Mayank Goswami

Algorithms, Geometry and Machine Learning

Associate Professor

Department of Computer Science
CUNY Queens College & CUNY Graduate Center
Science Building A202
65-30 Kissena Blvd, Flushing, NY 11367
Email: mayank.goswami@qc.cuny.edu

Hiring: Ph.D. and Postdoc Positions available! Requirements for the Ph.D. position are a strong mathematical foundation and knowledge of algorithm design. Requirements for the Postdoctoral position are a strong record of publication in top theoretical CS or ML venues. Email me if interested.

Short Bio: I received my Ph.D. from the Applied Mathematics and Statistics at the Stony Brook University, New York. My advisors were Joe Mitchell and David Gu. Thereafter, I was a researcher at the Max-Planck Institute for Informatics in Germany, in the Algorithms and Complexity group headed by Kurt Mehlhorn. I received my Bachelors in Mathematics (B.Math.) from the Indian Statistical Institute, Bangalore, India.

Research Interests:

  1. Algorithms - sorting, searching, binary search trees, succinct data structures and variants of Bloom filters, graph problems, I/O efficient algorithms, lower bounds.
  2. Computational geometry and algorithms for geometric databases.
  3. Theoretical machine learning - removing noisy labels, generalization performance.
  4. Conformal geometry, Teichmuller theory, and harmonic measure.

I hosted the Fall Workshop on Computational Geometry (FWCG) in October 2018. Here is the webpage.

I organize the Computer Science Seminar, Q4C (Queens College CS Colloquium)

Community Service
  • Program Committees: SODA 2026, ISAAC 2025, FWCG 2024, 2018, 2017, 2016, ICPP 2017
  • Organization: Hosted FWCG 2025 and 2018 at CUNY.
Publications

Reverse-chronologically ordered. Authors are ordered alphabetically by convention in theory. Uses of the files linked below are subject to copyrights of respective publishers. Please check before use.

