Curriculum Vitae

Downloadable CV

Education

• Ph.D in Mathematics, The Ohio State University, 2022
  • Thesis: Lattice Point Counting through Fractal Geometry and Stationary Phase for Surfaces with Vanishing Curvature
  • Advisor: Krystal Taylor
• M.S. in Mathematics, The Ohio State University, 2017
• B.A., Cum Laude in “The Language of Mathematics”, New York University Gallatin School of Individualized Study, 2014

Recent Professional Experience

• The Ohio State University:
  • Imageomics Institute
    • Senior Data Scientist (November 2024 - Present)
    • Research Data Manager and Technology Coordinator (March 2023 - November 2024)
  • AI and Biodiversity Change (ABC) Global Center
    • Senior Data Scientist (November 2024 - Present)
    • Research Data Manager and Technology Coordinator (June 2024 - November 2024)
• Erdős Institute Mentor (Fall 2022, Spring and May 2024)
  • Advised participants in project groups on the data science lifecycle for their projects.
  • Acted as a sounding-board for their ideas and general resource to help them succeed.
  • All seven project groups I advised finished, and two of four placed in the Top 5 in Fall 2022.

Selected Projects (pre-2023)

• Asymmetric Cloning to Eavesdrop on BB84 Protocol:
  • QuForce Innovation Fellow, (Mentor Alex Khan, April - August 2022)
    • 1st Place Demo
    • Worked with another mathematician and a physicist to determine the theoretical optimal strategy for asymmetric cloning on a quantum channel (minimizing disturbance while maximizing information gain).
    • Compared theoretical expectation to the experimental results from implementation of asymmetric phase-covariant cloning on IonQ’s 11-qubit quantum computer (utilizing the Qiskit SDK).
  • Independent Researcher, Continuing QuForce Project (August 2022 - March 2023)
    • Expanding our experimental investigation into the trade-off between information gain and detection when eavesdropping on quantum key distribution.
    • Exploring the impact of noise on our base fidelity rates through implementation on IonQ using Native Gates directly.
• Ph.D. Thesis Project: Lattice Points Close to the Heisenberg Norm, Advisor Prof. K. Taylor, OSU (September 2017 - May 2022)
  • Adapted technique used by Iosevich and Taylor (2011) to count lattice points on and near smooth surfaces to instead count lattice points on and near surfaces with vanishing curvature.
    • Removed the non-vanishing Gaussian curvature condition for similarly homogeneous objects defined by norms. The limitation lies in the decay of the Fourier transform of the surface measure.
    • Leveraged the geometry of Heisenberg norm balls to attain results despite vanishing curvature. This work is generalizable to similar objects (those with less homogenous dilations along one axis).
  • Utilized method to estimate the number of lattice points in and near the intersection of two surfaces.
• The Erdős Institute Boot Camp:
  • Topological Data Analysis Applied to Football (September - December 2021)
    • A Fall 2021 Top Project
    • Collaborated with two mathematicians and a research scientist on the NFL Big Data Bowl 2022 Kaggle Challenge.
    • Engineered predictive features by play-type to cluster into different strategies with UMAP and HDBSCAN.
    • Applied predictive modeling to each cluster to create a new metric for special teams play.
  • Predicting COVID Spread (September - December 2020)
    • Partnered with physics Ph.D. student to study COVID-19 spread at the county level in the United States as of December 2020 utilizing Random Forest and Nearest Neighbors Predictors (implemented in Python).
    • Compared responses to the pandemic across states by considering factors such as mask use, poverty levels, median age of the population, and population density in each county.

