Every entry.

887% revenue acceleration through repeatable forward-deployed engagement model.

• → FDE feedback loop ->

Joined Benmore as Employee #2 — Forward Deployed Strategist & Engineer. Embedded into client engineering teams, scoped systems end-to-end, and shipped production code from day one.

• Onboarded the first ten clients across SaaS, healthcare, and consumer verticals.
• Authored the Benmore Foundry CLI — internal orchestration layer for SMB AI consulting engagements.
• Cross-stack: Stripe, Django, Next.js, FastAPI, React Native, plus Claude Code skill systems.

PythonTyperDjangoFastAPINext.jsReact NativeStripeClaude Code

• → Experience & work ->
• → Why FDE ->

Presented "Spatial-DINO: Self Supervised, Annotation-Free 3D Modeling - Seeing is Believing" at the Kirchhausen Lab on July 15, 2025. Walked the lab through the problem statement (no general segmentation + tracking model for LLSM volumes across endosomes, viruses, mitochondria, clathrin-coated pits, nuclei, apilmods), the 3D student/teacher ViT design, KMeans content-aware cropping, NoPE, the streaming encoder, and the downstream-task benchmarks beating the prior Betzig-led approach.

• → BioArxiv preprint
• → SpatialDINO lessons ->

Designed and trained a 3D self-supervised vision transformer for label-free segmentation and tracking of subcellular dynamics in lattice light-sheet microscopy — pre-trained on 2.4 TB / 180k volumes across 24 A100s. Beat a prior approach co-led by Nobel laureate Eric Betzig on downstream evaluation.

• Adapted DINO-style self-supervised contrastive learning into 3D — student/teacher ViTs over LLSM volumes with native 3D iBOT block masking.
• Introduced KMeans content-aware 3D cropping, no-positional-encoding 3D ViTs (NoPE), and a 3D adaptation of SINDER for singular-defect repair.
• Built a streaming encoder with token-store + online softmax for full-volume inference at million-token sequence lengths.
• Beat the prior SOTA — including the Nobel-laureate-led approach — on downstream subcellular structure prediction.
• Released as a BioRxiv preprint, first-author; engineering log at /writing/spatialdino-lessons.

PyTorchDINO3D ViTSelf-Supervised LearningLLSMDDPTriton

• → BioArxiv preprint
• → SpatialDINO lessons ->
• → View papers ->

ML researcher at Harvard Medical School applying 3D vision transformers to lattice light-sheet microscopy. The lab images live-cell subcellular dynamics at ~3 nm; my job was to make the resulting 4D volumes interpretable at scale.

• Trained on multi-node DGX clusters: A100 / H100, NVLink intra-node, Infiniband inter-node, RAID + NVMe storage tier.
• PyTorch DDP with bf16 mixed precision and activation checkpointing to fit large 3D ViTs.
• Diagnosed a Rendezvous (RDZV) backend issue affecting Infiniband multi-node training — filed PyTorch issue #144779.

PyTorchDDPCUDAInfinibandNCCLDGXLLSM3D ViT

• → View research ->
• → PyTorch #144779
• → Kirchhausen Lab profile
• → Harvard ID (PDF)

BA in Math & CS, MS in CS, completed in four years.

• → BA degree (PDF)
• → MS degree (PDF)
• → Graduation post (LinkedIn)

Top mathematics undergraduate award at BU.

BU Master's thesis: dynamic checkpointing for Apache Flink. Static checkpoint intervals are a tax in idle periods and a stall during bursts; I built a controller that adapted cadence from live backpressure signals.

• Instrumented Flink JobManager to surface per-operator backpressure ratios as a control signal.
• Adaptive checkpoint cadence: shorten when load is low, lengthen under sustained backpressure to avoid amplifying stalls.
• RocksDB state backend benchmarked against in-memory; quantified write-amplification tradeoffs.
• Validated on the NEXMARK streaming benchmark — measured tail-latency wins on bursty workloads.

JavaApache FlinkRocksDBNEXMARKJVM

Six classes spanning programming-language theory (CS 320 — OCaml interpreter from scratch), optimization (DS 522 — SGD variants & implicit SGD), cloud (CS 561 — PageRank on a synthetic mini-internet), graduate algorithms (CS 630 — Gale-Shapley average-case analysis over 331,776 instances, reservoir sampling), mathematical statistics (MA 582), and a liberal-arts elective (HI 151).

• CS 320: hand-written lexer, parser, and stack-machine evaluator for a BNF language in OCaml.
• DS 522: Adam / AMSGrad / RMSProp comparison, plus article evaluations of Reddi 2018 and Toulis 2016.
• CS 561: built a generated-HTML mini-internet and ran PageRank locally vs. on GCP.
• CS 630: 331,776-instance enumeration of Gale-Shapley to study average-case behavior.
• MA 582: rigorous graduate inference — MLE, sufficient statistics, MGF, asymptotics.

OCamlPythonRGCPOptimizationStatistics

• → CS 320 OCaml interpreter
• → DS 522 SGD variants
• → CS 561 PageRank
• → CS 630 Gale-Shapley
• → MA 582 Mathematical Statistics
• → All coursework

My first production-grade Rust. Built an Excel-side marketplace + a server-side ingestion pipeline that converted unstructured data (CSVs, JSON dumps, free-form Excel) into structured records flowing through NATS JetStreams. Spent the first two weeks deep in The Rust Book — the borrow checker forces you to internalize ownership, lifetimes, and Send/Sync before you can ship anything async.