Peer-Reviewed Conferences

  1. New!! Waldo Gálvez, Mayank Goswami, Arturo Merino, GiBeom Park, Meng-Tsung Tsai, Victor Verdugo
    A Framework for the Design of Efficient Diversification Algorithms to NP-Hard Problems
  2. New!! Waldo Gálvez, Mayank Goswami, Arturo Merino, GiBeom Park, Meng-Tsung Tsai
    Computing Diverse and Nice Triangulations
    Proc. of the 25th International Symposium on Fundamentals of Computation Theory, (FCT), September 2025
  3. New!! V. Ashvinkumar, R. Chowdury, J. Gao, M. Goswami, J.S.B. Mitchell, V. Polishchuk
    Vantage Point Selection Algorithms for Bottleneck Capacity Estimation
    Proc of the 19th Algorithms and Data Structures Symposium (WADS), August 2025
  4. New!! J. Yao, L. Yi, M. Goswami, C. Chen
    A Theoretical Study of Neural Network Expressive Power via Manifold Topology
    Transactions on Machine Learning Research (TMLR), 2025
  5. New!! P. Austrin, I.O. Bercea, M. Goswami, N. Limaye, A. Srinivasan
    Algorithms for the Diverse-k-SAT problem: the geometry of satisfying assignments
    Proc of the 52nd EATCS International Colloquium on Automata, Languages and Programming (ICALP), July 2025
  6. M. Goswami, R. Jacob
    On Instance-Optimal Algorithms for a Generalization of Nuts and Bolts and Generalized Sorting
    Proc. Of the 27th International Conference on Approximation Algorithms for Combinatorial Optimization (APPROX), August 2024
  7. M. Goswami, R. Jacob
    An Algorithm for Bichromatic Sorting with Polylog Competitive Ratio
    Proc. Of the 15th Innovations in Theoretical Computer Science (ITCS), January 2024
  8. S. Zheng, Y. Zhang, L. Pang, W. Lyu, M. Goswami, A. Schneider, Y. Nevmyvaka, H. Ling, C. Chen
    On the Existence of a Trojaned Twin Model
    BANDS Workshop at the 11th International Conference on Learning Representations (ICLR), May 2023
  9. J. Yao, Y. Zhang, S. Zheng, M. Goswami, P. Prasanna, C. Chen
    Learning to Segment from Noisy Annotations: A Spatial Correction Approach
    The 11th International Conference on Learning Representations (ICLR), May 2023
  10. Omrit Filtser, Mayank Goswami, Joseph Mitchell, Valentin Polishchuk
    On Flipping the Frechet Distance
    Proc. of the 14th Innovations in Theoretical Computer Science (ITCS), January 2023
  11. P. Cesaretti, M.N. Bhat, M. Goswami and P. Pandey
    Distance and Time Sensitive Filters for Similarity Search in Trajectory Datasets
    Proc. of the SIAM Symposium on Algorithmic Principles of Computer Systems (APOCS 23), January 2023
  12. J. Gao, M. Goswami, Karthik C. S., M.T. Tsai, S.Y. Tsai, H.T. Yang
    Obtaining Approximately Optimal and Diverse Solutions via Dispersion
    Proceedings of the 15th Latin American Theoretical Informatics Symposium (LATIN), November 2022
  13. D. Deingeniis, X. Zhou, W.M. Wong, Y. Nomura, M. Goswami
    The Impact of Maternal PTSD and Child Temperament on Child Behavioral Problems: An Interpretable Machine Learning Approach
    Presented at the 38th Annual Meeting of the International Society for Traumatic Stress Studies (ISTSS), November, 2022
  14. Y. Zhang, W. Zhang, S. Bald, V.P. Pingali, C. Chen, M. Goswami
    Stability of SGD: Tightness Analysis and Improved Bounds
    Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (UAI) August 2022
  15. W. Zhang, Y. Zhang, X. Hu, M. Goswami, C. Chen, D. Metaxas
    A Manifold View of Adversarial Risk
    Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022)
  16. S. Zheng, Y. Zhang, H. Wagner, M. Goswami, C. Chen
    Topological Detection of Trojaned Neural Networks
    Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS'21), December 2021.
  17. S. Zheng, P. Wu, Y. Zhang, M. Goswami, C. Chen, D. Metaxas
    Learning with Feature-Dependent Label Noise: A Progressive Approach
    Proc. of the 9th International Conference of Learning Representations (ICLR), 2021. (Spotlight).
  18. P. Wu, S. Zheng, M. Goswami, C. Chen, D. Metaxas
    A Topological Filter for Learning with Label Noise
    Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS'20), December 2020.
  19. M. Goswami, R. Jacob, R. Pagh
    On the I/O-Complexity of the k-nearest neighbors problem
    Proc. of the 2020 ACM SIGMOD/PODS (Principles of Database Systems) Conference (PODS'20), June 2020.
  20. S. Zheng, M. Goswami, P. Wu, A. Goswami, C. Chen, D. Metaxas
    Error-Bounded Correction of Noisy Labels
    Proc. of the 37th International Conference on Machine Learning (ICML'20), July 2020.
  21. E. Arkin, R. Das, J. Gao, M. Goswami, J.S.B. Mitchell, V. Polishchuk, C. Toth
    Cutting Polygons into Small Pieces with Chords: Laser-Based Localization
    Proc. of the European Symposium on Algorithms (ESA'20), July 2020.
  22. M. Bender, M. Goswami, D. Mededovic, P. Montes, K. Tsichlas
