Elham joined Columbia in 2020 as the Herbert and Florence Irving Assistant Professor of Cancer Data Research (in the Irving Institute for Cancer Dynamics) and Assistant Professor of Biomedical Engineering. She is also affiliated with the Department of Computer Science, Data Science Institute, and the Herbert Irving Comprehensive Cancer Center. Elham holds a BSc in Electrical Engineering from Sharif University of Technology, an MSc in Electrical Engineering and a PhD in Bioinformatics from Boston University. She was a postdoctoral fellow in the Dana Pe'er Lab at Columbia University and Memorial Sloan Kettering Cancer Center. Her multidisciplinary research utilizes novel machine learning techniques and single-cell genomic and imaging technologies to study the dynamics and circuitry of interacting cells in the tumor microenvironment. She is a recipient of the NYAS/Takeda Early-Career Innovator in Science Award, CZI Science Diversity Leadership Award, NSF CAREER Award, Tri-Institutional Breakout Prize for Junior Investigators, NIH NCI Pathway to Independence Award, American Cancer Society Postdoctoral Fellowship, and IBM Best Paper Award at the New England Statistics Symposium.
Teaching: BMCS 4480 Statistical Machine Learning in Genomics (Spring Semester)
NCI T32 Postdoctoral Fellow (co-mentored with José McFaline-Figueroa)
Lingting is a postdoctoral research scientist at the Herbert and Florence Irving Institute for Cancer Dynamics. She received a BS in biomedical engineering at Rutgers University, where she worked on developing an in vitro approach to identifying skin sensitizers with machine learning tools in Dr. Martin Yarmush’s Lab. Then for her Ph.D. degree, she joined Dr. Lance Kam’s lab at Columbia BME to study the mechanosensing of regulatory T cell induction for the generation of Tregs to treat autoimmune diseases. Now, Lingting is very excited to study cancer with computational approaches and explore the interaction between the immune system and cancer in the Azizi lab! Outside of the lab, Lingting enjoys cycling, camping, traveling, and exploring NYC.
PhD student (co-advised with David Blei), Eric & Wendy Schmidt Center Ph.D. Fellow
Achille is currently a Columbia PhD student in Computer Science. He previously studied at Ecole Polytechnique in France, where he developed his passion for theoretical science (mathematics, statistics, physics, CS) and machine learning. Achille has oriented his scientific excitement toward biology and genomics when conducting research in the Yosef Computational Biology lab at UC Berkeley in 2019. He is enthused about the potential of data, computer power and rigorous analytical tools to solve global issues and he hopes to make valuable progress in the Azizi Lab!
PhD Student, Kaganov Fellow
Cameron is a PhD student in the BME department. While an undergraduate at Stanford, she majored in both Physics and Human Biology, and was a member of the varsity women's lacrosse team. After completing her undergraduate degrees in 2018, she stayed at Stanford for her Master's in Bioengineering. Originally from the Boston area, Cameron is happy to be back on the East Coast and is very excited to be able to explore machine learning and cancer biology in the Azizi lab!
Linyue (Joy) Fan
MS/PhD Student, Van C. Mow Fellow
Joy is a current PhD student in the BME department. She completed undergraduate training at MIT, where she studied Biological Engineering with a minor in Computer Science. Her previous work in the MIT Synthetic Biology Center involved using deep learning approaches to study the behavior of synthetic circuits in human stem cells. She is excited about working at the intersection of computer science, engineering, and experimental biology, and hopes to develop novel machine learning methods for the study of cancer in the Azizi lab.
MS/PhD Student, Columbia Presidential Fellow
Yinuo is currently pursuing his PhD in BME after completing his BS in Computer Science at Columbia. He is interested in applying computational and statistical methods to sequence analysis, especially processing single-cell and long-read sequencing data.
Ioana (Lia) Lia
MS/PhD Student (co-advised with José McFaline-Figueroa)
Ioana is currently pursuing her PhD in the Biomedical Engineering department at Columbia University. She completed her undergraduate degrees in Applied Mathematics and Biomedical Engineering at Columbia, where she became interested in better understanding cancer and its possible solutions. After working on engineering bacteria to treat cancer in the Danino lab, Ioana is hoping to use single cell genomics and machine learning methods to gain more insight into the disease progression and treatment response in cancer; and she is very excited to do so under the guidance of Prof. Azizi and Prof. McFaline-Figueroa.