Recent Research and Performance Awards

Papers and Projects

• Best Student Paper Award for BioCLIP at IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR) 2024
• 1st Place: QuForce Demo Day (2022)
• Top Project: Erdős Institute Fall Boot Camp (2021)

Awards & Honors

• Nominated by OSU for the 2024 Council of Graduate Schools (CGS)/ProQuest Distinguished Dissertation Award in Mathematics, Physical Sciences and Engineering (Summer 2024)
• SIAM-NSF Early Career Travel Award (July 2024)
• Graduate Associate Performance Award (2021)
• Rhodus Graduate Fellowship (Autumn 2018 and 2019)

Selected Publications

• Elizabeth G. Campolongo, Yuan-Tang Chou, Ekaterina Govorkova, Wahid Bhimji, Wei-Lun Chao, Chris Harris, Shih-Chieh Hsu, Hilmar Lapp, Mark S. Neubauer, Josephine Namayanja, Aneesh Subramanian, Philip Harris, Advaith Anand, David E. Carlyn, Subhankar Ghosh, Christopher Lawrence, Eric Moreno, Ryan Raikman, Jiaman Wu, et al. Building Machine Learning Challenges for Anomaly Detection in Science. (arXiv, March 2025).
• Maksim Kholiavchenko, Jenna Kline, Maksim Kukushkin, Otto Brookes, Sam Stevens, Isla Duporge, Alec Sheets, Reshma R. Babu, Namrata Banerji, Elizabeth Campolongo, Matthew Thompson, Nina Van Tiel, Jackson Miliko, Eduardo Bessa, Majid Mirmehdi, Thomas Schmid, Tanya Berger-Wolf, Daniel I. Rubenstein, Tilo Burghardt, Charles V. Stewart. Deep dive into KABR: a dataset for understanding ungulate behavior from in-situ drone video. Multimedia Tools and Applications (2024). https://doi.org/10.1007/s11042-024-20512-4.
• Brian Pigott, Elizabeth Campolongo, Hardik Routray, Alex Khan. Eavesdropping on the BB84 Protocol using Phase-Covariant Cloning: Experimental Results. (under review, arXiv, September 2024).
• Be open to unexpected opportunities. Work-life balance requires creativity, but it is worth the effort. Notices of the American Mathematical Society, Early Career Series (August 2024).
• Lattice Points Close to the Heisenberg Spheres, with K. Taylor, La Matematica, 2 (2023), no. 1, pp. 156–196.
• Lattice Point Counting through Fractal Geometry and Stationary Phase for Surfaces with Vanishing Curvature (Dissertation for Ph.D. in Mathematics, 2022).