    Batched Predecessor and Sorting with Size-Priced Information in External Memory
    Proc. of the 14th Latin American Theoretical Informatics Symposium (LATIN'20), June 2020.
  23. P. Charlemsook, M. Goswami, L. Kozma, K. Mehlhorn, T. Saranurak
    Multi-finger binary search trees
    29th International Symposium on Algorithms and Computation (ISAAC), December 2018.
  24. M. Astefanoaei, P. Cesaretti, P. Katsikouli, M. Goswami, R. Sarkar
    Multi-resolution sketches and locality sensitive hashing for fast trajectory processing
    Proceedings of the 26th International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2018).
  25. M. A. Bender, M. Farach-Colton, M. Goswami, R. Johnson, S. McCauley, S. Singh
    Bloom Filters, Adaptivity and the Dictionary Problem
    Proc. of the 59th Annual IEEE Symposium on Foundations of Computer Science (FOCS), October 2018.
  26. M. Goswami, D. Medjedovic, E. Mekic, P. Pandey
    Buffered Count-Min Sketch on SSD: Theory and Experiments
    Proc. of the 26th European Symposium on Algorithms (ESA), August 2018.
  27. K.S. Liu, Tyler Mayer, H.T. Yang, E. Arkin, J. Gao, M. Goswami, M.P. Johnson, N. Kumar, S. Lin
    Joint Sensing Duty Cycle Scheduling For Heterogenous Coverage Guarantee
    Proc. of the 36th Annual IEEE Conference on Computer Communications 2017 (INFOCOMM'17).
  28. M. Goswami, R. Pagh, F. Silvestri, J. Sivertsen
    Distance Sensitive Bloom Filters without False Negatives
    Proc. of the 28th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA'17), January, 2017.
  29. P. Afshani, M. Bender, M. Farach-Colton, J. Fineman, M. Goswami, M.T. Tsai
    Cross Referencing and the Limits of Write Optimization
    Proc. of the 28th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA'17), January, 2017.
  30. P. Chalermsook, M. Goswami, L. Kozma, K. Mehlhorn, T. Saranurak
    Pattern-Avoiding Access in Binary Search Trees
    Symposium on Foundations of Computer Science (FOCS'15), October 2015.
  31. J. Gao, M. Goswami
    Medial Axis Based Routing has Constant Load Balancing Factor
    European Symposium on Algorithms (ESA'15), September 2015.
  32. P. Chalermsook, M. Goswami, L. Kozma, K. Mehlhorn, T. Saranurak
    Self-Adjusting Binary Search Trees: What Makes Them Tick?
    European Symposium on Algorithms (ESA'15), September 2015.
  33. M. Goswami, S. Li, J. Weng, J. Gao, X. Gu, E. Saucan
    Space Filling Curves for 3D Sensor Networks with Complex Topologys
    Proc. of the 27th Canadian Conference on Computational Geometry (CCCG'15), August 2015.
  34. P.Charlemsook, M. Goswami, L. Kozma, K. Mehlhorn, T. Saranurak
    Greedy is an almost optimal deque
    Proc. of the Algorithms and Data Structures Symposium (WADS'15), August, 2015.
  35. M. Goswami, X. Gu, V. Pingali, G. Telang
    Computing Teichmüller Maps between Polygons
    Proc. of the 31st International Symposium on Computational Geometry (SoCG'15), June, 2015. Invited to Journal of Computational Geometry (SoCG15 special issue).
  36. M. Goswami, A. Grønlund, K.G. Larsen, R. Pagh
    Approximate Range Emptiness in Constant Time and Optimal Space
    Proc. of the 26th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA'15), January, 2015.
  37. A. Bishnu, S. Desai, A. Ghosh, M. Goswami, S. Paul
    Uniformity of point samples in metric spaces using gap ratio
    Proc. of the 12th Annual Conference on Theory and Applications of Models of Computation (TAMC'15), May 2015.
  38. M. Bender, M. Farach-Colton, M. Goswami, D. Medjedovic, P. Montes, M.T. Tsai
    The Batched Predecessor Problem in External Memory
    Proc. of the European Symposium on Algorithms (ESA'14), September, 2014.
  39. M. Goswami, C.C. Ni, X. Ban, V. Pingali, J. Gao, X. Gu
    Load Balanced Short Path Routing in Large-Scale Wireless Networks Using Area-Preserving Maps
    proc. of the 15th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc'14), August, 2014.
  40. W. Zeng, M. Goswami, X. Gu, F. Luo
    Geometric Registration Based on Distortion Estimation
    Proc. of the International Conference on Computer Vision (ICCV'13), December, 2013.
  41. X. Ban, M. Goswami, W. Zeng, X. Gu, J. Gao
    Topology Dependent Space Filling Curves for Sensor Networks and Applications
    Proc. of the 32nd Annual IEEE Conference on Computer Communications (INFOCOM'13), April, 2013.
  42. R. Shi, M. Goswami, J. Gao, X. Gu
    Is Random Walk Truly Memoryless - Traffic analysis and Source Location Privacy Under Random Walk
    Proc. of the 32nd Annual IEEE Conference on Computer Communications (INFOCOM'13), April, 2013.
  43. R. Jiang, X. Ban, M. Goswami, W. Zeng, J. Gao, X. Gu
    Exploration of Path Space using Sensor Network Geometry
    Proc. of the 10th International Symposium on Information Processing in Sensor Networks (IPSN), 49-60, April, 2011.
Grants

