**Office:** Room M234

**Phone:** +31 20 592 4210

**Email:** dadush AT cwi DOT nl

I am currently a tenured researcher at CWI in the Networks & Optimization group. Previously, I was a Simons Postdoctoral Fellow for 2 years at the Courant Institute of Mathematical Sciences at New York University. I completed my PhD in 2012 within the ACO (Algorithms, Combinatorics, and Optimization) program at Georgia Tech under Santosh Vempala (Professor of Computer Science).

- I was awarded an ERC Starting grant for the project "Towards a Quantitative Theory of Integer Programming" (see link for the press release). I am now looking for one Postdoc. Please see the official opening here: Postdoc Position. I will review applications starting November 19th, however the application process will remain open until the position are filled.

- I am a co-organizer for the workshop Lattices: Geometry, Algorithms and Hardness at the Simons Institute, Feb 18-21, 2020.
- I am on the committee of the Mixed Integer Programming (MIP 2019) workshop at MIT, July 11-15, 2019.
- I organized a workshop on Discrepancy Theory and Integer Programming, June 11-15 at CWI. Slides for the talks are available on the website.

- Ph.D.:
- Sander Borst.

- Samarth Tiwari.

- Huck Bennett (joint with Chee Yap). Graduated August 2017. Currently Postdoc @ University of Michigan.

- M.Sc.:
- Sophie Huiberts. Graduated December 2017.

- Interns:
- Huck Bennett . Fall 2016.
- Venkata Gandikota . Fall 2016.

- Fall 2019: Continuous Optimization. Mastermath website.
- Spring 2019: Geometric Functional Analysis and its Applications. Co-Instructor: Jop Briet. Mastermath announcement. Course webpage: link.
- Spring 2018: Introduction to Lattice Algorithms and Cryptography. Co-Instructor: Leo Ducas. Mastermath announcement. Course webpage: link.
- Spring 2017: Advanced Topics in Semidefinite Programming. Co-Instructor: Nikhil Bansal. Mastermath announcement. Course webpage: link.
- Spring 2016: Algorithms Beyond the Worst-Case. Co-Instructor: Bodo Monthey. Mastermath Announcement. Course webpage: link.
- Spring 2013: Lattices, Convexity and Algorithms. Co-Instructor: Oded Regev. New York University (graduate: CSCI-GA 3033-013).

Please visit the seminar website for the current schedule.

Feel free to drop me a line if you would like to give a talk.

Here's my curriculum vitae (CV).

- Lattice Algorithms and the Geometry of Numbers
- Linear Programming and the Simplex Method
- Extended Formulations
- Algorithms for Integer Programming, Cutting Plane Methods
- Convex Optimization
- Asymptotic Convex Geometry (properties of convex bodies as dimension tends to infinity)

- NWO Veni Grant: New Frontiers in Lattice Algorithms and Design, 2015 - 2018.

- A.W. Tucker Prize for Best Thesis in Mathematical Optimization, 2015. Citation: link.
- Informs Optimization Society Student Paper Prize, 2011.
- Informs JFIG Paper Competition, Finalist, 2010 & 2011.

- A Scaling-Invariant Algorithm for
Linear Programming whose Running Time Depends only on the Constraint Matrix

D. Dadush, S. Huiberts, B. Natura, L. Végh. Manuscript, 2019.

- Smoothed Analysis of the Simplex Method

D. Dadush, S. Huiberts. Invited chapter in Beyond Worst Case Analysis (editor Tim Roughgarden), 2020+.

- On Approximating the Covering Radius and
Finding Dense Lattice Subspaces (slides)

D. Dadush. STOC 2019. - AWGN-Goodness is Enough: Capacity-Achieving Lattice Codes based on Dithered Probabilistic Shaping

A. Campello, D. Dadush, C. Long. IEEE Transactions on Information Theory, Vol. 65(3), 1961 - 1971, 2019. - Balancing Vectors in Any Norm

D. Dadush, S. Nikolov, K. Talwar, N. Tomczak-Jaegermann. FOCS 2018. - A Friendly Smoothed Analysis of the
Simplex Method

D. Dadush, S. Huiberts. STOC 2018 (invited to SICOMP special edition). - The Gram-Schmidt Walk: A Cure for
the Banaszczyk Blues

N. Bansal, D. Dadush, S. Garg, S. Lovett. Theory of Computing, Vol. 15, Art. 21, 1-27, 2019. Preliminary version in STOC 2018. - Lattice based Locality Sensitive Hashing
is Optimal (extended abstract)

C. Chandrasekaran, D. Dadush, E. Grigorescu, V. Gandikota. ITCS 2018. - Geometric Rescaling Algorithms
for Submodular Function Minimization

D. Dadush, L. Végh, G. Zambelli. Accepted in Mathematics of Operations Research, 2020. Preliminary version in SODA 2018. - Fast, Deterministic and Sparse
Dimensionality Reduction

