Samantha Klasfeld
Mentor: Doris Wagner, PhD

Thesis Title: Development and Application of Next Generation Sequencing Pipelines in Arabidopsis
Post PhD Plans: Postdoctoral Research Fellow, Pfizer
Mentor Comment: Sammy was a fantastic PhD student and lab member. In addition to developing a new tool for removing noise found in genomic datasets including ChIP-seq, she contributed to significantly to three other projects in the lab. Sammy is also an excellent teacher and promoter of data science: she taught python bootcamp, sequencing data analysis in an undergraduate research lab and even created a ChIP-seq and RNA-seq analysis that implemented over several months with all lab members. The latter that made the University/lab closure during Covid 19 one of the most productive times in the lab! Last but not least, Sammy was instrumental in initiating and stimulating lab discussions on diversity and equity. In summary Sammy is an outstanding scientist who left the lab a better place. I have no doubt she will similarly excel in her new position.

Alexandra Lee
Mentor: Casey Greene, PhD

Thesis Title: Big data for small organisms: Computational approaches to leverage large-scale microbial transcriptomic compendia
Research and Lab Description: My lab focuses on developing computational methods, mainly machine learning and deep learning, to answer different biological questions. My thesis research focused on developing computational approaches to use large-scale transcriptomic compendia to study transcriptional patterns, particularly in microbes.
Post PhD Plans: Scientist II, Computational Biology at Rheos Medicine
Mentor Comment: Dr. Lee is a creative, thoughtful scientist who has developed machine learning based approaches to answer important biological and methodological questions. I have no doubt that she will bring these techniques and new ones to bear on the challenges that we face in health and society in the years ahead.

Apexa Modi
Mentor: Sharon Diskin, PhD

Thesis Title: Characterizing the Gene Networks Associated with Non-coding Elements in Pediatric Cancer Using Integrative Genomics
Research and Lab Description: Our lab studies the childhood cancer: neuroblastoma, and we use genomics to mine drivers of disease. My thesis work involved characterizing the role of long non-coding RNAs in six pediatric cancers.
Post PhD Plans: Bioinformatics Senior Scientist I, AbbVie
Mentor Comment: Apexa has been an absolute joy to mentor. She is exceptionally focused, creative, and driven for a young scientist. Apexa plotted her own course and independently tackled all obstacles along the way to produce an exceptional body of work. Everyone enjoyed having Apexa in the lab during her time at UPenn and she will be sorely missed. I feel privileged to be a part of her journey and know she will be a huge success in her future endeavors! 

Chi-Yun Wu
Mentor: Nancy R. Zhang, PhD

Thesis Title: Multi-Omics Single-cell Analysis in Cancers
Research and Lab Description: My PhD research focused on computational/statistical method development for copy number aberration (CNA) detection and multi-omics integration in single-cell and spatial tumor sequencing data. The Zhang lab is a very interdisciplinary lab consisting of clever people from diverse backgrounds with the PI Nancy being an awesome researcher and mentor. I feel so lucky to have Nancy as my mentor!
Post PhD Plans: Postdoctoral scholar at Gladstone Institute/UCSF
Mentor Comment: Having Chi-Yun in the lab is an absolute joy. It has been a privilege watching her mature into a confident researcher. What impresses me with Chi-Yun is her capacity for growth and her tenacity in tackling difficult problems. She is a perfectionist, and she doesn’t give up! I am extremely proud of her research and I am even more proud of her as a person. I will miss her.

Qin Zhu
Mentors: Junhyong Kim, PhD; Kai Tan, PhD

Thesis Title: Understanding Gene Regulation in Development and Differentiation Using Single Cell Multi-Omics
Research and Lab Description: I was co-advised by Dr. Kai Tan and Dr. Junhyong Kim. Kai Tan’s lab uses the cutting-edge single cell tools and computational methods to systematically study cancer and cellular development. Junyhong Kim’s lab pioneers in single cell study and employs both quantitative modeling and experimental methods to understand the fundamental mechanisms that govern dynamical biological processes. During my thesis research, I used single-cell technology and computational methods to understand the development of hematopoietic stem cells and C. elegans embryos.
Post PhD Plans: Currently I’m doing a postdoc in Dr. Zev Gartner’s Lab at UCSF. I’m working on using single cell technology and computational methods to understand drug action in diseases such as cancer. In the coming years I hope to continue doing research and plan to look for faculty positions in academia.
Mentor Comment: Junhyong Kim: I first met Qin, when as a Masters student, he took my computational biology course. At that time, from reading his programs I thought he was a software engineer who learned biology. It was only later I learned that he was a biologist who just learned programing during my course! After he transitioned into the GCB PhD program, I was fortunate to become his co-advisor. He is the most productive student I have ever graduated. Not only that, he is a true scholar who has always had deepening his knowledge as his prime goal. I am honored to have had him as a student.

Gregory Chen
Mentor: Kai Tan, PhD
Saul Winegrad Award for Outstanding Dissertation

Thesis Title: Leveraging Systems Immunology to Understand the Molecular Underpinnings of Chimeric Antigen Receptor T-cell Therapy
Mentor Comment: It has been a privilege to mentor Greg! His ability to understand complex problems at the highest level, as well as to design and execute detailed experiments is simply unparalleled. Besides scientific research, Greg has demonstrated repeatedly as a natural leader and community builder. I look forward to hearing many great things from Greg!

Joe Park
Mentor: Dan Rader, MD; Marylyn Ritchie, PhD

Thesis Title: A Genome-First Approach to Investigating the Biological and Clinical Relevance of Exome-Wide Rare Coding Variation Using Electronic Health Record Phenotypes
Research and Lab Description: I was co-mentored for my thesis work as part of both the Rader and Ritchie labs, where we used genomic and EHR bioinformatic methods to assess how common and rare genetic variants associate with quantitative and qualitative phenotypes derived from EHR diagnosis codes, laboratory data, and clinical imaging. For my thesis, I studied how rare coding genetic variants derived from whole-exome sequencing associate with electronic health record (EHR) phenotypes to assess how loss-of-function variants relate to both known and novel gene-phenotype relationships in order to inform about the understudied genetic landscape of cardiometabolic diseases as well as methods for discovering novel biology.
Post PhD Plans: I’m currently back in medical school finishing up the MD-PhD curriculum before applying to residency! Clinically, I am planning on pursuing an Internal Medicine residency going into Cardiology, and research-wise I hope to continue working in the human genomics realm to uncover novel biology and contribute to the integration of genomics into healthcare.
Mentor Comment: Dan Rader: Working with Joe was one of the highlights of my career! Joe sets very high goals for himself and works with enthusiasm and diligence, applying novel techniques and methods to problems that truly are on the cutting edge of human genomics research. He has a terrifically inquisitive nature that dramatically enhanced his training and will serve him well in his academic career. He is also remarkably collaborative and focused on his large community of colleagues and friends. I’ll also note that Joe is a founding member and Concertmaster of the Penn Medicine Symphony Orchestra, and in that role has also contributed to the vitality of the Penn Medicine community.