My research is supported thanks to the following sponsors.

  • National Science Foundation: AF: Small: RUI: Understanding the Geometry and Diversity of Solutions - Algorithms for Generating Diverse Solutions in Optimization.
  • National Science Foundation - AF:Small: RUI: Towards resolving the dynamic optimality conjecture. Award ID: 1910873.
  • National Science Foundation CRII: AF: RUI: Faster and Cache-Efficient Similarity Filters and Searches for Big Data (Award Id : 1755791).
  • CUNY Collaborative Open Educational Resources in STEM (COERS) Program: Project-based pedagogical approach in introductory C++ courses. Co-PI (along with Daniel Garbin and Kwang Hyun Kim).
  • PSC CUNY Cycles 48 and 49 award (type B).

Journal

  1. A. Bishnu, S. Desai, A. Ghosh, M. Goswami, S. Paul
    Uniformity of Point Samples in Metric Spaces Using Gap Ratio
    SIAM J. Discret. Math. 31(3): 2138-2171 (2017).
  2. W. Zhang, Y. Zhang, X. Hu, Y. Yao, M. Goswami, C. Chen, D. Metaxas
    Manifold-driven decomposition for adversarial robustness
    Frontiers Comput. Sci. 5 (2023).
  3. O. Flitser, M. Goswami, J.S.B. Mitchell, V. Polishchuk
    On Flipping the Fréchet Distance
    Algorithmica (2024).
  4. M. Goswami, X. Gu, V. Pingali, G. Telang
    Computing Teichmüller Maps between Polygons
    Journal of Foundations of Computational Mathematics (JoFOCM).