Refereed Conference and Workshop Papers

• Arpita Chowdhury, Dipanjyoti Paul, Zheda Mai, Jianyang Gu, Ziheng Zhang, Kazi Sajeed Mehrab, Elizabeth G. Campolongo, Daniel Rubenstein, Charles V. Stewart, Anuj Karpatne, Tanya Berger-Wolf, Yu Su, Wei-Lun Chao. “PROMPT-CAM: A Simpler Interpretable Transformer for Fine-Grained Analysis” (arXiv Jan. 2025, CVPR 2025).
• Kazi Sajeed Mehrab, M. Maruf, Arka Daw, Harish Babu Manogaran, Abhilash Neog, Mridul Khurana, Bahadir Altintas, Yasin Bakis, Elizabeth G Campolongo, Matthew J Thompson, Xiaojun Wang, Hilmar Lapp, Wei-Lun Chao, Paula M. Mabee, Henry L. Bart Jr., Wasila Dahdul, Anuj Karpatne. “Fish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images” (arXiv, July 2024, CVPR 2025).
• Harish Babu Manogaran, M. Maruf, Arka Daw, Kazi Sajeed Mehrab, Caleb Patrick Charpentier, Josef C. Uyeda, Wasila Dahdul, Matthew J Thompson, Elizabeth G Campolongo, Kaiya L Provost, Paula M. Mabee, Hilmar Lapp, Anuj Karpatne. “What Do You See in Common? Learning Hierarchical Prototypes over Tree-of-Life to Discover Evolutionary Traits” (arXiv, September 2024, ICLR 2025).
• M. Maruf, Arka Daw, Kazi Sajeed Mehrab, Harish Babu Manogaran, Abhilash Neog, Medha Sawhney, Mridul Khurana, James P. Balhoff, Yasin Bakis, Bahadir Altintas, Matthew J. Thompson, Elizabeth G. Campolongo, Josef C. Uyeda, Hilmar Lapp, Henry L. Bart, Paula M. Mabee, Yu Su, Wei-Lun Chao, Charles Stewart, Tanya Berger-Wolf, Wasila Dahdul, Anuj Karpatne. “VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images”, 2024 Advances in Neural Information Processing Systems 37 (NeurIPS 2024) Datasets and Benchmarks Track, Vancouver, BC, Canada, Dec. 2024, pp.131035–131071.
• Samuel Stevens*, Jiaman Wu*, Matthew J. Thompson, Elizabeth G. Campolongo, Chan Hee Song, David Edward Carlyn, Li Dong, Wasila M. Dahdul, Charles Stewart, Tanya Berger-Wolf, Wei-Lun Chao, and Yu Su. “BioCLIP: A Vision Foundation Model for the Tree of Life”, 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR’24 Oral), Seattle, WA, June 2024, pp. 19412-19424. (*: Equal Contribution).
• M. Kholiavchenko, J. Kline, M. Ramirez, S. Stevens, A. Sheets, R. Ramesh Babu, N. Banerji, E. Campolongo, M. Thompson, N. Van Tiel, J. Miliko, E. Bessa, I. Duporge, T. Y. Berger-Wolf, D. Rubenstein, C. Stewart, “KABR: In-Situ Dataset for Kenyan Animal Behavior Recognition From Drone Videos”, 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops, Waikoloa, Hawaii, Jan. 2024, pp. 31–40.
• J. Kline, C. Stewart, T. Y. Berger-Wolf, M. Ramirez, S. Stevens, R. Ramesh Babu, N. Banerji, A. Sheets, S. Balasubramaniam, E. Campolongo, M. Thompson, C. V. Stewart, M. Kholiavchenko, D. I. Rubenstein, N. Van Tiel, J. Miliko , “A Framework for Autonomic Computing for In Situ Imageomics”, 2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS), Toronto, ON, Canada, 2023, pp. 11–16, doi: 10.1109/ACSOS58161.2023.00018.

Competition and Workshop Organization

• Beetles as Sentinel Taxa: Predicting drought conditions from NEON specimen imagery (Imageomics Challenge Lead), November 2024 - Present.
  • Part of larger HDR Institutes Scientific Modeling out of distribution (Scientific-Mood) ML Challenge: nsfhdr.org/mlchallenge-y2 (Lead Organizer).
• Anomaly Detection in Scientific Domains AAAI Workshop (Co-organizer, nsfhdr.org/AAAI-workshop), March 2025.
• Butterfly Hybrid Detection ML Challenge (Imageomics Challenge Lead), November 2023 - March 2024.
  • Part of larger HDR Institutes ML Anomaly Detection Challenge: nsfhdr.org/mlchallenge.
• Image Datapalooza, August 2023 (Co-organizer, site: imageomics.osu.edu/image-datapalooza-2023).