D. Dadush, C. Guzman, N. Olver. SODA 2018. - Rescaling Algorithms for Linear
Conic Feasibility

D. Dadush, L. Végh, G. Zambelli. Accepted in Mathematics of Operations Research, 2019. - Towards Strong Reverse Minkowski Type Inequalities for Lattices

D. Dadush, O. Regev. FOCS 2016. - An Algorithm for the Komlós
Conjecture Matching Banaszczyk's Bound

N. Bansal, D. Dadush, S. Garg. SIAM Journal of Computing, Vol. 48(2), 534-553, 2019. Special edition for FOCS 2016. - Towards a Constructive Version of Banaszczyk's Vector Balancing Theorem

D. Dadush, S. Garg, S. Lovett, A. Nikolov. Theory of Computing, Vol. 12, Art. 2, 1-58, 2019. Special edition for APPROX-RANDOM 2016. - On the Lattice Distortion Problem

H. Bennett, D. Dadush, N. Stephens-Davidowitz. ESA 2016. - Rescaled Coordinate Descent Methods for Linear Programming

D. Dadush, L. Végh, G. Zambelli. IPCO 2016. - Solving the Closest Vector Problem
in 2^n Time: The Discrete Gaussian Strikes Again! (slides)

D. Aggarwal, D. Dadush, N. Stephens-Davidowitz. FOCS 2015. - Solving the Shortest Vector Problem
in 2^n Time via Discrete Gaussian Sampling (slides)

D. Aggarwal, D. Dadush, O. Regev, N. Stephens-Davidowitz. STOC 2015. - Faster Deterministic Volume Estimation in
the Oracle Model via Thin Lattice Coverings (slides)

D. Dadush. SOCG 2015. - On the Shadow Simplex Method for Curved
Polyhedra (slides)

D. Dadush, N. Hähnle. Discrete & Computational Geometry, 56, 882-909, 2016.

Preliminary version in SOCG 2015. - Short Paths on the Voronoi Graph and the Closest
Vector Problem with Preprocessing (slides)

N. Bonifas, D. Dadush. SODA 2015. - On the Closest Vector Problem with
a Distance Guarantee

D. Dadush, O. Regev, N. Stephens-Davidowitz. CCC 2014. - On the existence of 0/1 polytopes with
High Semidefinite Extension Complexity (slides)

J. Briet, D. Dadush, S. Pokutta. Mathematical Programming, Series B, 153, 179-199, 2015.

Preliminary version in ESA 2013. - On the Lattice Smoothing Parameter
Problem (slides)

K.M. Chung, D. Dadush, F.H. Liu, C. Peikert. CCC 2013. - Lattice Sparsification and the
Approximate Closest Vector Problem (slides)

D. Dadush, G. Kun. Theory of Computing, Vol. 12, Art. 2, 1-34, 2016. Preliminary version in SODA 2013. - Algorithms for the Densest Sublattice
Problem

D. Dadush, D. Micciancio. SODA 2013. - Near-Optimal Deterministic Algorithms
for Volume Computation via M-Ellipsoids (slides)

D. Dadush, S. Vempala. Proceedings of the National Academy of Sciences, 110, 19237-19245, 2013. - Unconditional Differentially Private
Mechanisms for Linear Queries

A. Bhaskara, D. Dadush, R. Krishnaswamy, K. Talwar. STOC 2012. - A Randomized Sieving Algorithm for Approximate Integer Programming
(slides)

D. Dadush. Algorithmica, 70, 208-244, 2014.

Preliminary version in LATIN 2012. - Deterministic Construction of an Approximate M-Ellipsoid and its
Applications to Derandomizing Lattice Algorithms

D. Dadush, S. Vempala. SODA 2012. - On the Chvátal-Gomory Closure of a
Compact Convex Set (slides)

D. Dadush, S.S. Dey, J.P. Vielma. Mathematical Programming, Series B, 145, 1, 327-348, 2014.

Preliminary version in IPCO 2011.

Optimization Society Student Paper Prize, 2011. - The Split Closure of a Strictly Convex Body

D. Dadush, S.S. Dey, J.P. Vielma. Operations Research Letters, vol. 39, p. 121-126, 2011. - The Chvátal-Gomory Closure of a Strictly Convex Body

D. Dadush, S.S. Dey, J.P. Vielma. Mathematics of Operations Research, vol. 36, p. 227-239, 2011.

INFORMS JFIG Paper Competition Finalist. - Enumerative Lattice Algorithms in Any
Norm via M-Ellipsoid Coverings (slides)

D. Dadush, C. Peikert, S. Vempala. FOCS 2011. - Thin Partitions: Isoperimetric Inequalities and a Sampling Algorithm for Star Shaped Bodies

D. Dadush, C. Chandresekaran, S. Vempala. SODA 2010.