• tokio + async-trait for concurrent I/O across hundreds of NATS subjects.
• NATS JetStream for at-least-once delivery, persistent streams, and replay.
• Merkle-tree POC (SHA-256 + canonical JSON hashing + sorted pairwise concat) for tamper-evident sync of records across the pipeline.
• Excel side: JavaScript Office Add-in scaffolded with Yeoman (`yo generator-office`).
• Generated TLS dev certificates with `office-addin-dev-certs`, trusted them in macOS Keychain, wired their paths into `nats.conf` so the add-in published over TLS.
• Borrow checker lessons: `&str` vs `String`, ownership over defensive `.clone()`, Send + 'static for futures.

Rusttokioasync-traitserdesha2NATS JetStreamYeomanJavaScriptOffice Add-ins

• → merkle_tree (Rust POC)
• → Merkle tree write-up
• → excel_connector (Yeoman + NATS)
• → The Rust Book

Built an internal ALS resource-discovery web app for clinicians and patient families. The whole product was scoped to Section 508 / WCAG 2.1 AA — accessibility was the bar, not an afterthought.

• React frontend wired to a Strapi headless CMS so non-technical staff could update content without a deploy.
• Swagger-documented REST API for self-service contributor onboarding.
• Section 508 / WCAG 2.1 AA compliance: keyboard-only nav, ARIA landmarks, focus-visible rings, sufficient contrast, skip links, screen-reader tested.
• Validated search and filter UX with real ALS clinicians; iterated on care-workflow ergonomics.

ReactStrapiSwagger / OpenAPINode.jsPostgreSQLWCAG 2.1Section 508

Invited talk to BU Hack4Impact on navigating a career in tech as an undergrad - the path from physics into CS + math, running VC and research internships in parallel, and how each step fed the next.

Distributed Systems (CS 350) — Raft consensus from scratch in Go, plus a MapReduce coordinator/worker. OOP & Design Patterns (CS 611) — Monsters & Heroes turn-based RPG plus a final Java Swing trading platform.

• CS 350: full Raft state machine with leader election, log replication, and snapshot install RPC.
• CS 350: MapReduce coordinator + worker with plugin-loaded map/reduce functions.
• CS 611: Monsters & Heroes — battle, market, inventory, 2D grid world.
• CS 611: group capstone trading platform with Java Swing GUI and singleton persistence.

GoRaftJavaOOPDesign Patterns

• → CS 350 deep dive
• → CS 611 Monsters & Heroes
• → CS 611 Trading System
• → All coursework

Admitted to BU's accelerated Bachelor's + Master's in Computer Science - finishes both degrees in four years instead of six.

Returned for a second summer doing deep diligence - embedded with a portfolio company on its EU expansion strategy. Pricing, GTM motion, regulatory fit, and competitive landscape across the European market.

Got a VC offer from MassMutual Ventures (Feb 2022) and a Summer 2022 VC internship offer from State Street. Turned both down to stay at Battery - the bar, the deal flow, and the people were the right place to keep learning.

Battery taught me VC end-to-end. Worked under Dallin Bills sourcing early-stage B2B software - learned the difference between vertical and horizontal SaaS, fintech investment theses (payments, infra, embedded, neobanks), and how Battery sized markets across verticals. Got fluent in the financial bar: Rule of 40, ARR growth vs. burn multiples, gross retention vs. logo churn vs. net dollar retention, magic number, and CAC payback. Sourced 3 deals to partner-meeting stage, including CarNow.

• → Battery Ventures
• → CarNow (Battery portfolio)
• → Michael Brown - GP
• → Dallin Bills (LinkedIn)

Sophomore fall: TA'd a 300-level Mechanics course. The following spring: kept a 20-hour work week while carrying an 18-credit load.

"Ultrafast Two Dimensional Infrared Spectroscopy of Supercritical Fluids: Energy Relaxation and Local Critical Slowing Effects." NSF-funded UROP under Lawrence Ziegler (CAS Chemistry).

• → BU CS profile
• → UROP Symposium 2021 brochure (PDF)
• → UROP 2020-2021 awarded students

Freshman year I joined Larry Ziegler's ultrafast spectroscopy lab under PhD student Matt Rotondaro. Aligned femtosecond lasers, prepared supercritical Xe and SF6 fluids, and wrote auto-correlation analysis code. Matt's thesis was on energy transfer in supercritical fluids - N2O rotational/vibrational relaxation, isolated binary collision breakdown, and near-critical density fluctuations. Working in the lab is what made me realize I liked the math and the code more than the optics bench.

• Aligned and maintained a femtosecond ultrafast laser system for 2D infrared spectroscopy.
• Prepared supercritical Xe and SF6 fluid samples for near-critical density studies.
• Wrote auto-correlation analysis code for rotational and vibrational energy relaxation traces.
• Co-authored the J. Chem. Phys. + ACS papers on N2O dynamics in supercritical solvents.

PythonNumPyUltrafast Optics2DIR SpectroscopySupercritical Fluids

• → PubMed - 2DIR Xe/SF6 (J. Chem. Phys. 2022)
• → AIP - Ultrafast 2DIR full paper
• → ACS - J. Phys. Chem. Lett.
• → Matt Rotondaro (LinkedIn)

Left Chandigarh for Boston University as an undergraduate.

Accepted to University College London, Nanyang Technological University, Boston University, NYU, and Dartmouth. Picked BU for its physics program and proximity to MIT/Harvard labs.

Sat the exam alongside ~1M candidates across India - top-percentile result.

Two years of E&M, particle physics, organic and physical chemistry, and optics - the standard JEE Advanced gauntlet for kids who wanted to do physics in India. Also sat AP Calculus, AP Physics C: Mechanics, and AP Physics C: E&M.