Selected Conferences, Workshops, and Talks

• ML Commons: NSF HDR ML Challenge (February 2025).
• FARR Conference Invited Speaker and AI Reproducibility Panelist (October 2024):
  • Contributed Talk: FAIR and Reproducible Data, Models, and Workflows in Imageomics.
• HDR Ecosystem Conference (September 2024):
  • Contributed Talk: Anomaly Detection: Hybrid Butterflies.
  • Poster Presentation: Imageomics: FAIR ML Products for Biological Knowledge Discovery.
• SIAM ED24 CP3 Session Chair, Contributed Talk: Andromeda 2.0: FAIR Exploration of High-Dimensional Data (July 2024).
• Imageomics All Hands Collaborator Day Poster Presentations and Demos (April 2024):
  • Imageomics: ML for Biological Knowledge Discovery.
  • Data Dashboard: Facilitating Data Exploration.
• NSF Research Infrastructure Workshop Poster Presentation: Imageomics: ML for Biological Knowledge Discovery. (March 2024).
• HDR Ecosystem Conference (presented by co-authors in October 2023):
  • Contributed Talk: FAIR and Reproducible Data, Models, and Workflows in Imageomics.
  • Poster Presentation: Data Dashboard: Facilitating Data Exploration.
• APS March Meeting Contributed Talk: Asymmetric Cloning to Eavesdrop on BB84 Protocol (March 2023).
• miniMAGNTS Poster Presentation: Lattice Point Counting: From Gauss Circle Problem to Heisenberg Norms (August 2021).
• SIAM Annual Meeting, AWM Workshop Poster Presentation: Lattice Point Counting: From Gauss Circle Problem to Heisenberg Norms (July 2021).
• Hausdorff Trimester Program at The Hausdorff Center for Mathematics, Universität Bonn:
  • Seminar Series: Harmonic Analysis From the Edge & Arithmetic Applications of Fourier Analysis (May-August 2021).
  • The Polynomial Method, Summer School (June 2021).
  • The Circle Method: Entering its Second Century, Summer School (June 2020–Postponed to May 2021).
• IEEE NAECON Presentation: A Tutorial on Topological Data Analysis for Big Data Analytics (July 2019).
• First Midwest Graduate Student Conference: Geometry and Topology meet Data Analysis and Machine Learning Poster Presentation: Performing Topological Data Analysis through the Ayasdi Platform (June 2019).
• INFORMS Symposium Presentation: Big Data Analysis with Topological Data Analysis (presented by co-author in October 2018).

Teaching

• Experiential Introduction to AI and Ecology Co-Lead Instructor (Academic Year 2024 - 2025)
• Data Training Workshop Lead Instructor (April 2024)

• Carpentries Git Training Co-Instructor (September 2023, August 2024, February 2024 & 2025)

• Teaching Assistant for The Erdős Institute Boot Camp (May, September - December 2022)
  • Assisted students during group problem sessions, answering questions regarding technical and theoretical practices.
  • Ensured groups progressed at a reasonable rate, providing hints as necessary.
• Teaching Associate at BAMM: Beyond the Classroom Summer Camp, OSU (June 2021)
  • Evaluated middle and high school students’ submissions as they discovered the math behind magic tricks.
  • Assisted students in Zoom help sessions and led afternoon discussions.
• Recitation Instructor, Tutor, and Grader, OSU (August 2016 - May 2022)
  • Graded Intro Analysis I & II, Analysis Overview, honors and regular sections of Foundations of Higher Mathematics (proof writing course), and Linear Algebra.
  • Contributed to creation of content for college pre-calculus Ximera textbook.
  • Taught recitation sections of Calculus I.
  • Tutored Calculus I & II, Calculus for Engineers, Business Calculus, and College Algebra.
• Tutoring Undergraduate Level (September 2013 - May 2014)
  • Tutored college student in discrete mathematics, linear algebra, and programming (C++).
  • Two to three days a week in three-hour sessions.
• Junior Faculty at HCSSiM, Hampshire College (June - August 2012)
  • Taught algebraic topics such as modular arithmetic and basic group theory in first main course; taught lessons on fractals and random walks (eg., absorbing Markov chains) in chaos theory course.
  • Taught two ``minis” (seven day, hour-long) on cryptology: pen and paper ciphers, then modern cryptology.
  • Gave an hour-long, program-wide lecture on cracking the Enigma.
  • Assisted students with assigned problems and course material during daily three-hour problem sessions.

Skills

• Data Analytics and Machine Learning: Python (Pandas, Polars, NumPy, scikit-learn, matplotlib, Plotly), Toplogical Data Analysis (UMAP, HDBSCAN), Qiskit.
• Computer Languages: Python, LaTeX, Git, Java, basic HTML, Elm, and bash/zsh programming.
• Tools/Platforms: Jupyter Notebook, GitHub, Microsoft Office Suite, iWork, Zoom, Linux, Macs, and PCs.
• Foreign Languages: Functionally proficient in Spanish and Italian. Arabic (beginner), French (reading).
• Public Speaking: Twelve years of theatre performance and training, including Off-Broadway.