Justin is a Columbia PhD student in the CS department. He completed his undergrad and Master’s at UC Berkeley in 2020 where he studied Computer Science & Molecular and Cellular Biology with an emphasis in Immunology. Justin has experience developing methods for single-cell data analysis in both the Song Lab and the Yosef Lab at UC Berkeley. He hopes to continue developing computational methods to uncover valuable biological insights in the Azizi Lab!
MS/PhD Student (co-advised with José McFaline-Figueroa), NSF Graduate Research Fellow and Blavatnik Fellow
Kevin graduated from Dartmouth College with a BA in Biomedical Engineering with High Honors and is an entering MS/PhD student in the Biomedical Engineering Department at Columbia. As an undergraduate, he conducted research using data science and machine learning to improve emerging biomedical imaging modalities such as fluorescence-guided surgery and photoacoustic imaging in breast cancer. After graduating, Kevin joined ClearView Healthcare Partners as a strategy consultant to advise biotechnology and pharmaceutical companies. He is interested in advancing novel therapeutics in cancer and other intractable diseases. He joins the Azizi and McFaline-Figueroa labs to further their work in machine learning and cancer biology dynamics.
PhD Student (co-advised with Andrea Califano)
Ming is a Ph.D. student in the Molecular Therapeutics and Systems Biology Departments at Columbia University Medical Center. He completed his BS in Computer Science and Mathematics from UC San Diego in 2019 and his MS in Computational Biology from Cornell University in 2022. Mingxuan has experience developing deep learning and statistical models for cancer genomics data at Memorial Sloan Kettering Cancer Center. His research focuses on developing novel probabilistic learning models for multi-omics data that decode cancer dynamics under molecular therapies with interaction networks and graphs. He is excited to create interpretable machine learning models that offer quantitative perspectives on systems onco-pharmacology in the Azizi and Califano labs.
Collaborating PhD Student
Nicolas is a Computer Science Ph.D. student at Columbia University interested in Bayesian Statistics, Reinforcement Learning and Probabilistic Programming. Previously, he worked at Fero Labs where he focused on developing new machine learning algorithms for improving process efficiency in industrial settings with the aim of reducing CO2 emissions. More generally he is interested in applications of AI and Machine Learning to high-impact domains that contribute positively to society. Nicolas holds a B.A in Computer Science, Mathematics, and Statistics from Columbia University.
Xumin is currently a MS student in the BME department. She majored in Bioinformatics previously at Xi’an Jiaotong-Liverpool University, where she worked in the Wei lab to improve the performance of the MeRIP-Seq peak caller. She was inspired to use deep learning to investigate the connection between the immune system and cancer. She is eager to explore computational genomics in the Azizi lab!
Michael is pursuing his MS in Biomedical Engineering. In the past, he majored in Biomedical Engineering and minored in Computer Science and Electrical Engineering at George Washington University in DC. At GWU, Michael conducted research and developed a passion for machine learning and artificial and how he can leverage it to create personalized treatment for patients. In the Azizi Lab, Michael hopes to develop this interest further and explore how single-cell data can create better patient treatments and outcomes.
Jia Yi (Ady) Zhang
Ady is a SEAS MS BME student specializing in Machine Learning and Bioinformatics. She graduated from the Johns Hopkins University double majoring in Applied Mathematics & Statistics and Molecular & Cellular Biology. At the Azizi Lab, she is excited to leverage ML to single-cell data in order to further understand cancer biology and ultimately make a clinical impact. In her free time, Ady enjoys painting, singing, and learning guitar!
Josh is an MS student in the Biomedical Engineering Department at Columbia University. He completed his BS in Computer Science at Rensselaer Polytechnic Institute in 2022 with a focus on machine learning applications. Josh has experience in developing deep learning models combining clinical data and imaging techniques for clinical usage such as surgical navigations. He is currently interested in researching interpretable machine learning models that contribute to identification of biological systems for the Azizi lab.
