school and qualified for the Airman Education and Commissioning Program. The Air Force sent me to school to get my BSEE and an officer’s commission. Then I was sent to Wright-Patterson AFB to work in the Air Force R&D labs where I worked on designing and fabricating solid-state circuits using Gallium Arsenide material (GaAs). 

After I retired out, I started teaching mathematics at ITT Technical Institute for twelve years. I covered everything from college algebra to Calculus I & II. Teaching has been a very satisfying career change for me.

Why I Chose the ACM Program: I have always been interested in math since I was a kid but, math theory and theoretical type courses bored me. My passion was number crunching on real world type problems and interpreting the results. The ACM program focused me to do just that. Compute smarter not harder. My favorite course in the program was Complex Variables with Prof. Brown.

Masters Project Summary: I studied extracting weak signals from background noise and comparing which mathematical techniques were most sensitive to finding weak signals. What I looked at was the Fast Fourier transform (FFT) and wavelets for denoising the signals.

Education: Bachelor of Arts in Mathematics Education from University of Michigan, Ann Arbor, 2010. Master of Science in Applied and Computational Mathematics from University of Michigan, Dearborn, 2017.

Current Job(s): I teach mathematics in Bloomfield Hills. I have been teaching for 7 years and have taught everything from remedial algebra 1 to AP calculus. During the summer I teach Math 103 at the University of Michigan Ann Arbor for their Comprehensive Studies Program. I have been teaching with that program since 2011.

Why I chose the ACM Program: I really enjoy math and wanted to push myself to learn more about it! Also this program is accredited by Rackham which was a huge deciding factor for me.

My Masters' Thesis: "Using Simulation Models & Survival Analysis to Understand HIV and AIDS" under Dr. Frank Massey.

My non-mathematical passions: I love cooking, baking, traveling (my "places to go" list keeps expanding!), planning events for friends, spending time with my family, fashion, mission work (I have been to Central America twice for mission trips), and crafting.

Education: B.S. in Adolescence Education (7-12): Mathematics and Physics, SUNY Cortland, New York (2012)M.S. in Applied and Computational Mathematics, University of Michigan Dearborn, Michigan (2016)

Current Job: I have been working as a mathematics teacher at Novi High School in Novi, Michigan for 5 years. I have taught a variety of coursework including Advanced Placement (AP) and International Baccalaureate (IB) courses. 

Why I chose the ACM program: I was excited about learning applications of mathematics since my undergraduate coursework was mostly theoretical based. The program allowed me to work on solving mathematics problems that had applications in the real world and the coursework continuously challenged my mathematics skills. My favorite course was Partial Differential Equations with Professor Zhao.

Masters Project Summary: I studied the backpropagation algorithm which is a method of gradient descent to train neural networks. I used the Haberman’s Survival Data Set and the Java application Neuroph to apply the algorithm and train the data set.   

Education: B.S. in Mathematics/ Mathematics Secondary Education, Grove City College, Pennsylvania (2012). M.S. in Applied and Computational Mathematics, University of Michigan Dearborn, Michigan (2016).

Current Job: I have been working as a Mathematics teacher at Mumford High School in Detroit, MI over the past four years. I have taught 9th, 11th and 12th grade courses.  I was initially placed here through a program called Teach for America. I also coach the Boys’ and Girls’ Tennis Team.

Why I Chose the ACM program: I wanted to continue my mathematical education as it has made me a better teacher overall. The focus on Applied Math appealed to me as most of my undergraduate work was theoretical. My favorite course in the program was Dynamical Systems with Professor Lachance.

Masters Research Project: I studied different models of Opinion Dynamics which seeks to model how opinions evolve in a population considering different types of agents. I extended the work of Serge Galam to different combinations of agents and wrote a code in Mathematica to simulate the model.

Education:    B.S. in Management Science, School of Management, Xi’an Jiaotong University, China. (2013); M.S. in Applied & Computational Mathematics, CASL, University of Michigan -Deaborn. (2016); M.S.E. in Industrial Systems Engineering, CECS, University of Michigan - Dearborn. (2016).

Biography: I was enrolled in the dual degree program in the University of Michigan - Dearborn. I’m now a PhD candidate at Georgia Institute of Technology, majoring in Operations Research. Before this, I was working for the University of Michigan - Dearborn as a graduate student instructor for engineering statistics. I have also been working for Ford Motor Company for one year doing system simulation analysis using discrete events simulation and Monte Carlo simulation.

Why I chose the ACM program: The ACM program provides solid training on mathematics theories as well as their applications in the real world. The mathematical education is essential for engineering students like me who are planning to continue for a PhD. My favorite course in ACM is Advanced Calculus taught by Prof. Alan Wiggins.

Master Research Projects: Data-driven algorithm design for robust optimization; Utility-based sensitivity analysis for alternatives ranking; Simulation-based system analysis using Monte Carlo method; Change-point statistics inference and applications in engineering field. Detailed information can be found on my personal website: https://sites.google.com/a/umich.edu/junxuanli/.

Previous degree: Oakland University: BA in Economics, 2010.

Current Job: I have recently started working as a quality assurance analyst. I work at a local software company named Workforce Software. Before this, I was involved with application development and worked directly inside the professional services department. The majority of the work I do involves writing or testing code.

As a volunteer, I am a mathematics tutor. I have helped students with a variety of subjects dealing with geometry to calculus.

This work relates indirectly to the MS Degree in Applied and Computational Mathematics since many of the consultants that I work with are trained in either mathematics or computer science. I was influenced by an older neighbor who used to write code for the Texas Instrument calculators.

Favorite Classes at UM-Dearborn: Complex Variables with Professor Brown:  Understanding Cauchy’s integral theorem and the Residue theorem allowed me to study the Riemann zeta function. Understanding how to construct the real numbers was also beneficial to my studies.

Numerical Analysis with Professor Massey:  It was interesting to see how computer programs can numerically approximate solutions. In particular, what is known as Gaussian quadrature is effective in numerical integration. Numerical Solutions to PDEs with Professor Zhao: I liked learning about theory behind the finite element and finite difference methods.

Favorite Math Books: Fundamentals of Mathematics by Professor Richardson: This greatly enhanced my understanding of mathematics and is great for undergraduate or graduate students. Linear Algebra by Professor Strang: I enjoyed reading this textbook when I took Linear Algebra. It helped provide a conceptual framework for an interesting subject. It also helped me understand some of Abstract Algebra. 

Masters Project Summary: My project dealt with calculating numerical values for the Riemann zeta function. I first read Edward’s Riemann’s Zeta Function and then found a useful set of tutorials made by MrYouMath (a German mathematician) on Youtube. I wrote a variety of Java programs that calculated numerical values for the Riemann zeta function. I also analyzed applications of the Riemann zeta function including the Cauchy-Schlomilch transformation, Abel-Plana formula, Lehmer’s Phenomenon, and Apery’s constant.