Workshops

  1. Omrit Filtser, Mayank Goswami, Joseph S.B. Mitchell and Valentin Polishchuk
    On Flipping the Frechet Distance
    30th Annual Fall Workshop on Computational Geometry (FWCG 2022), October, 2022
  2. Madhav Narayn Bhat, Paul Cesaretti, Mayank Goswami and Prashant Pandey
    Distance and Time Sensitive Filters for Similarity Search in Trajectory Datasets
    30th Annual Fall Workshop on Computational Geometry (FWCG 2022), October, 2022
  3. Jie Gao, Mayank Goswami, Karthik C.S., Meng-Tsung Tsai, Shih-Yu Tsai and Hao-Tsung Yang
    Obtaining Approximately Optimal and Diverse Solutions via Dispersion
    30th Annual Fall Workshop on Computational Geometry (FWCG 2022), October, 2022
  4. M. Astefanoaei, P. Katsikouli, M. Goswami, R. Sarkar
    Lightweight Sketches for Mining Trajectory Data
    The 27th Fall Workshop on Computational Geometry (FWCG), October 2017.
  5. K.S. Liu, T. Mayer, H.T. Yang, E. Arkin, J. Gao, M. Goswami, M.P. Johnson, N. Kumar, S. Lin
    Joint Sensing Duty Cycle Scheduling for Heterogeneous Coverage Guarantee
    The 26th Fall Workshop on Computational Geometry (FWCG), October 2016.
  6. E. Arkin, P. Brass, R. Das, J. Gao, M. Goswami, J.S.B. Mitchell, V. Polishchuk, C. D. Toth
    Optimal Cutting of a Polygon by Lasers
    The 26th Fall Workshop on Computational Geometry (FWCG), October 2016.
  7. M. Bender, M. Goswami, D. Medjedovic, P. Arango
    The I/O complexity of sorting with two key lengths
    Workshop on Massive Data Algorithmics (MASSIVE), 2013.
Talks
  1. Algorithms for Generating Diverse Solutions to SAT, Fine-grained and Parameterized Complexity Today (FPcT) at National University of Singapore, June 2025.
  2. Applications of Conformal and Quasiconformal Maps, Tata Institute of Fundamental Research-Centre for Applicable Mathematics (TIFR-CAM), Bangalore, India, December 2024.
  3. Finding Diverse Triangulations and Geometric Knapsacks, NYU Courant Geometry Seminar, April 2024.
  4. On Instance Optimal Algorithms for Sorting Nuts and Bolts and Sorting with Priced Information, University of Wroclaw, Poland, August 2024.
  5. Finding Diverse Triangulations and Geometric Knapsacks, University of Edinburgh. Scotland UK, September 2024.
  6. Applications of Conformal and Quasiconformal Maps, Universidad Nacional Autonoma de Mexico, Oaxaca, Mexico, August 2023.
  7. On Flipping the Frechet Distance, ITCS, Simons Institute for Computing, Berkeley. January 2023.
  8. Universal Sorting: Finding a DAG with priced comparisons, Rutgers Theory Seminar, December 2022.
  9. How to stay socially distant: a geometric approach, NYU Courant Geometry Seminar, February 2021.
  10. On the I/O-Complexity of the K-Nearest Neighbors Problem, Principles of Database Systems (PODS), June 2020.
  11. Recent Progress on the Dynamic Optimality Conjecture, NYC Discrete Geometry Seminar, April 2019.
  12. Computing extremal quasiconformal mapping, SUNY Binghamton, April 2019.
  13. Multi-finger binary search trees, International Symposium on Algorithms and Computation (ISAAC), Jiaoxi, Taiwan, December 2018.
  14. On Clairvoyance in Binary Search Trees: Recent Progress on the Dynamic Optimality Conjecture, University of Padova, Italy, September 2018.
  15. Distance-sensitive Bloom Filters, University of Edinburgh, August 2017.
  16. Medial axis based routing has constant load balancing factor, Courant Geometry Seminar, New York University, November 2016.
  17. Computing Teichmuller Maps, University of Washington at Seattle, and City University of New York, October 2015.
  18. Medial axis based routing has constant load balancing factor, European Symposium on Algorithms, Patras (ESA'15).
  19. Tight lower bounds for approximate range emptiness, Summer School on Lower Bounds, Prague, June 2015.
  20. Computing Teichmuller Maps between Polygons, Symposium on Computational Geometry, Eindhoven (SoCG'15).
  21. Approximate Range Emptiness in Constant Time and Optimal Space, Symposium on Discrete Algorithms, San Diego (SODA'15).
  22. Load Balancing Using Area-Preserving Maps, International Symposium on Mobile Ad Hoc Networking and Computing, Philadelphia (MobiHoc'14).
  23. Computing Teichmuller Maps between Polygons, Courant Geometry Seminar, New York University, September 2014.
  24. Approximate Range Emptiness in Constant Time and Optimal Space, CG Group (organized by Joe Mitchell), Stony Brook University, August 2014.
  25. Computing Teichmuller maps and connections to Tropical Geometry, Oberseminar (organized by Hannah Markwig), Department of Mathematics at University of Saarland, July 2014.
  26. Geometric Registration Based on Distortion Estimation, International Conference on Computer Vision, Sydney (ICCV'13).
  27. The I/O complexity of sorting with two key lengths, Max-Planck Institute for Informatics, October 2013.
  28. Topology Dependent Space Filling Curves for Sensor Networks and Applications, International Conference on Computer Communications, Turin, Italy (INFOCOM'13).
  29. Is Random Walk Truly Memoryless - Traffic analysis and Source Location Privacy Under Random Walk, International Conference on Computer Communications, Turin, Italy (INFOCOM'13).
Students
  • Paul Cesaretti (2018-present)
  • Rakesh Ravindran (2018-2020, now at MongoDB)
  • Sammy Bald (2018-2021, now at Meta)
  • Xinglong Zhou (2020-present)
  • GiBeom Park (2023-present)
  • Xinying Chyn (2024-present)
Teachings
  • Spring 2025 - Great Ideas in Algorithms (381/780), Design & Analysis Algorithms (323/700), Algorithms for Big Data (328/780)
  • Computer Science Colloquium Course, Spring 2023, Fall 2023, Spring 2024.
  • Fall 2022 - Algorithms for Big Data (381/780), Design & Analysis Algorithms (323/700).
  • Spring 2021 - Algorithms for Big Data (381/780), Design and Analysis of Algorithms (323/700).
  • Fall 2020 - Algorithms for Big Data (381/780), Design and Analysis of Algorithms (323/700), Queens College, and Algorithms for Big Data (80100), Graduate Center.
  • Fall 2019 - Algorithms for Big Data (381/780.
  • Spring 2019 - Algorithms for Big Data (381/780), Design and Analysis of Algorithms (323/700), Queens College, and Analysis of alogrithms (70010), Graduate Center.
  • Fall 2018 - Algorithms for Big Data (381/780), Design and Analysis of Algorithms (323/700).
  • Spring 2018 - Algorithms for Big Data (381/780), Design and Analysis of Algorithms (323/700).
  • Fall 2017 - Discrete Structures (220), Design and Analysis of Algorithms (323/700).
  • Spring 2017 - Discrete Structures (220), Design and Analysis of Algorithms (323/700), Approximation Algorithms (381/780), Queens College, and Modern Approximation Algorithms (83020), Graduate Center.
  • Fall 2016 - Discrete Structures (220), Queens College, CUNY. Approximation Algorithms (381/780)
  • Approximation Algorithms, Fall 2015, Max-Planck Institute for Informatics.
  • Efficient Data Structures, Summer 2014, Max-Planck Institute for Informatics.
  • Applied Calculus, Fall 2008, Spring 2009, Stony Brook University.