Khushi is currently pursuing an MS in Computer Science. She previously majored in Computer Science at the University of California, Berkeley. Previously, her research focused on deep learning and computer vision architectures. At the Azizi lab, she hopes to develop her interest in developing these models for biomedical advancements. In her free time, Khushi enjoys painting, running, and scuba diving!
Kaylee Wanlu Fang
Kaylee is an undergraduate student studying Computer Science. She is interested in the intersection of technology and biomedicine, and she is passionate about applying machine learning techniques to advance biomedical research. She aspires to leverage artificial intelligence techniques to improve disease understanding, diagnosis, and treatment. In her free time, she enjoys art, music, and exploring both cities and nature.
Hannah Khanshali (CCNY)
IICD Research Intern
Hannah is a research intern in the IICD research program. She is an undergraduate student in the Macaulay Honors College at City College, majoring in Biology with an intended minor in Chemistry. She is interested in applying her knowledge of molecular/cellular biology and genetics in exploring computational methods to further understand the interactions and communication between the immune system and cancer. Outside of the lab, Hannah is a vocalist loves, making art, and hiking. She is excited to work on projects intersecting cancer biology and computational biology in the Azizi lab!
Danielle is a sophomore studying Computer Science at Columbia’s School of Engineering and Applied Science. She is excited about the potential of machine learning and computational biology to drive clinical advances. In her free time, Danielle loves to dance and explore NYC.
Jessie is a first-year student studying Biomedical Engineering at Columbia’s School of Engineering and Applied Sciences. She is excited to join the Azizi Lab to learn more about the fascinating applications of technology and machine learning in the field of medicine. In her free time, Jessie enjoys exploring NYC and playing piano.
Xueer Chen, Postdoctoral Research Scientist (2021-2022); Next position: Senior scientist at Bristol Myers Squibb.
Siyu He, PhD student co-advised with Kam Leong (2020-2023). Next position: Postdoctoral fellow at Stanford.
Crystal Shin, MS Student (2022-2023).
Shouvik Mani, MS Student (2021-2023). Next position: CS PhD student at Stanford.
Lauren Friend, MS Student (2020); Next Position: R&D Engineer at NASA Ames Research Center.
William O'Brien, Undergraduate Student (2023).
Tu Duyen Nguyen, IICD Alliance Program Summer Intern, Ecole Polytechnique (France) (Summer 2023).
Joshua Fuller, Research Assistant (2020-2023). Next position: MD student at Columbia.
Anabel Ojeda, IICD Summer Intern (Summer 2023).
Siddhant Sanghi, Undergraduate Student (2022-2023). Next position: PhD student at UC Davis.
Noa Kalfus, Undergraduate Student (2022-2023).
David Carrera, Undergraduate Student (2022-2022). Next position: Software engineer at Palantir.
Isha Arora, IICD Program Intern, Biomedical Engineering/Computer Science, Cornell University (2022).
Sopho Kevlishvili, Undergraduate Student (2021-2022).
Pranik Chainani, Visiting undergraduate from Statistics and Data Science, Yale University (Summer 2022).
Tamjeed Azad, Undergraduate Student (2020-2022); Next position: CS PhD student at Princeton U.
Ruxandra Tonea, Undergraduate Student (2021-2022); Next position: BME PhD student at U Chicago.
James Wang, Undergraduate Student (2021-2022); Next position: Associate Machine Learning Scientist at Atlassian.
Alex Toberoff, Undergraduate Student (2020-2021); Next position: Researcher at Jump Trading.
Max David Gupta, Undergraduate Student (2021).
Jose Pomarino Nima, Undergraduate Student (2020-2021).
Veronica Woldehanna, Undergraduate Student (2019-2020); Next Position: Software Engineer, Microsoft.
Debra Duval, Research Assistant (2021).
Kaleem Mehdi, Bioforce high school summer internship program (Summer 2022).
Madeline Rohde, High school Intern (2021-2022).
Princess Della Tsivor, High School Summer Student (2021); Next position: undergrad at Brown U.
Rachel Africk, High School Summer Student (2020); Next position: undergrad at U Penn SEAS.